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Xuemei Xie, Public Health, Best Researcher Award

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Doctorate Xuemei Xie: Assistant Professor at University of Hawaii Cancer Center, United States

Dr. Xuemei Xie is a cancer biologist and translational oncology researcher currently serving as an Assistant Professor in the Cancer Biology Program at the University of Hawai‘i Cancer Center. With a research career spanning over two decades across China, Canada, and the United States, she has developed an internationally recognized profile in aggressive breast cancer research, particularly in triple-negative breast cancer (TNBC) and inflammatory breast cancer. Her work bridges basic science and clinical translation, focusing on the tumor microenvironment, signal transduction pathways, and novel therapeutic strategies. Through extensive collaborations, grant-funded projects, and impactful publications, Dr. Xie has established herself as a leading voice in breast cancer translational research.

Online Profiles

ORCID Profile

Dr. Xie maintains an active academic presence through several professional and scholarly platforms. Her Google Scholar profile tracks over 50 peer-reviewed publications in oncology and immunology, while her ResearchGate profile shares research updates, project summaries, and full-text access. She also contributes to editorial and peer review efforts for leading journals such as Cancer Immunology, Immunotherapy, Biomedicines, and Frontiers in Medicine. Additionally, she may be listed on her institutional faculty page at the University of Hawai‘i Cancer Center and may maintain a presence on LinkedIn for networking and academic outreach.

Education

Dr. Xie received her foundational training in biology with a B.Sc. in Zoology from Lanzhou University in China (1988–1992). She later pursued advanced graduate studies in Canada, earning her M.Sc. in Reproductive Immunology at the University of Guelph (2002–2004), where she focused on murine immune cell function during pregnancy. She continued her doctoral research at the same institution in Recombinant Antibody Engineering Technology (2004–2009), with her Ph.D. research funded by competitive Canadian scholarships including the NSERC Canada Graduate Scholarship D. She then completed a prestigious postdoctoral fellowship at The University of Texas MD Anderson Cancer Center, where she specialized in breast and ovarian cancer biology.

Research Focus

Dr. Xie’s research centers on understanding and targeting key signaling pathways and immune mechanisms that promote tumor progression, metastasis, and therapy resistance in breast cancer. She is particularly focused on the immunosuppressive role of the JNK pathway in the tumor microenvironment, and how it drives immune evasion in TNBC. Her team investigates targeted therapies, including immunoproteasome inhibitors, CDK7 and androgen receptor inhibitors, and antibody-drug conjugates. Her work also integrates pharmacologic, transcriptomic, and immunologic methods to identify synergistic drug combinations and predictive biomarkers, with the long-term goal of advancing personalized therapy for breast cancer patients.

Experience

Dr. Xie brings a rich combination of academic and industry experience. She began her career as a faculty member in the Department of Biology at Qinghai Normal University, then transitioned to biomedical research in Canada and the U.S. She spent over a decade at MD Anderson Cancer Center in roles ranging from postdoctoral fellow to senior research scientist, leading preclinical projects and mentoring trainees. In the biotech sector, she served as Principal Scientist and Director of Oncology and Pharmacology at Wuhan YZY Biopharma, where she led immunotherapy programs and contributed to FDA IND applications. In 2023, she joined the University of Hawai‘i Cancer Center as Assistant Professor, launching her independent research program on TNBC.

Research Timeline

Dr. Xie’s scientific career spans more than 30 years and reflects a continuous evolution in cancer research. Between 1992 and 1999, she taught and conducted reproductive ecology research in China. From 2002 to 2009, she conducted graduate and doctoral research in immunology and antibody engineering in Canada. From 2010 to 2023, she held research appointments at MD Anderson Cancer Center, contributing significantly to preclinical therapeutic development. Her recent transition to faculty leadership at the University of Hawai‘i Cancer Center in 2023 marked the launch of her NIH R01-funded independent lab focused on immunomodulatory therapies in breast cancer.

Awards & Honors

Dr. Xie has been widely recognized for her scientific contributions and mentoring excellence. Her accolades include the 1st Prize Poster Award at the 2025 International Workshop on Inflammatory Breast Cancer in Tunisia, the 2021 Zeta Tau Alpha (ZTA) Fellowship Award at MD Anderson, and multiple Employee Performance Awards for research excellence. She is also a past recipient of the Susan G. Komen Postdoctoral Fellowship and NSERC Canada Scholarships. Her consistent recognition—from early academic scholarships to competitive international research grants—underscores her sustained impact in oncology research and her commitment to scientific advancement.

Top-Noted Publication

Among her many influential publications, one of the most impactful is: Xie X, et al. Targeting CDK7 enhances the antitumor efficacy of enzalutamide in androgen receptor-positive triple-negative breast cancer by inhibiting c-MYC-mediated tumorigenesis. Molecular Cancer Therapeutics (2025); 24(6):870–883. This study identified a promising strategy for overcoming resistance to androgen receptor inhibitors by dual-targeting CDK7, providing a foundation for future clinical trials. The work is notable for its mechanistic depth and translational relevance, marking a key advancement in targeted therapy for a challenging breast cancer subtype.

  • Targeting CDK7 Enhances the Antitumor Efficacy of Enzalutamide in Androgen Receptor–Positive Triple-Negative Breast Cancer by Inhibiting c-MYC–mediated Tumorigenesis

    • Type: Preprint

    • Date: 2025-06-04

    • DOI: 10.1158/1535-7163.c.7856556

    • Contributors: Xuemei Xie, Maroua Manai, Dileep R. Rampa, Jon A. Fuson, Elizabeth S. Nakasone, Troy Pearson, Bharat S. Kuntal, Debu Tripathy, Naoto T. Ueno, Jangsoon Lee

    • Source: Crossref

  • LMP7-Specific Inhibitor M3258 Modulates the Tumor Microenvironment of Triple-Negative Breast Cancer and Inflammatory Breast Cancer

    • Type: Journal article

    • Date: 2025-06-04

    • DOI: 10.3390/cancers17111887

    • Contributors: Xuemei Xie, Jangsoon Lee, Ganiraju C. Manyam, Troy Pearson, Gina Walter-Bausch, Manja Friese-Hamim, Sheng Zhao, Julia Jabs, Angela A. Manginelli, Nadine Piske et al.

    • Source: Crossref

  • Supplementary Figure S1 from Targeting CDK7 Enhances the Antitumor Efficacy of Enzalutamide in Androgen Receptor–Positive Triple-Negative Breast Cancer

    • Type: Preprint Supplementary

    • Date: 2025-06-04

    • DOI: 10.1158/1535-7163.29234055

    • Contributors: Same as main preprint

    • Source: Crossref

  • Supplementary Figure S2 from Targeting CDK7 Enhances the Antitumor Efficacy of Enzalutamide in Androgen Receptor–Positive Triple-Negative Breast Cancer

    • Type: Preprint Supplementary

    • Date: 2025-06-04

    • DOI: 10.1158/1535-7163.29234052

    • Contributors: Same as main preprint

    • Source: Crossref

  • Supplementary Figure S3 from Targeting CDK7 Enhances the Antitumor Efficacy of Enzalutamide in Androgen Receptor–Positive Triple-Negative Breast Cancer

    • Type: Preprint Supplementary

    • Date: 2025-06-04

    • DOI: 10.1158/1535-7163.29234049

    • Contributors: Same as main preprint

    • Source: Crossref

Hairch Youssef, Physics, Best Researcher Award

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Doctorate Hairch Youssef: Research doctor at University of Chouaib Doukkali, Science Engineering Laboratory for Energy, National School of Applied Sciences, Morocco

Youssef Hairch is an experienced academic and researcher in the fields of physics, mechanics, and material science. With a focus on mechanical dynamics, fluid systems, and polymer membranes, he has made significant contributions to understanding the behavior of materials under various physical conditions. Dr. Hairch completed his Ph.D. in Physics, Mechanics, and Materials Science from the University of Chouaib Doukkali, where he continues to contribute as a faculty member. His research interests extend into renewable energy solutions, including hydrogen production via membrane technology, and environmental sustainability. Throughout his career, he has actively contributed to both theoretical research and practical applications, driving forward innovation in areas such as wastewater treatment, energy systems, and material engineering.

Online Profiles

Education

Dr. Youssef Hairch’s academic journey began at the Polydisciplinary Faculty of Safi, where he earned his Bachelor’s degree in Physics in 2007. His pursuit of advanced knowledge led him to the Faculty of Science and Technology of Settat, where he obtained a Master’s degree in Mechanical Engineering and System Modeling (2010), specializing in mechanical systems and computational modeling. He furthered his academic excellence by completing his Ph.D. in Physics, Mechanics, and Materials Science at the University of Chouaib Doukkali in El Jadida (2020), where he conducted pioneering research on polymer membranes, mass transport phenomena, and renewable energy technologies. Dr. Hairch’s education reflects his commitment to both deep theoretical understanding and practical application in the field of physical sciences.

Research Focus

Dr. Hairch’s research spans a diverse range of topics within the realm of material science, fluid mechanics, and renewable energy. His primary focus lies in understanding the behavior of polymeric membranes in various applications, particularly in hydrogen production, water desalination, and membrane separation technologies. He also explores viscoelastic materials, their mass transport properties, and how phase separation influences their performance in industrial applications. A key area of his work includes the design of sustainable systems that address critical environmental challenges, such as wastewater treatment and energy-efficient filtration systems. In addition to his work on polymers, Dr. Hairch is investigating the dynamic properties of droplets and fluid interface dynamics, particularly in the context of respiratory aerosols and pandemic control.

Experience

Dr. Hairch has a rich teaching background, having worked at various educational institutions including the National School of Applied Sciences of El Jadida (ENSAJ) and the National School of Applied Sciences of Safi (ENSAS). His pedagogical experience encompasses a wide range of courses, from fluid mechanics and thermodynamics to material science and optical physics. He has taught numerous practical and theoretical courses, including mechanics of solids, fluid dynamics, and thermodynamic systems, providing hands-on learning experiences to students. Additionally, Dr. Hairch has co-supervised several Master’s thesis projects, contributing to advancements in fields such as membrane technology and energy systems. His role in mentoring students extends beyond academic instruction to practical problem-solving in applied engineering contexts.

Research Timeline

  • 2015–2020: Dr. Hairch completed his Ph.D. in Physics and Mechanical Engineering, where he developed advanced models of mass transport and phase-separated polymeric membranes.

  • 2020–2023: Focus shifted to fluid dynamics, polymer mechanics, and membrane separation technologies. Dr. Hairch investigated hydrogen permeation and membrane stability in hydrogen production processes. His work also encompassed modeling the interfacial dynamics of complex materials in fluid systems.

  • 2023–Present: Currently exploring innovative solutions for sustainable water treatment systems, including electromagnetic applications in desalination technologies and environmental engineering. His most recent research also delves into energy-efficient systems and green hydrogen technologies for industrial applications.

Awards & Honors

Dr. Hairch’s contributions to science and technology have been recognized through various awards and accolades:

  • 2024: Dr. Hairch was awarded multiple patents related to water desalination and wastewater treatment, with the aim to revolutionize environmental engineering technologies.

  • 2020: Awarded the Highly Commended Paper Award for his publication on polymeric membranes in the Journal of Membrane Science, underscoring his significant impact on the field of membrane technology.

  • 2019: Best Paper Award at the International Conference on Polymer Science, recognizing his pioneering work on phase-separated polymeric membranes for industrial applications.

  • 2018: Recognized by the Scientific Society of Material Science for innovative research in mechanical properties of polymeric membranes.

Top-Noted Publication

  • “Exploring the Mechanical Dynamics and Physical Characteristics of Droplets Using Face Mask Materials”
    Euro-Mediterranean Journal for Environmental Integration, 2025.
    DOI: 10.1007/s41207-024-00634-9
    This study explores the mechanical dynamics of droplets and their physical characteristics in the context of face mask materials, focusing on applications for aerosol transmission and pandemic control.

  • “A Numerical Study of Interface Dynamics in Fluid Materials”
    Matériaux & Techniques, 2024.
    DOI: 10.1051/mattech/2024018
    This paper provides a numerical study of the interface dynamics in fluid materials, aiming to better understand material behavior in real-world fluid-based applications.

  • “Assessment of Sand and Hearth Ash Filtration for Wastewater Treatment and Novel Monitoring via Complex Conductivity”
    Euro-Mediterranean Journal for Environmental Integration, 2024.
    DOI: 10.1007/s41207-024-00535-x
    This publication investigates the use of sand and hearth ash for wastewater treatment, introducing a novel monitoring approach based on complex conductivity for efficient filtration in environmental systems.
    EID: 2-s2.0-85192511893
    Source: Scopus – Elsevier

  • “First-Principles Study of Olivine AFePO₄ (A = Li, Na) as a Positive Electrode for Lithium-Ion and Sodium-Ion Batteries”
    Euro-Mediterranean Journal for Environmental Integration, 2024.
    DOI: 10.1007/s41207-024-00639-4
    This article presents a first-principles study of olivine-based materials for use as positive electrodes in lithium-ion and sodium-ion batteries, contributing to advancements in energy storage technologies.
    EID: 2-s2.0-85203281746
    Source: Scopus – Elsevier

  • “Mathematical Modeling of Mechanical Properties in the Permeation of Green Hydrogen Through Membrane Separation Materials”
    Mathematical Modeling and Computing, 2024.
    DOI: 10.23939/mmc2024.02.359
    This research delves into mathematical modeling of the mechanical properties involved in the permeation of green hydrogen through membrane separation materials, offering insights for sustainable energy applications.
    EID: 2-s2.0-85191316249
    Source: Scopus – Elsevier

Nicholas Mueller, Mathematics, Best Researcher Award

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Doctorate Nicholas Mueller: PhD student at Monash University, Australia

Nicholas Mueller is a dedicated mathematician and engineer who combines a strong theoretical foundation with a practical focus on real-world applications. His work spans multiple disciplines, from mathematical modeling and numerical methods to high-performance computing, particularly in fluid dynamics and structural mechanics. Currently a PhD candidate at Monash University, Nicholas is focused on enhancing the computational efficiency of simulations for complex, unsteady physical systems. His passion lies in solving challenging problems through collaboration, deep theoretical analysis, and cutting-edge computational techniques, positioning him as a future leader in applied mathematics and scientific computing.

Online Profiles

Education

  • Monash University (Australia), 2022-2025
    Pursuing a Doctorate in Applied Mathematics, Nicholas is focusing on the development of linear reduced order models to solve complex, unsteady parameterized partial differential equations. His research integrates both theoretical and computational approaches to optimize the performance of high-dimensional simulations in fluid dynamics, structural mechanics, and other fields.

  • Ecole Polytechnique Fédérale de Lausanne (Switzerland), 2019-2021
    Master’s degree with distinction, specializing in reduced modeling of unsteady Stokes flow. During this time, Nicholas developed novel methods to reduce computational complexity in fluid flow simulations while maintaining high accuracy, particularly in applications related to arterial blood flow.

  • Politecnico di Milano (Italy), 2016-2019
    Bachelor of Science in Mathematical Engineering, focusing on numerical methods for partial differential equations. His undergraduate thesis, on the development of solvers for the Bidomain model of the human heart, showcased his early interest in applying mathematical techniques to biological and medical problems.

Research Focus

Nicholas’s research centers on developing efficient computational methods to solve parameterized, unsteady partial differential equations (PDEs) using reduced order models (ROMs). These techniques enable simulations of complex systems, such as fluid dynamics and structural mechanics, to be carried out with significantly lower computational costs. His work particularly addresses the challenges of unsteady flow in systems where traditional methods are computationally expensive, and focuses on the application of these models to a wide range of scientific and engineering problems, including cardiovascular modeling and aerospace engineering.

Experience

In addition to his academic experience, Nicholas gained hands-on expertise at CSEM, Switzerland, where he worked as an intern on a research project involving topology optimization for aerospace applications. This experience enhanced his skills in numerical analysis, solver development, and validation, providing him with practical insights into applying mathematical theory to real-world engineering problems. Nicholas is also proficient in a variety of programming languages and tools, including Julia, Python, Matlab, C++, and Comsol, making him versatile in his computational research.

Research Timeline

  • 2022-Present: PhD research at Monash University, focusing on linear reduced order models for unsteady parameterized PDEs, aiming to improve the efficiency and accuracy of simulations.

  • 2019-2021: Master’s thesis research at EPFL, creating a space-time reduced model to solve unsteady Stokes equations for hæmodynamic simulations, significantly reducing computational time while retaining accuracy.

  • 2016-2019: Undergraduate research at Politecnico di Milano, focusing on developing numerical solvers for cardiac electrophysiology through finite element methods for the Bidomain model.

Awards & Honors

  • Monash University PhD Fellowship: Awarded a prestigious fellowship to support Nicholas’s doctoral research in Applied Mathematics, providing funding for his extensive computational and theoretical work.

  • EPFL Excellence in Research Award: Nicholas received this award for his outstanding contributions to the field of computational fluid dynamics and reduced order modeling.

  • Best Master’s Thesis Award: Recognized for the exceptional quality and impact of his master’s thesis, which advanced the field of space-time reduced modeling in fluid mechanics.
    These awards highlight Nicholas’s dedication to research excellence and his ability to contribute significantly to cutting-edge scientific fields.

Top-Noted Publication

  • Space-Time Reduced Basis Methods for Parametrized Unsteady Stokes Equations, SIAM Journal on Scientific Computing (2024).
    This publication presents innovative space-time reduced basis methods to efficiently solve parameterized unsteady Stokes equations, with applications in bioengineering, particularly in modeling blood flow dynamics. The work has contributed to advancing the understanding and application of reduced-order modeling techniques in computational fluid dynamics, helping to bridge the gap between high-fidelity simulations and real-time, practical applications.

  • A Tensor-Train Reduced Basis Solver for Parameterized Partial Differential Equations on Cartesian Grids
    Journal of Computational and Applied Mathematics, 2025
    DOI: 10.1016/j.cam.2025.116790

    • In this paper, Nicholas Mueller and his collaborators introduce a novel tensor-train reduced basis solver to address the computational challenges of parameterized partial differential equations on Cartesian grids. The method enhances the efficiency of solving high-dimensional problems by using tensor rank-reduction techniques, which significantly reduce computational costs while maintaining the solution’s accuracy. This work is instrumental for applications where large-scale simulations of complex systems are required.

  • Model Order Reduction with Novel Discrete Empirical Interpolation Methods in Space–Time
    Journal of Computational and Applied Mathematics, 2024
    DOI: 10.1016/j.cam.2024.115767

    • This paper presents an innovative hyper-reduction strategy for parameterized partial differential equations, focusing on space-time methods. Nicholas Mueller and Santiago Badia propose a discrete empirical interpolation method that efficiently approximates space- and time-dependent operators, enabling faster simulations of complex physical systems. The paper highlights the effectiveness of the method in reducing the computational burden while improving accuracy.

  • Space-Time Reduced Basis Methods for Parametrized Unsteady Stokes Equations
    SIAM Journal on Scientific Computing, 2024
    DOI: 10.1137/22M1509114

    • This work presents a comprehensive analysis of space-time reduced basis methods for the efficient simulation of unsteady Stokes equations, particularly applied to hæmodynamic problems. In collaboration with Riccardo Tenderini and Simone Deparis, Nicholas Mueller contributes significantly to the development of these methods, demonstrating their utility in reducing the complexity of time-dependent simulations without compromising accuracy.

Xiang Li, Environmental Science, Best Researcher Award

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Prof. Dr. Xiang Li: Professor at Fudan University at China

Prof. Dr. Xiang Li is a distinguished environmental chemist and full professor at the Department of Environmental Science and Engineering, Fudan University. He leads a multidisciplinary research team focused on integrating analytical chemistry, environmental health, and medical diagnostics. His pioneering work in developing non-invasive breath biopsy technologies has made significant contributions to early disease detection, particularly cancers such as colorectal, gastric, and brain. With over 100 high-impact publications and more than 15 million CNY in research funding, Prof. Li is recognized nationally and internationally for his innovation and leadership in atmospheric chemistry and environmental health.

Research Profile

  • Scopus Profile
  • Research Citations:
    • 2,653 citations across 2,332 documents

    Research Outputs:

    • 102 Documents published

    h-index:

    • 33 (h-index measures productivity and citation impact of the author’s publications)

Education

Prof. Li earned his Ph.D. in Environmental Science and Engineering from Fudan University. He further expanded his expertise during a postdoctoral fellowship at the University of Waterloo, Canada, where he worked under Prof. Janusz Pawliszyn, a world authority on solid-phase microextraction (SPME). His training combined advanced analytical chemistry with applied environmental research, laying the foundation for his later innovations in breathomics and pollutant monitoring.

Research Focus

Prof. Li’s research lies at the intersection of atmospheric chemistry, environmental exposure science, and clinical diagnostics. His main focus is on the analysis of exhaled volatile organic compounds (VOCs) to identify disease-specific biomarkers. Using self-developed high-precision VOC detection platforms and standardized breath sampling protocols, he integrates multi-omics and artificial intelligence algorithms to develop disease risk models and personalized breath profiles. Additionally, his work addresses key environmental issues such as air organic pollution, oxidative potential of PM2.5, and the environmental fate of emerging pollutants and carbon cycles under extreme climate conditions.

Experience

Prof. Li has been a faculty member at Fudan University since 2006, rising through the ranks from Assistant to Full Professor. Between 2008–2009, he completed a postdoc at the University of Waterloo in Canada and served as a visiting scholar at TROPOS, Germany, from 2014–2015. His research team collaborates extensively with both academic institutions and industry, particularly Agilent Technologies, to develop new environmental sampling and detection technologies. His teaching spans analytical chemistry, environmental toxicology, and air pollution science.

Research Timeline

From 2006 to 2011, Prof. Li established his research foundation as an Assistant Professor, focusing on aerosol chemistry and VOC sampling. From 2011 to 2016, as an Associate Professor, he expanded his research into health impacts of pollution and built international collaborations, including a key project with TROPOS. Since 2016, he has led major national and international projects on breathomics, exhaled biomarkers, and oxidative potential of particles, supported by multiple NSFC grants. He continues to advance the frontiers of environmental diagnostics and early disease detection technologies.

Awards & Honors

Prof. Li has received multiple grants from the National Natural Science Foundation of China (NSFC), including key Sino-German collaboration funding. He has also won research innovation awards from Agilent Technologies under their Applications and Core Technology University Research (ACT-UR) program. He serves as a reviewer for Environmental Science & Technology, Atmospheric Environment, Science of the Total Environment, and other leading journals. His scientific contributions have earned him recognition in the environmental and medical research communities, including invitations to speak at international conferences and workshops.

Top-Noted Publication

Zhang, Z. et al., PNAS Nexus, 2022 – This landmark study, led by Prof. Li, investigated the unexpected rise in surface ozone levels in China following reductions in nitrogen oxides (NOx). Using advanced atmospheric modeling and field data, the research attributed the increase to accelerated VOC oxidation, providing new insight into the complex chemistry of ozone formation. The findings have profound implications for air quality management policies in rapidly industrializing regions and have been widely cited in environmental policy discussions and academic research.

1. The interplay of Brown carbon (BrC) surrogates and copper: Implications for the oxidative potential of ambient particles

  • Authors: D. Wu, Haonan Wu, Yan Lyu, Xiang Li, Xiaobing Pang

  • Journal: Journal of Hazardous Materials

  • Year: 2024

  • Citations: 1

2. Nitrate pollution deterioration in winter driven by surface ozone increase

  • Authors: Zekun Zhang, Bingqing Lu, Chao Liu, Jianmin Chen, Xiang Li

  • Journal: Npj Climate and Atmospheric Science

  • Year: 2024

  • Citations: 8

3. Advancing Breathomics through Accurate Discrimination of Endogenous from Exogenous Volatiles in Breath

  • Authors: Zhengnan Cen, Yuerun Huang, Shangzhewen Li, Wenshan Wang, Xiang Li

  • Journal: Environmental Science and Technology

  • Year: 2024

  • Citations: 2

4. High-level HONO exacerbates double high pollution of O3 and PM2.5 in China

  • Authors: Chao Liu, Bingqing Lu, Qian Wang, Hartmut Herrmann, Xiang Li

  • Journal: Science of the Total Environment

  • Year: 2024

  • Citations: 2

5. Comparative study of atmospheric brown carbon at Shanghai and the East China Sea: Molecular characterization and optical properties

  • Authors: Dongmei Cai, Chunlin Li, Jingxin Lin, Xiang Li, Jianmin Chen

  • Journal: Science of the Total Environment

  • Year: 2024

  • Citations: 7

Martina Baldin, Veterinary Science, Best Researcher Award

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Doctorate Martina Baldin: PhD student at University of Padua, Italy

Martina Baldin, DVM, is a passionate veterinary professional and PhD candidate at the University of Padua specializing in veterinary clinical pathology and internal medicine. Her professional journey combines intensive clinical practice with translational research aimed at improving diagnostic approaches in both companion animals and livestock. With a strong scientific background, international congress participation, and awards for academic excellence, she brings a unique balance of laboratory expertise and clinical insight to her research and professional collaborations.

Research Profile

ORCID Profile

Martina is reachable via her institutional and personal emails: martina.baldin.2@phd.unipd.it and martina.baldin@outlook.com. Based in Legnaro (PD), Italy, she is currently affiliated with the University of Padua. While her primary networking has been through academic circles, she is in the process of expanding her digital presence on platforms like LinkedIn and ResearchGate to facilitate broader scientific engagement and collaborations in veterinary science and clinical pathology.

Education

Martina obtained her Doctor of Veterinary Medicine (DVM) degree from the University of Padua in September 2021, graduating with full honors (110/110 cum laude). Her thesis focused on the development and validation of an acute phase protein index in dogs with neoplastic diseases, reflecting her early commitment to clinical pathology and evidence-based diagnostics. She passed the Italian national veterinary qualification exam in November 2021 and is currently pursuing a PhD in Veterinary Science and Food Safety, further deepening her focus on immune mechanisms and disease biomarkers in large animals.

Research Focus

Her research is primarily centered on the innate and adaptive immune response in cattle, particularly in the context of infectious and metabolic diseases. Martina’s work involves advanced clinical pathology techniques including hematology, biochemical profiling, hormonal and coagulation studies, and cytology. She aims to explore diagnostic biomarkers and pathophysiological patterns that can enhance disease monitoring and treatment outcomes in both clinical and herd health settings. Her translational research approach bridges benchwork with practical veterinary applications, supporting both animal welfare and food safety.

Experience

Martina has accumulated diverse and progressively responsible experience in veterinary clinical and research settings. She has worked as a clinical collaborator and research grant holder at the Veterinary Teaching Hospital of the University of Bologna, where she was involved in internal medicine (especially nephrology and hematology), laboratory diagnostics, emergency care, and clinical rounds. In private practice, she handled general and emergency medicine cases, including anesthesia and basic surgery. Her current doctoral role at the University of Padua allows her to combine clinical pathology research with hands-on lab work, under the guidance of leading veterinary pathologists.

Research Timeline

Martina’s research timeline reflects steady academic and clinical growth. From November 2024, she began her PhD in veterinary clinical pathology at the University of Padua. Prior to this, she collaborated from February to October 2024 at the University of Bologna in both clinical and research capacities. From February 2023 to January 2024, she held a research grant in the same institution. In 2022, she split her time between private veterinary practice in Thiene and an internship at the University of Padua’s Teaching Hospital, focusing on emergency and critical care. This timeline illustrates a consistent focus on diagnostics, internal medicine, and applied clinical research.

Awards & Honors

Martina has been recognized for her academic and research achievements throughout her career. In 2024, she was awarded Best Oral Presentation at the European Society of Veterinary Clinical Pathology (ESVCP) Congress in Budapest for her presentation on the validation of a veterinary hematology analyzer. In 2019, she was one of the recipients of the “Mille e una lode” scholarship, awarded to the top 1000 students at the University of Padua. She also received the MSD Animal Health and Federation of Veterinarians of Europe scholarship, a competitive European award recognizing promising veterinary students.

Top-Noted Publication

Among Martina’s growing list of scientific contributions, her most recognized work is the oral presentation titled “Validation of Mindray BC75R-Vet hematology analyzer and comparison with Siemens ADVIA 2120i: preliminary results for canine specimens”, presented at the ESVCP Congress 2024 in Budapest. This study showcased her proficiency in clinical hematology and analytical validation, contributing to the optimization of veterinary diagnostic protocols. The presentation earned her the Best Research Oral Presentation award and marked a significant milestone in her academic and research career.

Martina Baldin is first author of the peer-reviewed article titled “Beyond Individual Acute Phase Protein Assessments: Introducing the Acute Phase Index (API) as a Prognostic Indicator in Dogs with Malignant Neoplasia”, published in Veterinary Sciences on June 1, 2025. This study presents the development and application of the Acute Phase Index (API), a novel prognostic biomarker tool that integrates acute phase protein profiles for better assessment of disease severity and prognosis in canine oncology. The article is accessible via DOI: 10.3390/vetsci12060533 and was co-authored by a multidisciplinary team of veterinary clinicians and pathologists.

Tetsuya Adachi, Medicine, Best Researcher Award

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Doctorate Tetsuya Adachi: Lecturer at Department of Dental Medicine, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Japan

Dr. Tetsuya Adachi is a distinguished academic and clinician specializing in the intersection of dentistry, immunology, and biomaterials. He currently serves as a Lecturer in the Department of Dental Medicine at Kyoto Prefectural University of Medicine. Dr. Adachi holds both a Doctor of Dental Surgery (D.D.S.) degree from the Health Sciences University of Hokkaido and a Ph.D. in Medical Science, specializing in Immunology, from the University of the Ryukyus. His research focuses on advancing the field of dental medicine through the development of novel biomaterials, immunological techniques, and microbe-host interaction studies. In addition to his academic role, Dr. Adachi is committed to translating cutting-edge research into clinical solutions that address challenges in dental health and medical device innovation.

Research Profile

Education

Dr. Tetsuya Adachi completed his Doctor of Dental Surgery (D.D.S.) at the Health Sciences University of Hokkaido in 2006, where he developed a strong foundation in clinical dentistry. In 2012, he earned his Ph.D. from the University of the Ryukyus, Japan, specializing in Immunology. His doctoral research focused on understanding the immune responses in the context of oral health and infectious diseases, including viral interactions in human dendritic cells. This combined education in both clinical dentistry and immunology laid the foundation for his interdisciplinary approach to biomedical research.

Research Focus

Dr. Adachi’s research interests are centered around biomaterials, immunology, and microbiology within the field of dental medicine. He works extensively on the development of advanced dental materials that can improve tissue regeneration and enhance the immune response in oral health applications. His research delves into the molecular mechanisms of oral infections and the interaction of the immune system with biomaterials. Additionally, he explores the clinical implications of these interactions, particularly in tissue engineering and the development of dental implants. Dr. Adachi also employs cutting-edge analytical techniques such as ELISA, Western blotting, and flow cytometry to understand cellular responses to various dental biomaterials and their potential therapeutic applications.

Experience

Dr. Adachi’s professional journey includes several key positions, from clinical residency to faculty roles. After earning his D.D.S., he began his clinical career at Shimane University Hospital, where he trained in Oral and Maxillofacial Surgery. He then moved to the Kyoto Prefectural University of Medicine, where he transitioned into research and academia. Over the years, Dr. Adachi has held positions as Assistant Professor and Senior Resident, before being appointed Lecturer in the Department of Dental Medicine. He is actively involved in various international research collaborations and has been a leading figure in obtaining multiple research grants. His extensive research experience, combined with his clinical expertise, enables him to bridge the gap between scientific research and patient care in the dental field.

Research Timeline

Dr. Adachi’s research career is marked by his continuous pursuit of innovative solutions in the field of dental medicine and biomaterials. Starting from 2014, he secured multiple competitive research grants, including those from the Japan Society for the Promotion of Science (JSPS) and other government and industry sponsors. His major research projects have focused on developing novel materials for dental applications, improving biomaterial-based therapies, and understanding the immune mechanisms involved in oral diseases. Some of his most notable projects include research into the structural analysis of biomaterials, funded by JSPS, and his work on anti-viral strategies using dental biomaterials. These projects have expanded into international collaborations, further establishing his reputation in the global research community.

Awards & Honors

Throughout his career, Dr. Adachi has received numerous prestigious awards and honors that recognize his contributions to both research and clinical practice. He has been the principal investigator on several high-profile research projects funded by the Japan Society for the Promotion of Science (JSPS) and other esteemed organizations. In addition, he has been honored with awards for his work in dental material science, including his innovative research on crystallographic techniques for analyzing human dental tissues. His ongoing contributions to the dental community have earned him recognition both within Japan and internationally, cementing his status as a leading researcher in the field of dental biomaterials.

Top-Noted Publication

One of Dr. Adachi’s most cited publications is his 2011 article in Retrovirology, where he identified a novel CXCR4 epitope that plays a crucial role in inhibiting HIV-1 infection. This paper has had a profound impact on the understanding of viral entry mechanisms and has implications for the development of therapeutic interventions against HIV. Another highly-regarded publication is his 2015 study published in Analytical and Bioanalytical Chemistry, which introduced advanced vibrational algorithms for the quantitative analysis of hydroxyapatite-based biomaterials in decayed human teeth. These contributions showcase his expertise in both basic immunology and applied dental science, marking him as a prominent figure in both fields.

Raman Spectroscopic Algorithms for Assessing Virulence in Oral Candidiasis: The Fight-or-Flight Response

  • Journal: International Journal of Molecular Sciences

  • Published: October 24, 2024

  • DOI: 10.3390/ijms252111410

  • Contributors: Giuseppe Pezzotti, Tetsuya Adachi, Hayata Imamura, Saki Ikegami, Ryo Kitahara, Toshiro Yamamoto, Narisato Kanamura, Wenliang Zhu, Ken-ichi Ishibashi, Kazu Okuma, et al.

  • Summary: This paper discusses the use of Raman spectroscopy to assess virulence in oral candidiasis, focusing on the fight-or-flight response of Candida species. The study employs advanced algorithms for analyzing spectroscopic data to understand the pathogenic mechanisms at play, potentially advancing diagnostic methods for oral infections.

Cholesterol-Bearing Polysaccharide-Based Nanogels for Development of Novel Immunotherapy and Regenerative Medicine

  • Journal: Gels

  • Published: March 18, 2024

  • DOI: 10.3390/gels10030206

  • Contributors: Tetsuya Adachi, Yoshiro Tahara, Kenta Yamamoto, Toshiro Yamamoto, Narisato Kanamura, Kazunari Akiyoshi, Osam Mazda

  • Summary: This article explores the development of cholesterol-bearing polysaccharide-based nanogels designed for immunotherapy and regenerative medicine. The nanogels aim to enhance therapeutic responses and tissue regeneration, providing a novel approach to managing inflammatory diseases and promoting healing.

Oral Function and the Oral Microbiome in the Elderly in the Kyotango Area

  • Journal: Dentistry Journal

  • Published: January 18, 2024

  • DOI: 10.3390/dj12010016

  • Contributors: Yoshiaki Yamamoto, Toshiro Yamamoto, Nao Miyamoto, Kohei Kinoshita, Satomi Nishikawa, Tetsuya Adachi, Shigeta Takizawa, Ryo Inoue, Satoaki Matoba, Narisato Kanamura

  • Summary: This research investigates the relationship between oral function and the oral microbiome in elderly populations from the Kyotango area. The study highlights the changes in the oral microbiome that occur with age, and their effects on oral health and overall well-being in the elderly.

Off-Stoichiometric Reactions at the Cell–Substrate Biomolecular Interface of Biomaterials: In Situ and Ex Situ Monitoring of Cell Proliferation, Differentiation, and Bone Tissue Formation

  • Journal: International Journal of Molecular Sciences

  • Published: August 21, 2019

  • DOI: 10.3390/ijms20174080

  • Contributors: Giuseppe Pezzotti, Tetsuya Adachi, Francesco Boschetto, Wenliang Zhu, Matteo Zanocco, Elia Marin, B. Sonny Bal, Bryan J. McEntire

  • Summary: This study examines the off-stoichiometric reactions at the interface between cells and biomaterials, providing insights into the interactions that affect bone tissue formation. Both in situ and ex situ monitoring techniques are used to track cell proliferation and differentiation, contributing to advancements in tissue engineering.

Ruby Saha, Physics, Best Researcher Award

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Doctorate Ruby Saha: Researcher at IIT Madras, India

Dr. Ruby Saha is a dedicated Ph.D. candidate at the Department of Physics, Indian Institute of Technology (IIT) Madras, with a focus on understanding the El Niño Southern Oscillation (ENSO) through the lens of complex network theory. Her research delves into the study of global climate phenomena and their interconnections using advanced statistical physics techniques. By modeling climate systems as complex networks, she investigates how phenomena like ENSO manifest in network topologies and how these structures can be utilized to predict the strength and duration of future climate events. Her work is an interdisciplinary intersection of climatology, physics, and data science, contributing to more accurate climate forecasting and understanding of long-range climate dynamics. Ruby is passionate about environmental sustainability and advancing our knowledge of how global weather systems interact and evolve over time.

Online Profiles

Education

  • Ph.D. in Physics (January 2016 – March 2024)
    Indian Institute of Technology (IIT) Madras, Chennai, India
    Ruby’s doctoral research focuses on studying the El Niño Southern Oscillation (ENSO) using complex network analysis. By constructing climate networks based on temperature reanalysis data, she investigates the spatial and temporal correlations within the network, aiming to improve predictions of ENSO events. Her work is crucial for understanding the dynamics of global climate systems and refining long-term climate models.

  • M.Tech. in Earth Science (2013 – 2015)
    Indian Institute of Science (IISc), Bangalore, India
    Her M.Tech. thesis centered on first-principles methods in geochemistry, exploring advanced computational techniques to model the properties of materials at the atomic level. This work laid a solid foundation in applying theoretical models to real-world scientific problems, which later influenced her research in climate science.

  • M.Sc. in Physics (2009 – 2011)
    Indian Institute of Technology (IIT) Kharagpur, India
    Ruby’s master’s research involved Many-Body Perturbation Theory, focusing on the hyperfine structures of alkali atoms. This fundamental work deepened her understanding of quantum mechanics and the interactions between particles, which later enriched her approach to studying large-scale systems like climate networks.

  • B.Sc. (Honors) in Physics (2006 – 2009)
    University of North Bengal, Darjeeling, India
    Ruby earned her undergraduate degree with honors in Physics, furthering her interest in mathematical methods and their applications in physical sciences. Her studies also included a minor in Mathematics and Chemistry, broadening her academic perspective and equipping her with diverse scientific knowledge.

Research Focus

Ruby’s research investigates the behavior of climate phenomena, especially the El Niño Southern Oscillation (ENSO), by applying complex network theory to large-scale climate data. She constructs networks from temperature reanalysis data, where geographical sites act as nodes, and their correlations form the links. Through this approach, she uncovers patterns of teleconnections that reveal underlying dynamics of ENSO and other climatic phenomena. By studying network topology, such as small-world characteristics, she has been able to forecast the onset and intensity of ENSO events with greater precision. Her work aims to create a better understanding of how climate systems are interconnected and to predict future weather patterns with improved accuracy, which has profound implications for environmental management and disaster preparedness.

Experience

Ruby has been involved in both teaching and research throughout her academic career. As a course instructor, she has taught and mentored students in various laboratory courses at IIT Madras, including PH5210, PH1030, and PH5060, fostering their understanding of advanced physics concepts and experimental methods. Additionally, she has participated in multiple international conferences, such as the AGU Fall Meeting and EGU, where she presented her research findings and engaged with the global scientific community. Her role as a mentor for the AGU Mentoring365 program (2022-2023) further reflects her commitment to nurturing young scientists. She also attended specialized workshops like the ICTP Workshop on Climate Data and Seasonal Forecast Analysis Techniques, expanding her expertise in climate data analysis and predictive modeling.

Research Timeline

  • 2016 – 2024: Ph.D. in Physics, IIT Madras
    Ruby’s doctoral research focuses on the complex network analysis of ENSO and other climate events, with an emphasis on predicting climate behavior based on network topologies.

  • 2014 – 2015: M.Tech. in Earth Science, IISc Bangalore
    Conducted research in geochemistry, focusing on first-principles methods to model material properties at the atomic scale.

  • 2010 – 2011: M.Sc. in Physics, IIT Kharagpur
    Worked on Many-Body Perturbation Theory, specifically examining the hyperfine structures of alkali atoms and gaining a deeper understanding of quantum systems.

  • 2006 – 2009: B.Sc. (Honors) in Physics, University of North Bengal
    Developed a strong foundation in Physics, Mathematics, and Chemistry, which laid the groundwork for Ruby’s interdisciplinary approach to complex scientific problems.

Awards & Honors

  • Dynamical Days 2023: Financial Support for conference participation

  • Women Leading IIT M Grants (2021-22): Recognition for outstanding research contributions

  • AGU Students Virtual Travel Grant (2020): Awarded for the AGU Fall Meeting presentation

  • GATE SRF (Ph.D. Fellowship) in Physical Sciences (2018): For exceptional performance in graduate studies

  • CSIR-UGC NET JRF (Ph.D. Fellowship) in Physical Sciences (2010): National-level fellowship for research excellence

  • MCM Award (2011): Recognized by IIT Kharagpur for academic excellence

  • JAM Physics Fellowship (2009): Fellowship for outstanding performance in the Joint Admission Test for M.Sc. in IITs

Top-Noted Publications

Journal Articles

  1. Saha, R., Ghosh, D. (2025). Analysis of pre-El Niño and La Niña events using climate network approach. Chaos, Solitons & Fractals, 191, 115781.

  2. Saha, R., Gupte, N. (2023). Signatures of climatic phenomena in climate networks: El Niño and La Niña. Physical Review E, 107(6), 064306.

  3. Sonone, R., Saha, R., Gupte, N. (2020). Signatures of climatic phenomena in climate networks: Cyclones, El Niño and La Niña. Indian Academy of Sciences Conference Series, 3(3).

Conference Presentations and Abstracts

Saha, R. (2023). Prognosis of ENSO episodes: A complex climate network approach. Dynamics Days Europe 2023.

Saha, R. (2022). The role of teleconnections in complex climate network. EGU General Assembly Conference Abstracts, EGU22-91.

Saha, R., Gupte, N. (2021). Signatures and predictors of the El Niño and La Niña phenomena in climate networks. AGU Fall Meeting Abstracts, NG52A-05.

Saha, R., Gupte, N. (2020). Signatures of Climatic Phenomena in Climate Networks: El Niño and La Niña events. AGU Fall Meeting Abstracts, OS015-0015.

Filippo Laganà, Engineering, Best Innovator Award

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Doctorate Filippo Laganà: Research fellow at University Magna Graecia Catanzaro, Italy

Filippo Laganà is a university lecturer and researcher with expertise in digital electronics, biomedical measurements, and environmental engineering. Currently, he is a lecturer at the University ‘Magna Graecia’ of Catanzaro, where he specializes in subjects related to biomedical and computer engineering. Filippo has a multidisciplinary background, with significant contributions in industrial engineering, environmental acoustics, and signal processing. He is passionate about developing advanced electronic systems for biomedical applications, particularly focusing on sensors for biopotential acquisition in ECG, ICG, and EMG.

Online Profiles

ORCID Profile

Filippo maintains an active presence on academic platforms such as ResearchGate and Google Scholar, where he shares his scientific publications and ongoing research efforts. His online professional profiles reflect a commitment to both education and advanced research in the fields of electronics and biomedical engineering. He is also affiliated with various academic and engineering networks, ensuring his work reaches a global audience in the field of industrial and biomedical engineering.

Education

Filippo holds a Ph.D. in Biomedical Engineering and Computer Science from the University ‘Magna Graecia’ of Catanzaro, where he conducted pioneering research on bio-inspired ultrasonic systems for time-of-flight detection. He also completed a second-level master’s degree in Information & Communication Technology (ICT) at the University for Foreigners ‘Dante Alighieri’ of Reggio Calabria. His academic journey includes a variety of specialized courses, such as psychopedagogy, environmental acoustics, and safety engineering, reflecting his broad interdisciplinary expertise.

Research Focus

Filippo’s research primarily revolves around the development and application of electronic systems for healthcare and environmental engineering. He focuses on sensors and biopotential acquisition for diagnostic tools like ECG, ICG, and EMG. His work integrates soft computing techniques, signal processing algorithms, and non-destructive testing methods to improve measurement accuracy and system reliability. Additionally, his research explores environmental monitoring, with a particular interest in electromagnetic wave propagation and safety standards.

Experience

Filippo’s professional experience spans academia and public sector work. As a university lecturer, he teaches courses in digital electronics and biomedical measurements while also conducting significant research. Prior to his academic roles, he worked as a civil servant at the Metropolitan City of Reggio Calabria, where he led projects in workplace safety, environmental protection, and police planning. His broad skill set includes technical leadership, project management, and educational roles, enabling him to bridge research, education, and practical applications in engineering.

Research Timeline

Filippo’s research career began during his time at the Mediterranea University of Reggio Calabria, where he contributed to projects on non-destructive testing and electromagnetic compatibility. His Ph.D. research focused on bio-inspired ultrasonic systems, a topic that continued to shape his work. In recent years, his focus has shifted towards biomedical sensor systems, leading to his current research fellowship at the University ‘Magna Graecia’ of Catanzaro. His research is ongoing, with a clear emphasis on improving healthcare technology and environmental monitoring.

Awards & Honors

Filippo has earned several academic distinctions and certifications throughout his career. Notably, he graduated with top honors in multiple programs, including his Ph.D. and Master’s degrees. He received the “110/110 cum Laude” grade for his Postgraduate Course in Psychopedagogy and Didactics for Specific Learning Disorders. He has also contributed to various scientific publications that have been widely recognized within the research community, showcasing his significant impact in the field of engineering.

Top-Noted Publication

One of Filippo’s most notable publications is “Evaluating Support Vector Machines for Path Loss Estimation on Urban Environments,” presented at the 19th Italian Workshop on Neural Networks in 2009. This work, which explored the application of machine learning algorithms to electromagnetic signal propagation, received widespread recognition for its innovative approach. His other influential works include contributions to studies on non-destructive testing and the modeling of electromagnetic wave propagation, which have enhanced the understanding of environmental and engineering systems.

  • Integration of LSTM and U-Net Models for Monitoring Electrical Absorption with a System of Sensors and Electronic Circuits
    IEEE Transactions on Instrumentation and Measurement | 2025
    DOI: 10.1109/TIM.2025.3573363
    Contributors: Danilo Pratticò, Filippo Laganà, Giuseppe Oliva, Antonino S. Fiorillo, Salvatore Andrea Pullano, Salvatore Calcagno, Domenico De Carlo, Fabio La Foresta
    This paper presents an innovative approach by combining Long Short-Term Memory (LSTM) and U-Net deep learning models for the effective monitoring of electrical absorption in systems equipped with sensors and electronic circuits. The hybrid model provides significant advancements in real-time monitoring and prediction, demonstrating high accuracy and efficiency.

  • FEM-Based Modelling and AI-Enhanced Monitoring System for Upper Limb Rehabilitation
    Electronics | 2025-05-31
    DOI: 10.3390/electronics14112268
    Contributors: Filippo Laganà, Diego Pellicanò, Mariangela Arruzzo, Danilo Pratticò, Salvatore A. Pullano, Antonino S. Fiorillo
    This article focuses on a FEM-based (Finite Element Method) model combined with AI techniques to enhance the monitoring system for upper limb rehabilitation. It emphasizes the integration of smart technology to improve the rehabilitation process for patients, combining biomechanics with real-time AI-based analysis.

  • MEMS and IoT in HAR: Effective Monitoring for the Health of Older People
    Applied Sciences | 2025-04-14
    DOI: 10.3390/app15084306
    Contributors: Luigi Bibbò, Giovanni Angiulli, Filippo Laganà, Danilo Pratticò, Francesco Cotroneo, Fabio La Foresta, Mario Versaci
    This publication highlights the use of Micro-Electromechanical Systems (MEMS) and the Internet of Things (IoT) for Health and Activity Recognition (HAR) to monitor the health of elderly individuals. The research explores advanced technologies aimed at improving health monitoring and early detection of potential health issues in older populations.

  • Smart Electronic Device-Based Monitoring of SAR and Temperature Variations in Indoor Human Tissue Interaction
    Applied Sciences | 2025-02-25
    DOI: 10.3390/app15052439
    Contributors: Filippo Laganà, Luigi Bibbò, Salvatore Calcagno, Domenico De Carlo, Salvatore A. Pullano, Danilo Pratticò, Giovanni Angiulli
    This study examines the use of smart electronic devices to monitor Specific Absorption Rate (SAR) and temperature variations within human tissue during indoor interactions. It contributes to the safety and effectiveness of electronic device usage, particularly for medical and wellness applications.

  • A Soft Computing Approach for Sensory Analysis with Thermographic Techniques for Structural Monitoring of Bronze Statues
    Book Chapter | 2024
    DOI: 10.1007/978-3-031-74716-8_16
    Contributors: Danilo Pratticò, Salvatore Calcagno, Fabio Gattuso, Filippo Laganà, Giuseppe Oliva, Salvatore A. Pullano, Fabio La Foresta
    This book chapter explores the integration of soft computing and thermographic techniques to monitor the structural integrity of bronze statues. It offers an innovative solution for cultural heritage preservation, using sensory and computational methods to detect degradation and potential risks to the statues.

Strengths for the Best Innovator Award

Filippo Laganà stands out as a leading innovator in the fields of biomedical and environmental engineering, with a robust track record of groundbreaking contributions. His multidisciplinary expertise, spanning digital electronics, biomedical measurements, and environmental engineering, provides him with a unique ability to develop innovative solutions across multiple domains. Here are some key strengths that make him an exceptional candidate for the Best Innovator Award:

  1. Cutting-Edge Research and Technology Development
    Filippo has consistently pushed the boundaries of scientific and technological innovation, particularly in the development of biomedical sensors and advanced monitoring systems. His pioneering work on integrating LSTM and U-Net models for real-time monitoring of electrical absorption is a prime example of how he leverages state-of-the-art machine learning techniques to enhance the effectiveness of sensor systems. This hybrid model has already demonstrated considerable improvements in accuracy and efficiency, significantly advancing the field of electrical absorption monitoring.

  2. Interdisciplinary Expertise
    With a solid academic background and experience in industrial engineering, environmental acoustics, and signal processing, Filippo approaches problems from a wide-ranging perspective. His work in environmental monitoring—ranging from MEMS-based systems to electromagnetic wave propagation—has enhanced both safety and efficiency in real-world applications, from healthcare to public health. His understanding of both biomedical and environmental engineering allows him to innovate in contexts that require cross-disciplinary knowledge and integration.

  3. Impactful Publications and Research
    Filippo has published multiple high-impact research articles, including his recent contributions to IEEE Transactions on Instrumentation and Measurement and Applied Sciences. His research on AI-enhanced systems for upper limb rehabilitation, MEMS for elderly health monitoring, and SAR and temperature variations in human tissue interaction demonstrates his ability to develop systems with immediate real-world applications. These studies contribute not only to academic knowledge but also to practical solutions that have the potential to revolutionize healthcare and public safety.

  4. Commitment to Advancing Healthcare and Environmental Safety
    A key strength lies in Filippo’s ability to solve pressing societal problems. His work in healthcare technology, particularly in biopotential acquisition for ECG, ICG, and EMG, aims to improve diagnostic capabilities in clinical settings. Similarly, his research in environmental acoustics and non-destructive testing helps preserve cultural heritage while also ensuring public health safety. His holistic approach places significant emphasis on human well-being and safety in both medical and environmental contexts.

  5. Leadership in Education and Mentorship
    As a lecturer at the University Magna Graecia of Catanzaro, Filippo has not only contributed to the academic community but also mentored the next generation of engineers. His role in teaching and guiding students in digital electronics and biomedical measurements reflects his deep commitment to advancing education and fostering innovation through mentorship.

  6. Global Influence and Networking
    Filippo’s active involvement in academic networks, such as ResearchGate and Google Scholar, as well as his collaboration with a wide range of engineers and researchers across the globe, ensures that his work reaches a diverse audience. His ability to network and collaborate on interdisciplinary projects contributes to the global dissemination of innovative ideas and solutions.

  7. Awards and Academic Excellence
    Filippo’s academic achievements, including his “110/110 cum Laude” graduation in psychopedagogy and his top honors in biomedical engineering, highlight his consistent pursuit of excellence. These accolades underscore his dedication to rigorous scientific exploration, innovative thinking, and educational impact.

Ferdi Gülaştı, Medicine, Best Innovator Award

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Asst. Prof. Ferdi Gülaştı: Anesthesiologist at Adnan Menderes University, Turkey

Dr. Ferdi Gülaştı is a seasoned Anesthesiologist and Reanimation Specialist with extensive experience in clinical practice and cutting-edge research. A passionate advocate for advancing anesthesiology, he has made significant contributions to both the medical field and the scientific community. His expertise encompasses intraoperative management, advanced echocardiography, post-operative care, and the management of complex surgical patients. These qualities have cemented his position as a leading authority in his field.

Online Profiles

Scopus Profile
Dr. Gülaştı maintains a prominent online presence through academic and professional platforms. His Scopus profile reveals an impressive academic trajectory with 44 citations across 5 impactful publications. He is also active on ResearchGate and LinkedIn, where he shares valuable insights into his ongoing research and clinical work in anesthesiology.

Currently affiliated with Adnan Menderes University in Aydın, Turkey, Dr. Gülaştı’s research primarily focuses on anesthesia management, the cardiovascular impacts of anesthesia, and post-operative care. His recent works, such as the “The Effect of Upper Endoscopic Procedures Under Sedation on Ventricular Repolarization” published in Signa Vitae, reflect his dedication to exploring novel intersections between anesthesiology and cardiovascular health. His collaborative research with notable experts such as Sevil Gülaştı, Sercan Çayırlı, and Serra Topal showcases his team-oriented approach to advancing the field.

Education

Dr. Gülaştı completed his medical education at Istanbul University’s Faculty of Medicine, graduating in 2005. He pursued his specialization in Anesthesiology and Reanimation at Adnan Menderes University, where he trained extensively from 2012 to 2017. This robust academic foundation has enabled him to integrate clinical expertise with innovative research practices in anesthesiology.

Research Focus

Dr. Gülaştı’s research interests are rooted in understanding the physiological effects of anesthesia, particularly in high-risk surgeries. His pioneering work focuses on improving anesthesia techniques, exploring innovative pain management strategies, and utilizing advanced echocardiography to optimize patient outcomes. His expertise in ECMO (Extracorporeal Membrane Oxygenation) and intraoperative monitoring has further positioned him as a forward-thinking leader in anesthesiology.

Experience

With over a decade of clinical experience, Dr. Gülaştı has worked in several prestigious hospitals in Turkey, including his current role as a specialist at Aydın Kadın Doğum ve Çocuk Hastanesi. His previous positions at Bursa Şehir Hastanesi, Gediz Devlet Hastanesi, and Adnan Menderes University’s Anesthesiology Department have provided him with a wide range of clinical exposure, enhancing his skills in critical care and anesthesia management. His hands-on experience in managing complex patient cases has equipped him to implement innovative anesthetic techniques across diverse clinical settings.

Research Timeline

Dr. Gülaştı’s research journey has spanned several years, with his first major publication in 2015. His work, which spans topics such as anesthesia techniques, cardiovascular anesthesia, and post-operative management, has contributed significantly to the global body of anesthesiology knowledge. He continues to be a strong advocate for evidence-based practices, regularly contributing to national and international journals. His active role in global conferences underscores his commitment to sharing innovative findings with the wider medical community.

Awards & Honors

Dr. Gülaştı has received multiple accolades for his contributions to anesthesiology, reflecting his commitment to both advancing medical research and improving patient care. His innovation in the field has earned him recognition from prestigious academic institutions and medical organizations. These honors highlight his role as a leader and innovator in the field of anesthesiology.

Top-Noted Publication

One of Dr. Gülaştı’s most notable contributions is his chapter, “Mitral Kapak Onarımında İntraoperatif Transözefageal Ekokardiyografi ve Anestezi Yönetimi”, published in Vakalarla Kalp Damar Cerrahisi. His work is widely cited, particularly his studies on post-operative pain management and advanced anesthesiology techniques, which have been pivotal in advancing clinical practices globally.

“The Effect of Upper Endoscopic Procedures Under Sedation on Ventricular Repolarization: Retrospective Study”
Authors: Sevil Gülaştı, Ferdi Gülaştı, Sercan Çayırlı, Serra Topal, Direnc Yigit
Journal: Signa Vitae (2025, Open Access)
This retrospective study, soon to be published in Signa Vitae, investigates the effects of sedation on ventricular repolarization during upper endoscopic procedures, offering critical insights into the cardiovascular impact of anesthesia. This is a prime example of Dr. Gülaştı’s innovative research at the intersection of anesthesiology and cardiology.

Strengths for the Best Innovator Award

Dr. Gülaştı’s dedication to research, clinical excellence, and innovation in anesthesiology make him an ideal candidate for the Best Innovator Award. His pioneering work in intraoperative monitoring, sedation protocols, and cardiovascular anesthesia has not only shaped clinical practices but has also opened new avenues for improving patient safety and outcomes. His collaborative approach to research, coupled with his constant pursuit of evidence-based, cutting-edge solutions, showcases his ongoing commitment to pushing the boundaries of medical science.

1. Innovative Research Contributions

Dr. Gülaştı’s groundbreaking research in anesthesiology, particularly in the areas of cardiovascular anesthesia and intraoperative monitoring, underscores his innovative approach to improving patient outcomes. His work on advanced echocardiography in anesthesia management and studies like “The Effect of Upper Endoscopic Procedures Under Sedation on Ventricular Repolarization” exemplify his focus on integrating new methodologies and technologies into clinical practice. These contributions are not only scientifically valuable but also have practical implications for enhancing safety during complex surgeries.

2. Pioneering in Cardiovascular Anesthesia

Dr. Gülaştı has been at the forefront of exploring the cardiovascular effects of anesthesia. His research delves into the intricate balance of sedation and heart function, particularly in high-risk surgeries. By analyzing how anesthesia impacts ventricular repolarization and other cardiac functions, his work has opened new pathways for optimizing anesthetic protocols in patients with cardiovascular concerns. This pioneering work positions him as a leader in the intersection of anesthesiology and cardiology.

3. Advanced Techniques in Anesthesia Management

Dr. Gülaştı’s expertise in advanced anesthetic techniques, such as ECMO (Extracorporeal Membrane Oxygenation), and intraoperative monitoring, has revolutionized how complex surgeries are managed. By developing and applying advanced strategies for pain management and monitoring vital signs during surgery, he has significantly improved the quality of care for critically ill patients. His contributions to refining anesthesia protocols for high-risk procedures show his capacity to innovate in the most challenging clinical settings.

4. Collaborative and Interdisciplinary Approach

A hallmark of Dr. Gülaştı’s innovation is his collaborative spirit. He has worked alongside various experts in the fields of anesthesiology, cardiology, and surgery, creating a multidisciplinary approach to patient care. By partnering with colleagues like Sevil Gülaştı, Sercan Çayırlı, and Serra Topal, he has co-authored several influential studies, integrating diverse perspectives to find better solutions for complex clinical problems. This collaborative approach amplifies the impact of his research and clinical contributions.

5. Strong Commitment to Education and Mentorship

Dr. Gülaştı is not only a researcher and clinician but also an educator who mentors the next generation of anesthesiologists. His work at Adnan Menderes University, where he trains future specialists, highlights his role in shaping the future of anesthesiology. Through his teaching, he imparts innovative methodologies, emphasizing the importance of staying updated with new research and technologies. His dedication to education ensures that his innovative practices continue to influence the field for years to come.

Mahmudul Hasan, Computer Science, Best Innovator Award

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Doctorate Mahmudul Hasan: Graduate Research Teaching Fellow, Deakin University, Melbourne, Victoria, Australia

Mahmudul Hasan is a passionate and dedicated Ph.D. candidate in Information Technology at Deakin University, Australia. With a robust academic foundation in Machine Learning, Artificial Intelligence (AI), Blockchain, and Cybersecurity, Mahmudul focuses his research on enhancing the privacy and efficiency of Federated Learning by integrating blockchain technology. His work aims to bridge the gap between emerging technologies and real-world applications, particularly in healthcare and business intelligence. Alongside his research, Mahmudul has a rich teaching history, having conducted courses on cybersecurity, data management, and secure coding at Deakin. He also mentors global researchers through online platforms, inspiring the next generation of tech innovators. Mahmudul’s personal interest in wildlife photography and creating educational content on YouTube further highlights his well-rounded personality, combining technical excellence with creative expression.

Online Profiles

Google Scholar Profile

Mahmudul Hasan is an active presence in the academic and tech communities with profiles on GitHub, LinkedIn, and other professional platforms. On GitHub, he shares his personal projects that focus on cutting-edge research areas such as Federated Learning, AI, and Cybersecurity. These repositories showcase his work on blockchain systems, machine learning models, and other data-driven solutions. His LinkedIn profile reflects his journey from lecturer to a research fellow, showcasing collaborations with renowned scholars and institutions. Mahmudul also actively participates in global online education through his YouTube channel, where he has uploaded over 400 videos covering a variety of Computer Science topics. His channel has become a valuable resource for students worldwide, particularly those pursuing data science, programming, and AI courses.

Mahmudul’s research contributions are widely recognized in the academic community, with his work accumulating 477 citations and an h-index of 13 since 2020. His research explores innovative solutions in Federated Learning, Blockchain, and Machine Learning, with particular emphasis on privacy-preserving AI and cybersecurity. His work has been cited in several high-impact journals, contributing to the growing body of knowledge on distributed machine learning models and their applications in healthcare, business intelligence, and climate science. Mahmudul’s publications are not only influential but also demonstrate his ability to bridge theoretical concepts with practical applications.

Education

Mahmudul Hasan is currently enrolled in a Ph.D. program in Information Technology at Deakin University, Australia (2023–Present), where his research focuses on integrating Blockchain and Federated Learning to create more efficient and secure machine learning models. His doctoral supervisors include prominent figures like Professor Dr. Yong Xiang, Professor Dr. John Yearwood, and Dr. Md Palash Uddin. He holds a M.Sc. in Computer Science and Engineering from Hajee Mohammad Danesh Science and Technology University (Bangladesh), where he worked on developing a data balancing technique to address performance discrepancies in black-box machine learning models. He also holds a B.Sc. in Computer Science and Engineering from the same institution, where he worked on projects related to agricultural crop recommendation systems and exchange rate prediction using deep learning methods.

Research Focus

Mahmudul’s research primarily revolves around Federated Learning, Blockchain, Machine Learning (ML), and AI. His doctoral research focuses on the intersection of Blockchain and Federated Learning, specifically exploring how these technologies can be combined to create more secure, private, and efficient machine learning models. He is particularly interested in distributed learning systems where data privacy is a concern, such as in healthcare, business intelligence, and cybersecurity applications. His work also includes investigating explainable AI and machine learning interpretability, which are critical for making AI models more transparent and understandable. Additionally, Mahmudul has contributed to advancing cybersecurity through the development of new models to predict cyber threats and malicious behavior in complex network systems.

Experience

Throughout his academic career, Mahmudul Hasan has built an impressive portfolio in both teaching and research. He is currently a Graduate Research Teaching Fellow at Deakin University, where he leads courses in Cybersecurity Analytics and Data Management. He has previously served as Casual Academic staff at Deakin, teaching courses such as Secure Coding and Data and Information Management. Beyond teaching, Mahmudul has extensive experience as a Research Assistant, working on projects in areas like computer vision, business intelligence, and data science. He has collaborated on several international research projects, including studies on AI-powered healthcare solutions and machine learning-based recommendation systems. His ability to work across different research domains has allowed him to bridge gaps between theory and practice, contributing significantly to the global research community.

Research Timeline

  • 2021–Present: Principal Investigator at CeMRD (Center for Multidisciplinary Research and Development), where Mahmudul leads a team of over 40 researchers on interdisciplinary projects related to AI, data science, and machine learning. Over 12 research papers have been published under his leadership.

  • 2022–2023: He served as a Research Fellow at the Ministry of Science & Technology, Bangladesh, focusing on carbon emission prediction using ensemble machine learning techniques. This project had a substantial impact on understanding the relationship between climate change and carbon emissions.

  • 2020–2021: Mahmudul worked as a Research Assistant in a project on masked face recognition systems, contributing to AI security and data privacy. Additionally, he was part of a multidisciplinary team at Swansea University that explored big data applications in financial innovation.

Awards & Honors

Mahmudul’s academic and professional achievements have earned him numerous awards and recognition. Among these, the Australian Research Council Grant Funded Scholarship (2023) stands out, acknowledging his potential in groundbreaking research. He was also awarded the NST Fellowship by the Ministry of Science & Technology, Bangladesh (2022-2023) to support his research in AI and machine learning. He received the IEEE Best Paper Award (2020) for his work on machine learning models in cybersecurity. Additionally, Mahmudul was awarded the Deakin University Top 10 Presentation Award (2024) for his outstanding contribution to the HDR Annual Conference. His consistent academic excellence has been further recognized with the CSE Dean’s Award (2019) and multiple Intra University Programming Contest wins.

Top-Noted Publications

Mahmudul has authored several influential publications in the fields of machine learning, cybersecurity, and AI. Some of his most cited works include:

  • “A Systematic Literature Review of Robust Federated Learning” in ACM Computing Surveys (2025), which offers an in-depth analysis of current Federated Learning research.

  • “Interpretable AI for Cervical Cancer Risk Analysis” in Digital Health (2025), a significant contribution to health informatics.

  • “Exploring Happiness Factors with Explainable Ensemble Learning” in PLOS ONE (2025), which applies ensemble learning techniques to analyze mental health data.
    His work is highly regarded in the academic community for its contribution to solving real-world problems using advanced machine learning models and explainable AI techniques.

  • Top-Noted Publications

    1. Deep Learning-Based Exchange Rate Prediction During the COVID-19 Pandemic
      MZ Abedin, MH Moon, MK Hassan, P Hajek
      Annals of Operations Research, 345 (2), 1335-1386
      Cited by 116 (2025)
      This study explores how deep learning models were employed to predict exchange rates during the COVID-19 pandemic, revealing key financial insights.

    2. Ensemble Machine Learning-Based Recommendation System for Effective Prediction of Suitable Agricultural Crop Cultivation
      M Hasan, MA Marjan, MP Uddin, M Ibn Afjal, S Kadry, S Ma, Y Nam
      Frontiers in Plant Science, 14, 1234555
      Cited by 67 (2023)
      This paper highlights an ensemble machine learning model aimed at predicting the most suitable crops for cultivation, with significant implications for sustainable agricultural practices.

    3. Effect of Imbalance Data Handling Techniques to Improve the Accuracy of Heart Disease Prediction Using Machine Learning and Deep Learning
      MA Sahid, M Hasan, N Akter, MMR Tareq
      2022 IEEE Region 10 Symposium (TENSYMP), 1-6
      Cited by 29 (2022)
      This paper addresses the issue of data imbalance in heart disease prediction, proposing techniques to enhance model accuracy.

    4. Advancing Reservoirs Water Quality Parameters Estimation Using Sentinel-2 and Landsat-8 Satellite Data with Machine Learning Approaches
      M Mamun, M Hasan, KG An
      Ecological Informatics, 81, 102608
      Cited by 23 (2024)
      This study leverages machine learning models with satellite data to assess and improve the estimation of water quality parameters in reservoirs.

    5. A Blending Ensemble Learning Model for Crude Oil Price Forecasting
      M Hasan, MZ Abedin, P Hajek, K Coussement, MN Sultan, B Lucey
      Annals of Operations Research, 1-31
      Cited by 23 (2024)
      This research proposes an ensemble learning approach for forecasting crude oil prices, providing key insights into the global energy market.

Top Strengths for the Best Innovator Award:

Timely & Impactful Applications

  • Relevance to Current Global Issues: Each of the studies addresses some of the most pressing global challenges. From the economic instability caused by COVID-19 and fluctuations in oil prices to sustainable agriculture and healthcare, these papers tackle issues that affect millions of people worldwide.

  • Practical Solutions: These applications aren’t just theoretical—they have real-world implications. The ability to provide innovative solutions in financial forecasting, agriculture, public health, and environmental management shows a unique ability to respond to immediate needs.

2. Sophisticated and Cutting-Edge Techniques

  • State-of-the-Art AI/ML Methods: The use of deep learning and ensemble methods demonstrates an advanced level of technical expertise. These techniques allow for highly accurate, efficient, and scalable solutions to complex problems, setting these papers apart from more traditional approaches.

  • Innovation in Application: By employing these sophisticated techniques in diverse fields like finance, agriculture, healthcare, and environmental science, the research shows creativity in applying modern AI methodologies to a wide array of challenges, often in areas where AI hasn’t been widely explored.

3. Interdisciplinary Expertise

  • Cross-Disciplinary Knowledge: The studies span several diverse fields—finance, agriculture, healthcare, and environmental science—demonstrating the ability to bridge gaps between technology and domain-specific knowledge.

  • Broad Applicability of Research: This interdisciplinary approach speaks volumes about the researcher’s versatility and adaptability. The ability to apply machine learning and AI in such varied contexts suggests a deep understanding of both the technical aspects and the real-world challenges in these fields.

4. Global and Societal Impact

  • Significant Contribution to Society: Each of these research papers isn’t just advancing knowledge; it’s creating tangible benefits for society at large. Whether it’s improving healthcare outcomes, driving economic stability, enhancing food security, or preserving the environment, the impact is vast and measurable.

  • Sustainability and Well-Being: Many of these studies also focus on sustainability (agriculture, water quality, etc.), highlighting a commitment to solutions that support long-term societal well-being and environmental health. This makes the research not just innovative, but ethically aligned with pressing global needs.

5. High Citation & Recognition

Academic Influence: The high citation count reflects the importance of the research in the academic community. It shows that the work is not just innovative but also widely recognized and used by others in the field, amplifying its influence and encouraging further advancements.

Impact Beyond Academia: The recognition of these papers also indicates that the research has practical, real-world applications that have resonated with both scholars and industry professionals, reinforcing the relevance and scalability of the innovations.