Tag: Best Researcher Award

Atulkumar Manchalwar, Engineering, Best Researcher Award

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Doctorate Atulkumar Manchalwa: Assistant Professor at AISSMS College of Engineering Pune, India

Dr. Atulkumar Anil Manchalwar is a Structural Engineering expert with a primary focus on seismic hazard assessment and earthquake response control of buildings. With a Ph.D. from Visvesvaraya National Institute of Technology (VNIT), Nagpur, he has dedicated his career to enhancing the seismic resilience of reinforced concrete structures. He has a reputation for his innovative work on performance-based seismic analysis, optimization of metallic dampers, and the design of base isolation systems. Dr. Manchalwar is committed to exploring new frontiers in earthquake engineering and mentoring the next generation of engineers.

Online Profiles

  • Scopus Profile
    Access Dr. Manchalwar’s research output, citations, and co-authors through his comprehensive Scopus profile.

  • Google Scholar Profile
    View Dr. Manchalwar’s Google Scholar profile to explore his top-cited papers and academic contributions.

  • Research Impact Metrics

    • Citations by Documents: Dr. Manchalwar’s 47 documents have been cited 70 times, indicating a strong influence in his field of study.

    • h-index: An h-index of 5 means that Dr. Manchalwar has 5 papers each with at least 5 citations, reflecting a consistent academic contribution to seismic engineering and structural dynamics.

Education

Dr. Manchalwar’s educational journey began with a Bachelor’s degree in Civil Engineering from Babasaheb Naik College of Engineering, Pusad, where he graduated in 2010 with a solid academic record (70.38%). He pursued his Master’s in Structural Engineering at Kavikulguru Institute of Technology and Science, Ramtek, where he was awarded the 5th rank in his university. His academic excellence culminated in a Ph.D. at VNIT Nagpur, where his research focused on seismic response control of buildings using supplementary devices. His doctoral studies were supervised by renowned experts, and his work continues to shape the future of structural engineering.

Research Focus

Dr. Manchalwar’s research spans multiple domains within Structural Engineering, with a primary emphasis on seismic hazard assessment, earthquake response control, and vulnerability analysis of RC structures. His pioneering work includes optimizing seismic response through devices like metallic dampers, base isolation techniques, and soil-structure interaction models. Additionally, he investigates how structural dynamics can be leveraged to mitigate damage in buildings during seismic and blast events. His research continues to influence the design of more resilient infrastructures, particularly in seismic zones.

Experience

Dr. Manchalwar has an extensive academic career spanning over a decade. He currently serves as a faculty member at AISSMS College of Engineering, Pune. He has previously taught at institutions such as Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, and G H Raisoni College of Engineering, Nagpur. His academic roles involve teaching core subjects like Earthquake Engineering, Structural Dynamics, and Prestressed Concrete Structures at both undergraduate and postgraduate levels. In addition to teaching, he has held multiple administrative roles, including NAAC and NBA accreditation coordination and as the IIC Department Coordinator. He is also involved in organizing hackathons, technical events, and innovation activities within his academic community.

Research Timeline

  • 2013-2019: Ph.D. Research (VNIT Nagpur):
    Dr. Manchalwar’s doctoral research concentrated on seismic response control using supplementary damping devices such as metallic dampers and isolators. His work utilized advanced structural analysis tools like SAP2000 and MATLAB to model and simulate the effects of different damping strategies on the performance of RC buildings under seismic loads.

  • 2019-Present: Post-Ph.D. Research:
    After completing his Ph.D., Dr. Manchalwar continued exploring the dynamic behavior of buildings, focusing on response control under both seismic and blast loading conditions. His ongoing projects investigate the efficacy of hybrid damping systems, base isolation systems, and the optimization of structural elements to reduce vulnerability to natural and man-made forces.

Awards & Honors

Dr. Manchalwar’s academic and research accomplishments have been widely recognized. Some of his most notable awards include:

  • Dr. Jai Krishna Prize by The Institution of Engineers (India) for exceptional academic performance in his field.

  • Top Performing Mentor award from NPTEL for his contributions to online teaching and mentoring of students in Civil Engineering.

  • University ranks during his academic tenure: 5th rank in M.Tech and several top placements in undergraduate competitions.

Top-Noted Publication

Dr. Manchalwar has authored and co-authored numerous influential publications in top-tier journals and conferences. Some of his most significant works include:

  1. “Performance of RC Structures Equipped with Steel and Aluminium X-Plate Dampers” – Journal of Institute of Engineers India Series A, 2016. This paper analyzes the effectiveness of different damper materials in enhancing the seismic performance of RC structures.

  2. “Seismic Response Control of Building with Optimal Location of Metallic Damper” – Structures and Buildings, 2019. In this paper, Dr. Manchalwar introduces methods for optimizing damper placement to maximize seismic performance.

  3. “Seismic Performance of Structure with Isolated Foundation Using U-shape Steel Damper as an Isolator” – Soil Mechanics & Foundation Engineering, 2020. This work focuses on improving building resilience by utilizing advanced isolation techniques.

  4. “Vibration Control of Structure Using Inelastic Tuned Mass Damper” – Asian Journal of Civil Engineering, 2024 (Accepted). A cutting-edge study on the application of inelastic tuned mass dampers to control structural vibrations.

His work has been published in leading SCI and Scopus-indexed journals, contributing valuable insights to the field of earthquake engineering.

Research Impact & Innovations

Beyond publications, Dr. Manchalwar has significantly impacted the industry with his innovative approaches. His patent on “Water Distribution Apparatus with Inbuilt Flow Rate Control Mechanism” (2024), and others focusing on plant monitoring and railway wagon load monitoring, illustrate his commitment to practical applications of engineering solutions. His innovations are aimed at improving the efficiency, safety, and sustainability of structural and civil engineering systems.

Dharmendar Reddy Yanala, Mathematics, Best Researcher Award

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Professor Dharmendar Reddy Yanala: PROFESSOR at ANURAG UNIVERSITY, India

Dr. Yanala Dharmendar Reddy is an accomplished academician and researcher with over 20 years of experience in the field of Applied Mathematics. Currently serving as a Professor in the Department of Mathematics at Anurag University, Hyderabad, he has dedicated his career to the study of Fluid Dynamics, specifically in Magnetohydrodynamics (MHD) and nanofluid heat transfer. His research interests include MHD boundary layers, heat and mass transfer, and the impact of nanoparticles on fluid dynamics. Dr. Reddy is known for his ability to blend theoretical models with numerical techniques to solve complex problems in the realms of geophysics, astrophysics, and industrial applications. His work is not only significant for academia but also for practical applications in energy systems, environmental engineering, and medical technologies. His passion for education and research is matched by his commitment to fostering the next generation of mathematicians and engineers.

Online Profiles

  • Google Scholar: Yanala Dharmendar Reddy – A platform for accessing Dr. Reddy’s scholarly articles and citations.

  • Scopus ID: 57202329139 – Tracking all of Dr. Reddy’s research contributions on Scopus, a global database for academic research.

  • ORCID: 0000-0002-8926-7259 – Ensuring that Dr. Reddy’s research activities are uniquely identified and linked to his academic and professional work.

  • WOS Researcher ID: B-7614-2018 – A profile on Web of Science, further validating Dr. Reddy’s research output and professional standing.

  • Citations & Research Impact

    • Total Citations: 2276

    • h-index: 27

    • i10-index: 54

    These metrics indicate Dr. Reddy’s significant impact on the academic community, with a well-established record of influential publications. His h-index of 27 reflects a consistent contribution to high-quality research, with at least 27 publications that have each been cited 27 or more times. Additionally, an i10-index of 54 highlights his ability to produce scholarly works that have been widely referenced and utilized in ongoing research, further cementing his reputation as a key figure in his field.

Education

Dr. Reddy completed his Ph.D. in Applied Mathematics at Osmania University, Hyderabad, in 2017. His doctoral research focused on the numerical techniques used to study the MHD boundary layer flow of nanofluids over stretching sheets, a topic with profound implications for industrial heat transfer and energy systems. Prior to this, he earned his M.Sc. in Mathematics with distinction from Osmania University (2005) and a B.Sc. in Computer Science (2003), demonstrating early aptitude in both theoretical and computational aspects of mathematics. His academic journey reflects a solid grounding in both pure and applied mathematics, which laid the foundation for his later research endeavors.

Research Focus

Dr. Reddy’s research explores complex fluid dynamics problems, specifically focusing on Magnetohydrodynamics (MHD) and the heat and mass transfer of nanofluids. MHD flow has applications in various fields, such as power generation, astrophysics, and environmental systems. His interest in nanofluids stems from the growing need to enhance heat transfer in industrial and technological applications. Nanofluids are a class of fluids that contain nanoparticles, which significantly improve the thermal properties of base fluids. By studying the interaction between magnetic fields, fluid flow, and nanoparticle behavior, Dr. Reddy aims to propose solutions to challenges in energy efficiency, industrial heat exchangers, and even medical applications like hyperthermia treatment. His work has resulted in both theoretical advancements and practical applications, benefiting a wide range of industries.

Experience

Dr. Reddy’s academic career spans two decades, with significant contributions to teaching, research, and academic administration. He has been a Professor in the Department of Mathematics at Anurag University since December 2024. Previously, he served as an Associate Professor (2020-2024) and Assistant Professor (2005-2020) at Anurag Group of Institutions, where he helped shape the curriculum and research landscape in applied mathematics. Throughout his career, Dr. Reddy has mentored countless undergraduate, postgraduate, and doctoral students. His leadership roles also include serving as the Additional Controller of Examinations at Anurag Group from 2012 to 2017, where he managed examination procedures, ensuring fairness and transparency. Dr. Reddy is dedicated to fostering a research-driven environment in his academic roles, encouraging collaboration and innovation among his students and colleagues.

Research Timeline

  • 2014-2016: Dr. Reddy completed a UGC-sponsored Minor Research Project on the “Impact of Flow Parameters on Heat and Mass Transfer” using numerical techniques. This project laid the groundwork for his future work on MHD flows and nanofluids.

  • 2017-2020: Focused on MHD nanofluid flow, leading to multiple publications on heat transfer enhancement in industrial and biological systems.

  • 2020-Present: Expanded his research to include chemical reactions, radiation effects, and their influence on nanofluid flow. His current projects involve exploring novel fluid systems for applications in energy systems and medical technologies, which continue to garner significant academic and industrial interest.

Awards & Honors

Dr. Reddy’s contributions to academia have been widely recognized. In 2024, he was listed among the Top 2% Scientists Worldwide, an accolade co-published by Elsevier and Stanford University, placing him in an elite group of researchers globally. Additionally, he received the Best Teacher Award from AQER in 2024 for his excellence in teaching and his innovative contributions to the field of mathematics. His involvement in academic organizations includes life memberships in the Indian Science Congress Association and the Andhra Pradesh Society for Mathematical Sciences, where he plays an active role in promoting mathematics research in India. These awards and recognitions underscore his dedication to both research and teaching.

Top-Noted Publication

  1. Chemical reaction and Soret impacts on MHD heat and mass transfer Casson hybrid nanofluid (MoS2+ZnO) flow based on engine oil across a stretching sheet with radiation
    Journal: Chemical Thermodynamics and Thermal Analysis (2025)
    DOI: 10.1016/j.ctta.2025.100163
    Contributors: Radhika, M.; Dharmendar Reddy, Y.

  2. Impact of thermal radiation and viscous dissipation on MHD heat transmission MoS2 and ZnO/engine oil hybrid nanofluid flow along a stretching porous surface
    Journal: Multiscale and Multidisciplinary Modeling, Experiments and Design (2025)
    DOI: 10.1007/s41939-024-00589-y
    Contributors: Mangamma, I.; Reddy, Y.D.

  3. Numerical solutions of steady radiative Maxwell-nanofluid flow toward a stretching sheet in the presence of magnetic field and porous medium
    Journal: Modern Physics Letters B (2025)
    DOI: 10.1142/S0217984924504323
    Contributors: Babu, P.R.; Kumar, M.A.; Raju, R.S.; Reddy, Y.D.

  4. Viscous dissipation and radiation effects on MHD heat transfer copper-water nanofluid flow over an exponentially shrinking surface
    Journal: Multiscale and Multidisciplinary Modeling, Experiments and Design (2025)
    DOI: 10.1007/s41939-024-00708-9
    Contributors: Radhika, M.; Reddy, Y.D.

  5. A numerical study on MHD Maxwell fluid with nanoparticles over a stretching surface: Impacts of thermal radiation, convective boundary condition and induced magnetic field
    Journal: Numerical Heat Transfer, Part A: Applications (2024)
    DOI: 10.1080/10407782.2024.2338259
    Contributors: Venkatesh, N.; Raju, R.S.; Anil Kumar, M.; Dharmendar Reddy, Y.

Shiting Wen, Computer Science, Best Researcher Award

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Professor Shiting Wen: Professor at School of Computer and Data Engineering, NingboTech University, China

Professor Shiting Wen is an esteemed faculty member at the School of Computer and Data Engineering at NingboTech University, China. His academic journey has seen him achieve high levels of recognition in the field of Computer Science, where he specializes in Big Data Processing, the Internet of Things (IoT), and Artificial Intelligence (AI). With a BSEng in Computer Science from Northeast Forest University and a Ph.D. from both the University of Science and Technology of China (USTC) and City University of Hong Kong (CityU), Prof. Wen has made extensive contributions to various high-impact research areas. He has published over 60 research papers in top-tier journals and conferences such as ICML, ICDE, Inf. Sci., and TITS, cementing his position as a leading academic in his field. Prof. Wen also has a strong presence in academic governance, serving as a Program Committee (PC) member for various international conferences and contributing as an editor for well-regarded journals. His research has garnered international recognition for advancing technologies in AI and IoT, shaping the future of data science and telecommunications.

Online Profiles

ORCID Profile

Prof. Wen’s work is widely disseminated across several academic platforms, including DBLP, where his extensive list of publications and conference proceedings are readily accessible. He maintains an active online presence in the academic community, contributing to significant journals in the fields of data mining, machine learning, IoT, and cloud computing. His research activities and papers have influenced a broad spectrum of disciplines, from blockchain technology and decentralized federated learning to reinforcement learning and knowledge graph reasoning. These platforms serve as an essential resource for those interested in the cutting-edge developments Prof. Wen is driving in these areas. His academic footprint spans multiple disciplines, reflecting the depth and diversity of his research endeavors.

Education

Prof. Wen’s educational background is a strong foundation for his success in the field of computer science. After completing his Bachelor’s Degree in Computer Science and Technology from Northeast Forest University in 2007, he went on to pursue graduate studies at the University of Science and Technology of China (USTC) and City University of Hong Kong (CityU). Under the guidance of renowned experts Prof. Lihua Yue (USTC) and Prof. Qing Li (CityU), he earned his Ph.D. in Computer Science in 2012. His doctoral research focused on pioneering algorithms and methodologies related to data mining, big data, and intelligent systems, which led to several publications in top-tier conferences. Prof. Wen’s education journey reflects not only academic rigor but also a continuous drive to contribute to the advancement of data engineering and AI technologies.

Research Focus

Prof. Wen’s research interests are highly interdisciplinary, with a focus on Big Data Processing and Mining, the Internet of Things (IoT), and Artificial Intelligence. Specifically, his work examines how big data can be processed efficiently, using novel algorithms for data mining and pattern recognition. He explores decentralized systems and federated learning as solutions to large-scale data analysis in distributed environments, such as IoT devices. His AI research includes the application of machine learning algorithms to real-world problems like medical image analysis, blockchain technology, and time series classification. Prof. Wen’s innovative approach to cross-cutting challenges in IoT and AI is advancing both theoretical frameworks and practical applications, particularly in smart healthcare systems, intelligent transportation, and secure data exchange. His research has become crucial in addressing emerging global challenges in data analytics, automation, and security.

Experience

Prof. Wen has extensive professional experience, both in academia and in administrative roles. In addition to his academic role at NingboTech University, where he teaches and mentors graduate students, he has held a significant leadership position as the deputy director of the Bureau of Science and Technology in Yinzhou District, Ningbo City. His contributions to the local scientific community, particularly in the areas of technology innovation and policy development, have further solidified his influence in the region. Prof. Wen has been a key reviewer and editor for top journals such as IEEE Transactions on Knowledge and Data Engineering (TKDE), Knowledge-Based Systems (KBS), and Web Mining and Data Mining (WWWJ). As an editor for Information Technology and Telecommunications, he continues to shape the academic discourse in his fields of expertise. His participation in numerous program committees for leading conferences like WSDM, DASFAA, WISE, ICML, and CIKM has allowed him to contribute to the shaping of future research agendas.

Research Timeline

Prof. Wen’s research trajectory spans over a decade, marked by several key milestones:

  • 2010-2014: Prof. Wen laid the groundwork for his academic career by focusing on foundational topics such as the Internet of Things (IoT), human-centric computing, and data engineering. During this period, he made early contributions to the development of algorithms for data analysis and processing.

  • 2014-2020: This phase marked a shift towards more specialized research, particularly in big data processing and federated learning. Prof. Wen began exploring decentralized data systems, a trend that would become central to his work in AI and blockchain technologies. His research in this period was focused on the intersection of IoT, cloud computing, and machine learning.

  • 2021-Present: Prof. Wen has taken on a leadership role in research surrounding AI safety, reinforcement learning, and blockchain applications. His work in federated learning and decentralized AI models continues to evolve, with applications in healthcare, transportation, and smart cities. His recent contributions have been widely recognized, with papers published in conferences such as ICML, CIKM, and ADMA.

Awards & Honors

Throughout his career, Prof. Wen has received several prestigious awards and honors in recognition of his outstanding contributions to the fields of computer science and data engineering. He has received recognition from key research institutions for his innovation in AI, IoT, and Big Data. He has also earned accolades for his service in academic governance, including his active role as a Program Committee member and editorial board member for well-respected journals. Additionally, Prof. Wen has been the recipient of various research grants, helping him drive forward cutting-edge projects in machine learning, IoT, and blockchain technology. His work continues to be instrumental in advancing the boundaries of knowledge in these transformative fields.

Top-Noted Publications

Among Prof. Wen’s many publications, the following are especially notable for their impact on both academia and industry:

  • “Overcoming Heterogeneous Data in Federated Medical Vision-Language Pre-training: A Triple-Embedding Model Selector Approach” (AAAI 2025) – This paper addresses the critical challenge of data heterogeneity in federated learning and proposes novel approaches to enhance model training in medical AI applications.

  • “ExClique: An Express Consensus Algorithm for High-Speed Transaction Processing in Blockchains” (INFOCOM 2025) – A groundbreaking paper on blockchain transaction processing, offering new solutions for enhancing consensus algorithms in decentralized systems.

  • “Towards Efficient Decentralized Federated Learning: A Survey” (ADMA 2024) – This survey paper delves into the methodologies and challenges of decentralized federated learning, providing insights into efficient approaches for distributed AI systems.

  • “Facilitating Feature Selection and Extraction in Clinical Trials with Large Language Models” (ADMA 2024) – This work highlights how AI and large language models can revolutionize clinical trials by automating and improving feature extraction for medical data analysis.

These publications reflect Prof. Wen’s focus on AI-driven innovation, decentralized learning systems, and applications in healthcare and blockchain technology, which continue to influence future research in these areas.

Mohamed Saad Bouh Elemine Vall, Mathematics, Best Researcher Award

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Doctorate Mohamed Saad Bouh Elemine Vall: Assistant professor at Higher Institute of industrial Engineering, Mauritania

 

Dr. Mohamed Saad Bouh Elemine Vall is a Mauritanian mathematician and Assistant Professor at the Institut Supérieur de Génie Industriel in Nouakchott, Mauritania. His academic work spans theoretical and applied mathematics, with a concentration on nonlinear analysis, partial differential equations, and variational methods. With over ten years of experience in higher education and scientific research, Dr. Vall has built a strong international research portfolio, particularly in the analysis of elliptic and parabolic problems within generalized functional frameworks. He is also deeply engaged in interdisciplinary applications, contributing to both mathematical theory and real-world problem solving through simulations, statistical modeling, and data analysis.

Online Profiles

Google Scholar Profile

Citations and Indices

Since 2020, Dr. Vall has accumulated a total of 99 citations, with 84 of them coming in recent years. His h-index stands at 5, reflecting a solid impact of his publications in the scientific community, while his i10-index is 2, indicating that two of his publications have received at least 10 citations each. These indices highlight the growing relevance and influence of his research in applied mathematics and nonlinear analysis.

Dr. Vall maintains an active online academic presence. His Google Scholar profile showcases his research impact, citation metrics, and publication trends across mathematical journals. Through ResearchGate, he regularly shares his work with the international scientific community, including peer-reviewed articles, conference presentations, and ongoing research updates. These platforms reflect both the breadth and depth of his contributions in mathematics, and serve as a resource for students and collaborators worldwide.

Education

Dr. Vall earned a Ph.D. in Mathematics and Applications from the University Sidi Mohamed Ben Abdellah in Fès, Morocco, where he specialized in nonlinear analysis and functional spaces. He also holds a Master’s degree in Mathematical Sciences with a specialization in Partial Differential Equations, Modeling, and Scientific Computing (EDPMCS). His earlier education includes a Bachelor’s and Master’s degree in Applied Mathematics from the University of Nouakchott, preceded by a DEUG in Mathematics and Physics, and a Baccalaureate in Mathematical Sciences obtained at the Lycée National of Mauritania. This robust academic background underpins his expertise in both pure and applied domains of mathematics.

Research Focus

Dr. Vall’s research lies at the intersection of nonlinear functional analysis, variational methods, and mathematical modeling. He specializes in Musielak-Orlicz and variable exponent Sobolev spaces, developing new existence and multiplicity results for weak and entropy solutions to elliptic and parabolic PDEs. His interests extend to the mathematical study of complex real-world systems, including epidemiological dynamics, econometric time-series models, and data-driven simulations. He is particularly noted for using modern numerical tools like Python, R, and Mathematica to bridge theory and computation, making his research relevant to both pure mathematicians and applied scientists.

Experience

Dr. Vall has taught at various academic institutions including the University of Nouakchott Al Aassriya, the Institut Supérieur de Comptabilité et d’Administration des Entreprises (ISCAE), and the Institut Universitaire Professionnel. He has delivered over 20 unique undergraduate and graduate-level courses covering analysis, topology, statistics, numerical methods, and programming with R, Python, and Octave. His teaching portfolio also includes courses in econometrics, data science, and statistical modeling, tailored for students in engineering, economics, and logistics. In addition to classroom teaching, he has supervised numerous master’s dissertations and co-supervised doctoral theses in both theoretical mathematics and applied modeling.

Research Timeline

Dr. Vall’s research trajectory began in 2013 with work on entropy solutions in Musielak-Orlicz frameworks. From 2015 to 2018, he focused on strongly nonlinear problems involving variable exponent growth, collaborating closely with research groups in Morocco. Between 2019 and 2021, his work evolved to cover Kirchhoff-type elliptic problems and the use of numerical simulations in public health modeling, notably during the COVID-19 pandemic. More recently (2022–2025), his research has delved into non-local operators, anisotropic Laplacians, and hybrid analytical-computational approaches, with publications in journals such as Nonlinear Dynamics, Complex Variables and Elliptic Equations, and Boundary Value Problems.

Awards & Honors

In recognition of his academic excellence, Dr. Vall received a Certificate of Excellence for the 2013 cohort of the Master’s program in Fès. He has been selected to participate in multiple advanced mathematics schools organized by CIMPA, including programs on waste management modeling and inverse problems in geometry. He has presented research at major conferences, including the International Conference on Differential Geometry and the Spring School on Nonlinear PDEs. His contributions to mathematical research and teaching have earned him respect in both national and international academic communities.

Top-Noted Publication

One of Dr. Vall’s most distinguished publications is the 2025 article titled:
A. Ahmed, M. S. B. Elemine Vall, Weak solutions in anisotropic (α→(z), β→(z))-Laplacian Kirchhoff models, published in Complex Variables and Elliptic Equations.
This work addresses a class of generalized Kirchhoff equations involving anisotropic operators and variable growth conditions, contributing novel theoretical results and extending the frontier of nonlinear elliptic theory. The paper has received recognition for its methodological depth and relevance in advanced PDE analysis.

  • Entropy solutions for parabolic equations in Musielak framework without sign condition and with measure data

    • Authors: MSB Elemine Vall, A Ahmed, A Touzani, A Benkirane

    • Journal: Archivum Mathematicum

    • Volume: 56 (2), Pages 65-106

    • Year: 2020

  • Entropy solutions for nonlinear parabolic problems with noncoercivity term in divergence form in generalized Musielak-Orlicz spaces

    • Authors: A Talha, A Benkirane, MSB Elemine Vall

    • Journal: Nonlinear Studies

    • Volume: 25 (1)

    • Year: 2018

  • Fractional double-phase problems with Kirchhoff-type operators and variable exponents

    • Authors: M El Khayr Boukraa, MSB Elemine Vall

    • Journal: Journal of Elliptic and Parabolic Equations

    • Year: 2025

  • Weak solutions in anisotropic (α→(z), β→(z))-Laplacian Kirchhoff models

    • Authors: MSB Elemine Vall, A Ahmed

    • Journal: Complex Variables and Elliptic Equations

    • Year: 2025

  • Multiplicity of weak solutions in double phase Kirchhoff elliptic problems with Neumann conditions

    • Authors: A Ahmed, MSB Elemine Vall, S Boulaaras

    • Journal: Boundary Value Problems

    • Volume: 2025 (1), Pages 50

    • Year: 2025

fady zakaria, Medicine, Best Researcher Award

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Doctorate fady zakaria: Newgiza University, Egypt

Fady Zakaria is a dedicated medical student in his second year at Newgiza University, specializing in pediatric neurology with a particular interest in epilepsy. Fady’s academic journey is driven by a deep passion for exploring molecular biology and its applications in the diagnosis and treatment of neurological conditions. As an aspiring physician-scientist, his research aims to bridge the gap between molecular mechanisms and clinical practices, particularly in pediatric populations. His work is characterized by a meticulous approach to scientific inquiry, a strong desire to contribute to medical knowledge, and a commitment to improving pediatric healthcare outcomes.

Online Profiles

ORCID Profile

At this stage, Fady does not have a personal website or LinkedIn profile. However, his professional identity and research contributions can be accessed through his academic affiliations and publications, which highlight his ongoing dedication to advancing medical research. He is actively working towards developing an online presence that will reflect his growing body of research and professional experiences as he progresses through his medical career.

Education

Fady Zakaria is currently enrolled in the undergraduate medical program at Newgiza University, where he has been excelling in both clinical and research components of his education. His academic journey is set to culminate in his graduation with a Bachelor of Medicine, Bachelor of Surgery (MBBCH) degree in March 2024. Throughout his medical education, Fady has demonstrated a particular interest in neurobiology and molecular genetics, specifically as they relate to pediatric epilepsy. His studies have provided him with a strong foundation in both theoretical and practical aspects of medicine, preparing him for future research and clinical practice in neurology.

Research Focus

Fady’s current research is centered around the role of microRNAs (miRNAs) in pediatric epilepsy, focusing on their potential as both biomarkers for early diagnosis and therapeutic targets for treatment. His work investigates the molecular pathways through which miRNAs influence neuronal function and how they can be harnessed to improve clinical outcomes for children suffering from epilepsy. By identifying specific miRNA profiles associated with epilepsy, Fady aims to contribute to a deeper understanding of the disease’s pathogenesis and to propose novel, non-invasive diagnostic tools. His research is driven by a desire to address the unmet needs of pediatric patients who face chronic neurological disorders.

Experience

Although Fady is early in his research career, he has already gained invaluable experience through active participation in several research projects and clinical audits. As a first author, he presented a study on the role of venous thromboembolism prophylaxis in general surgical patients at the Annual Meeting of Al-Salam Surgeons in May 2025, which gave him an opportunity to engage with professionals in the surgical and clinical fields. Additionally, Fady contributed to the preparation of a presentation on “Closing defects, from simple to difficult” at the United Conference of Hepatogastroenterology and Infectious Diseases in 2024. This exposure to a wide range of medical disciplines has provided him with the practical skills and interdisciplinary knowledge necessary to tackle complex clinical questions. Fady continues to refine his skills in both research and presentation, positioning himself for a future in academic medicine.

Research Timeline

  • 2023-Present: Fady’s research journey began in 2023, when he started investigating the role of miRNAs in pediatric epilepsy as part of his academic focus at Newgiza University. This research is ongoing and is expected to culminate in further publications and potential collaborations with experts in neurology and genetics.

  • 2024: As part of his final year of medical school, Fady plans to expand his research into therapeutic applications of miRNA-based treatments for pediatric epilepsy. This year will also mark the completion of his undergraduate medical education and the beginning of his transition into more specialized clinical and research roles.

  • 2025 and Beyond: After graduation, Fady intends to pursue a medical career that combines clinical practice with continued research in molecular neurology, aiming to contribute to the development of personalized treatment plans for children with epilepsy.

Awards & Honors

Though Fady has not yet received formal awards or honors, his contributions to the field are already gaining attention. His work was recognized during the Annual Meeting of Al-Salam Surgeons in 2025, where he presented his clinical audit on thromboembolism prevention. This recognition is just the beginning of what is expected to be a promising academic and clinical career. Fady continues to work diligently on his research and aims to earn accolades as his contributions to the field expand.

Top-Noted Publication

Fady’s most notable publication to date is the systematic review titled The Role of MicroRNAs in the Pathogenesis and as Biomarkers for Pediatric Epilepsy, published in Molecular Diagnosis & Therapy on June 8, 2025. The publication, co-authored with prominent experts in the field, delves into the potential of miRNAs to not only serve as biomarkers for early diagnosis of epilepsy in children but also to guide the development of novel therapeutic strategies. This work is a significant contribution to the field, offering a comprehensive review of the existing literature while proposing new avenues for future research. Fady’s ability to synthesize complex data and present it clearly has earned him recognition among his peers and mentors.

Fady Zakaria’s most notable publication is the journal article The Role of MicroRNAs in the Pathogenesis and as Biomarkers for Pediatric Epilepsy: A Systematic Review, published in Molecular Diagnosis & Therapy on June 8, 2025. This article delves into the potential of microRNAs (miRNAs) as both biomarkers for early diagnosis and therapeutic targets in pediatric epilepsy. The systematic review synthesizes current research on the molecular mechanisms underlying epilepsy and discusses how miRNAs could revolutionize diagnostic practices and treatment strategies for children with this neurological condition. Fady co-authored this paper alongside Steven Amged Yousef, Janna AbdelDayem, Rawan ElGamal, Omar Y. Issa, Mohamed Mansour, Harvey Bastorous, Eslam Emad, and Rudayna Mahgoub. The paper has garnered attention for its in-depth analysis and forward-looking approach to the role of miRNAs in epilepsy.

DOI: 10.1007/s40291-025-00791-9

Dharmendra Kumar Yadav, Chemistry, Best Researcher Award

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Dr. Dharmendra Kumar Yadav: Assistant Professor at Department of Biologics, College of Pharmacy, Gachon University, Korea

Dr. Dharmendra Kumar Yadav is a globally recognized scientist, currently serving as an Assistant Professor at the Department of Biologics, College of Pharmacy, Gachon University, South Korea. With a Ph.D. in Biological Science from CSIR-Central Institute of Medicinal and Aromatic Plants (Lucknow, India), he is regarded as one of the world’s top 2% scientists. His research integrates molecular modeling, chemoinformatics, bioinformatics, and plasma medicine, focusing on computational approaches for drug discovery and therapeutic applications. His work explores the in-silico prediction of biological activities and the molecular mechanisms behind plasma’s interactions with biomolecules, particularly in cancer treatment. Dr. Yadav’s groundbreaking contributions to plasma chemistry and bioinformatics have positioned him at the forefront of these rapidly evolving fields.

Online Profiles

Google Scholar Profile

  • Citations: 4874 total, with 3868 since 2020.

  • h-index: 37 total, with 32 since 2020.

  • i10-index: 122 total, with 113 since 2020.

Dr. Yadav maintains a robust digital presence through platforms such as Google Scholar, ResearchGate, and LinkedIn, where his work on molecular dynamics simulations, plasma medicine, and drug design is extensively shared. His profiles serve as a bridge between his research and the broader scientific community, enabling collaborations with top universities and research institutes. He regularly engages in academic discourse, providing valuable insights into cutting-edge computational techniques and interdisciplinary research. Through these platforms, Dr. Yadav not only shares his findings but also mentors the next generation of scientists, fostering international collaborations and partnerships.

Education

Dr. Yadav’s educational background is grounded in interdisciplinary research, combining biological sciences with advanced computational techniques. He earned his Ph.D. in Biological Science in 2013, working on QSAR model development for anticancer compounds at CSIR-Central Institute of Medicinal and Aromatic Plants, affiliated with Jawaharlal Nehru University, India. His research during his doctorate focused on developing predictive models for natural compounds, aiming to assess their in-vitro and in-vivo anticancer activities. Prior to his Ph.D., Dr. Yadav obtained his M.Sc. in Biomedical Science from Bundelkhand University, Jhansi, India, where he laid the foundation for his career in computational biology and drug discovery.

Research Focus

Dr. Yadav’s research is multifaceted, spanning several cutting-edge areas of computational biology, chemistry, and medicine. At the core of his work is the development of predictive QSAR models aimed at the functional identification of DNA and protein motifs, leveraging statistical methods and machine learning algorithms. His research into plasma medicine focuses on understanding the interactions between reactive plasma species and cellular biomolecules, such as DNA, proteins, and phospholipids. By using computational techniques like molecular dynamics simulations and density functional theory (DFT), Dr. Yadav seeks to unravel the underlying mechanisms of plasma therapy, particularly for cancer treatment. His other areas of interest include nanotechnology and plasma-surface interactions, with a goal to improve the efficiency of plasma for chemical production and fuel synthesis.

Experience

Dr. Yadav has over 10 years of academic and professional experience in both research and teaching. Since March 2024, he has been an Assistant Professor at Gachon University, where he teaches and mentors undergraduate, master’s, and Ph.D. students in the fields of pharmaceutical sciences and computational biology. His academic journey also includes roles as Principal Scientist at Arontier Co. Ltd., where he worked on drug development projects, and Research Professor at Gachon University from 2016 to 2019. Prior to his academic tenure, Dr. Yadav gained international exposure as a Post-Doctoral Research Fellow at Hanyang University, Seoul, South Korea, and a CSIR-Research Associate at the University of Delhi. His diverse experience across academia, research institutions, and industry positions him as a leading expert in his field.

Research Timeline

  • 2021–2022: Co-Principal Investigator for an AI-based anticancer drug development project funded by Gachon University Hospital, focusing on the development of RET-targeted therapies.

  • 2017–2020: Led the National Research Foundation of Korea (NRF) funded project on plasma medicine, exploring its application in cancer therapy and the interaction of reactive species with biomolecules.

  • 2015–2028: As Principal Investigator, led a long-term project funded by the Science & Engineering Research Board (SERB) on QSAR and molecular docking of COX inhibitors.

  • 2014–2015: Worked as a Research Associate at University of Delhi, developing QSAR models for anticancer natural products and advancing drug discovery.

  • 2013–2014: Postdoctoral Fellow at Hanyang University, where he conducted advanced research in nanoscale characterization and the study of plasma interactions with materials.

Awards & Honors

Dr. Yadav’s exceptional contributions to molecular dynamics, drug design, and plasma medicine have earned him recognition as one of the top 2% scientists worldwide. He has received numerous prestigious awards, including research grants from major funding agencies such as the National Research Foundation of Korea (NRF) and Science & Engineering Research Board (SERB). His achievements in interdisciplinary research, particularly in computational biology and cancer therapy, have also led to invitations to deliver keynote speeches at international conferences. Dr. Yadav is highly regarded for his leadership in advancing computational tools for drug discovery and plasma applications in medicine.

Top-Noted Publications

Dr. Yadav’s academic work has been widely published in high-impact journals and presented at international conferences. His publications on molecular dynamics simulations of reactive oxygen species (ROS) in plasma medicine are among the most cited in the field. Notable publications include studies on the interaction of plasma-generated ROS with native and oxidized lipid membranes and their implications for cancer therapy. His research on QSAR modeling for anticancer compounds has influenced the development of new drug discovery approaches. Dr. Yadav’s contributions have significantly advanced the understanding of plasma-biomolecule interactions, making him a leading authority in computational toxicology and drug design.

  • Epigallocatechin 3-gallate: From green tea to cancer therapeutics

    • Citations: 193

    • Published: 2022

    • This one explores the potential of EGCG (a key component of green tea) in cancer treatment. Green tea’s bioactive compounds, like EGCG, have been linked to a variety of health benefits, including anti-cancer effects.

  • Biomedical features and therapeutic potential of rosmarinic acid

    • Citations: 168

    • Published: 2022

    • This article focuses on rosmarinic acid, which is found in herbs like rosemary and basil. It has antioxidant, anti-inflammatory, and antimicrobial properties, making it a great candidate for therapeutic applications.

  • Influence of reactive species on the modification of biomolecules generated from the soft plasma

    • Citations: 140

    • Published: 2015

    • This paper looks at how reactive species (like free radicals) interact with biomolecules, a topic of interest in plasma medicine and biotechnology.

  • Molecular dynamic simulations of oxidized skin lipid bilayer and permeability of reactive oxygen species

    • Citations: 118

    • Published: 2019

    • This publication discusses how reactive oxygen species (ROS) affect the permeability of skin lipid bilayers, which could have implications for skin health, drug delivery, and cosmetics.

  • Identification of novel acetylcholinesterase inhibitors designed by pharmacophore-based virtual screening, molecular docking and bioassay

    • Citations: 100

    • Published: 2018

    • This one focuses on drug discovery for neurodegenerative diseases by identifying compounds that inhibit acetylcholinesterase, an enzyme linked to Alzheimer’s disease.

Abhishek Bansal, Medicine, Best Researcher Award

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Doctorate Abhishek Bansal: Assistant professor at The oxford medical college hospital and research centre, India

Dr. Abhishek Bansal is a distinguished clinical biochemist with a deep focus on the biochemical underpinnings of diabetes, metabolic syndrome, kidney disorders, and molecular signaling. With an academic background including a Ph.D. in Medical Biochemistry from Malwanchal University, Indore, Dr. Bansal has established himself as a prominent researcher and educator. His work revolves around understanding chronic diseases and their biomarkers, contributing significantly to the advancement of clinical diagnostics. Dr. Bansal has authored 33 publications, including books, book chapters, and research articles, and has participated in numerous international workshops, enhancing his expertise in medical biochemistry and molecular diagnostics. He is currently an Assistant Professor at The Oxford Medical College, Hospital & Research Centre, Bangalore, where he continues to advance the field of biochemistry and mentor the next generation of researchers.

Online Profiles

Education

Dr. Abhishek Bansal’s educational journey is marked by rigorous academic training in medical biochemistry. He completed his Ph.D. in Medical Biochemistry at Malwanchal University, Indore in 2024, where his research focused on the evaluation of biomarkers for chronic kidney disease, a project supervised by Dr. Shreya Nigoskar. His M.Sc. in Medical Biochemistry was awarded by Jawaharlal Nehru Medical College, KAHER, Belagavi in 2020. His master’s thesis explored the correlation between plasma ascorbate levels and Type 2 diabetes management, supervised by Dr. Chetana P. Hadimani. Dr. Bansal’s foundational training began with a B.Sc. in Medical Laboratory Technology from MM(DU), Mullana, Haryana in 2016, where he was introduced to clinical laboratory technologies and methodologies. This combination of academic rigor and hands-on research experience has equipped him with a comprehensive understanding of medical biochemistry and clinical diagnostics.

Research Focus

Dr. Bansal’s research is deeply rooted in the intersection of clinical biochemistry, diabetes, metabolic syndrome, and kidney disorders. His research interests are specifically concentrated on identifying novel biomarkers that could improve the early detection, diagnosis, and management of chronic kidney disease (CKD) and metabolic diseases. He is particularly interested in molecular signaling pathways and their alterations in chronic diseases such as Type 2 diabetes and kidney dysfunction. Dr. Bansal’s recent work has led to an exploration of human neutrophil gelatinase-associated lipocalin (NGAL), asymmetric dimethylarginine (ADMA), and kidney injury molecule-1 (KIM-1) as promising biomarkers for CKD, which could significantly improve clinical outcomes through early intervention.

Experience

Dr. Bansal has accumulated diverse teaching and research experience in academic and clinical settings. He began his teaching career as a Tutor/Demonstrator in the Department of Biochemistry at Government Medical College, Rajouri (Aug 2021 – Apr 2022), where he helped students understand clinical biochemistry concepts and laboratory techniques. He later joined Pt. BDS PGIMS, Rohtak, where he continued in a similar role, further honing his teaching and research skills. Since June 2024, Dr. Bansal has been serving as Assistant Professor in the Department of Biochemistry at The Oxford Medical College, Hospital & Research Centre, Bangalore. In this position, he teaches undergraduate and postgraduate students, mentors research projects, and contributes to departmental initiatives in medical research.

Research Timeline

  • 2024: Ph.D. in Medical Biochemistry, Malwanchal University, Indore – Thesis on kidney disease biomarkers.

  • 2020: M.Sc. in Medical Biochemistry, Jawaharlal Nehru Medical College, KAHER, Belagavi – Research on plasma ascorbate levels in Type 2 diabetes.

  • 2016: B.Sc. in Medical Laboratory Technology, MM(DU), Mullana, Haryana – Gained foundational knowledge in clinical laboratory techniques.

  • Aug 2021 – Apr 2022: Tutor/Demonstrator, Govt. Medical College, Rajouri

  • Apr 2022 – May 2024: Tutor/Demonstrator, Pt. BDS PGIMS, Rohtak

  • Jun 2024 – Present: Assistant Professor, The Oxford Medical College, Hospital & Research Centre, Bangalore

  • 2018-2020: Conducted research on Vitamin C’s impact on Type 2 diabetes as part of M.Sc. thesis.

Awards & Honors

Dr. Bansal’s exceptional contributions to the field of medical biochemistry have earned him several prestigious fellowships and honors. He holds the title of FMIIP (Fellow, Medical and Industrial Institute of Pathology), FMERU (Fellow, Medical Education and Research University), and FMERC (Fellow, Medical and Educational Research Council), marking his academic excellence and contributions to clinical research. These recognitions are a testament to his sustained commitment to advancing medical education and clinical biochemistry.

Top-Noted Publication

Dr. Bansal’s research on chronic kidney disease biomarkers is widely regarded as one of his most impactful contributions. His doctoral thesis titled, “Evaluation of Serum Human Neutrophil Gelatinase-Associated Lipocalin, Asymmetric Dimethylarginine, Kidney Injury Molecule-1, and Beta-Trace Protein as Potential Biomarkers of Chronic Kidney Disease”, has been published in leading international journals. This work is a significant step forward in the identification of non-invasive biomarkers that can aid in the early diagnosis and prognosis of chronic kidney disease. His contributions to biochemistry and nephrology are shaping new approaches in clinical diagnostics.

1. Evaluating Asymmetric Dimethylarginine (ADMA) as a Biomarker for Preeclampsia: A Meta-Analysis

  • Journal: Journal of Neonatal Surgery

  • Year: 2025

  • DOI: 10.52783/jns.v14.1599

  • EID: 2-s2.0-85218718990

  • ISSN: 2226-0439

  • Contributors: Bansal, A.; Hadimani, C.P.; Patil, S.B.; Lah, N.A.Z.B.N.

  • Summary: This meta-analysis evaluates the potential of Asymmetric Dimethylarginine (ADMA) as a reliable biomarker for predicting preeclampsia, a condition that affects pregnant women and can lead to serious complications. This research contributes to improving early detection and management strategies for preeclampsia.

2. Serum Adipsin Levels as a New Marker in Type 2 Diabetes Mellitus: A Meta-Analysis

  • Journal: International Journal of Diabetes in Developing Countries

  • Year: 2025

  • DOI: 10.1007/s13410-025-01449-2

  • EID: 2-s2.0-85217198282

  • ISSN: 0973-3930, 1998-3832

  • Contributors: Bansal, A.; Honnapurmath, V.K.; Singh, A.

  • Summary: This meta-analysis investigates the relationship between serum adipsin levels and Type 2 diabetes mellitus (T2DM). The study highlights adipsin as a promising new biomarker for the disease, offering potential for improved diagnosis and therapeutic strategies in diabetic care.

3. Serum Fetuin-A as a Biomarker for Gestational Diabetes Mellitus: A Meta-Analysis

  • Journal: International Journal of Diabetes in Developing Countries

  • Year: 2025

  • DOI: 10.1007/s13410-025-01507-9

  • EID: 2-s2.0-105007297404

  • ISSN: 0973-3930, 1998-3832

  • Contributors: Bansal, A.; Pragaspathy, V.

  • Summary: This article explores the role of fetuin-A as a potential biomarker for gestational diabetes mellitus (GDM). By conducting a comprehensive meta-analysis, the study supports fetuin-A’s potential in predicting GDM, which could lead to better management and outcomes for pregnant women.

4. AEFI (Adverse Events Following Immunization) Among Children Less Than 2 Years Following Pentavalent Vaccine: A Cross-Sectional Study in India

  • Journal: Journal of Pharmaceutical and Therapeutic Research

  • Year: 2024

  • DOI: 10.53555/jptcp.v31i3.4779

  • Contributors: Dixit, P.; Prashant, P.; Gera, V.; Bansal, A.; Bansal, A.

  • Summary: This cross-sectional study investigates the adverse events following immunization (AEFI) in children under 2 years old in India after receiving the Pentavalent vaccine. The study provides valuable insights into vaccine safety and emphasizes the importance of monitoring adverse events post-vaccination.

5. Development of an Anti-Microbial Starch-Based Polymer Film Embedded with Silver Nanoparticles by Green Synthesis from Tea Extract: A Potential Low-Cost Wound Dressing for Rural Populations in Developing Countries

  • Journal: International Journal of Biomedical Nanoscience and Nanotechnology

  • Year: 2024

  • Report Type: Research Report

  • Contributors: Dinda, S.; Patil, A.B.; Hogade, S.A.; Bansal, A.

  • Summary: This innovative report outlines the development of a starch-based polymer film containing silver nanoparticles, synthesized through a green process using tea extract. The wound dressing, aimed at rural populations in developing countries, offers a low-cost, effective solution for wound care and antimicrobial protection.

Muhammad Ahmad, Computer Science, Best Researcher Award

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Doctorate Muhammad Ahmad: Student at University of Electronic Science and Technology of China, China

Muhammad Ahmad is a passionate AI researcher and software engineer with expertise in generative AI, deep learning, and medical image analysis. Currently, he is pursuing a Master’s degree in Information and Communication Engineering at the University of Electronic Science and Technology of China (UESTC), where he maintains a strong academic record with a GPA of 3.54/4.0. Muhammad combines his solid theoretical background with hands-on experience in developing innovative AI models, focusing on healthcare applications to improve diagnostic accuracy and patient outcomes.

Online Profiles

ORCID Profile

Education

Muhammad completed his Bachelor of Science in Computer Science from the University of South Asia in Lahore, Pakistan, graduating with a CGPA of 3.16/4.0. During his undergraduate studies, he conducted a notable final year project on Walmart Weekly Sales Prediction using machine learning techniques. Currently, he is advancing his knowledge and research capabilities through a fully funded Master’s program at UESTC, China, where his studies focus on cutting-edge topics such as large language models, generative AI, and medical imaging technologies.

Research Focus

His research is concentrated on the application of deep learning and generative AI methods to medical imaging, particularly focusing on neurodegenerative diseases and brain tumor diagnostics. Muhammad explores the fusion of local and global image features using hybrid architectures and leverages large language models (LLMs) to improve the interpretability and accuracy of medical image analysis, aiming to develop scalable AI solutions for early disease detection and prognosis.

Experience

Muhammad has garnered practical industry experience as a Software Engineer specializing in Artificial Intelligence at E-teleQuote Inc. in Florida, USA, where he led projects on generative AI, real-time chatbot development, and speech-to-text and sentiment analysis technologies. Prior to this, he completed a Machine Learning internship at Quid Sol in Lahore, Pakistan, where he built data pipelines, implemented machine learning algorithms for object detection and tracking, and developed custom deep learning models, strengthening his skills in feature engineering and AI optimization.

Research Timeline

In June 2025, Muhammad published a peer-reviewed article on a hybrid deep learning architecture with adaptive feature fusion for Alzheimer’s disease classification in Brain Sciences. In May 2025, he submitted a manuscript detailing a novel method for dynamic fusion of local and global features aimed at improving brain tumor diagnosis to the International Journal of Machine Learning and Cybernetics. These works reflect his commitment to advancing AI-driven medical research through innovative model designs and rigorous evaluation.

Awards & Honors

Muhammad’s academic excellence and community contributions have been recognized through several awards, including a fully funded scholarship for his Master’s degree at UESTC. He earned a semester scholarship for excellence in a machine learning workshop and received volunteer recognition for his active role in community welfare initiatives through the Rooh Foundation. Additionally, he has demonstrated his technical prowess by winning first and second positions in competitive web development contests hosted by COMSATS University and Superior University, respectively.

Top-Noted Publication

Muhammad’s most notable publication, “Hybrid Deep Learning Architecture with Adaptive Feature Fusion for Multi-Stage Alzheimer’s Disease Classification,” published in Brain Sciences in 2025, presents an innovative approach that integrates multiple feature sets for more accurate staging of Alzheimer’s disease. This research contributes significantly to the field of AI-assisted medical diagnostics by enhancing feature representation and classification performance, offering a promising tool for clinical applications.

Hybrid Deep Learning Architecture with Adaptive Feature Fusion for Multi-Stage Alzheimer’s Disease Classification
Brain Sciences | 2025-06-06
DOI: 10.3390/brainsci15060612
Contributors: Ahmad Muhammad, Qi Jin, Osman Elwasila, Yonis Gulzar

Abstract (expanded):
This article introduces a novel hybrid deep learning architecture designed to enhance the classification of Alzheimer’s disease (AD) through the integration of adaptive feature fusion. The model combines both global and local features from neuroimaging data, optimizing classification performance across multiple stages of Alzheimer’s disease. The study leverages convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to process and fuse brain images for a more accurate disease diagnosis and staging. By enhancing feature extraction with adaptive fusion techniques, the architecture outperforms traditional methods in terms of accuracy and reliability.

Key Contributions:

  1. Hybrid Model Design: The integration of CNNs for feature extraction and RNNs for sequence learning provides a comprehensive framework for Alzheimer’s classification.

  2. Adaptive Feature Fusion: The study proposes a dynamic fusion strategy that adapts to various stages of the disease, improving classification precision.

  3. Stage-Specific Diagnosis: The model successfully categorizes Alzheimer’s at different stages, addressing the clinical challenge of early-stage detection.

Impact & Relevance:
This work is a significant step forward in the use of AI for medical diagnostics, particularly for neurodegenerative diseases. The proposed model has the potential to aid clinicians in diagnosing Alzheimer’s disease at earlier stages, leading to better patient outcomes. It highlights the growing role of deep learning in medical image analysis and opens doors for future research on hybrid architectures in healthcare.

Khadija Daoud, Public Health, Best Researcher Award

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Doctorate Khadija Daoud: Phd Student at Sciences and Engineering of Biomedicals, Biophysics and Health Laboratory, Higher Institute of Health Sciences, Hassan First University, Settat, Morocco

Khadija Daoudi is a dedicated PhD candidate in Health Sciences at the Higher Institute of Health Sciences – Hassan, with a strong foundation in nursing sciences and health education. She specializes in analyzing communication patterns within health education sessions to improve interaction between educators and students, ultimately enhancing health literacy and patient care. Khadija combines her research expertise with practical teaching experience, demonstrating leadership, resilience, and a commitment to advancing health education in Morocco and beyond. Her multidisciplinary approach integrates analytical thinking and interpersonal skills to address real-world healthcare challenges.

Online Profiles

ORCID Profile

Khadija Daoudi is affiliated with Université Hassan 1er, Settat, Morocco. She is registered on Scopus under ID 59152670500 and has an ORCID profile (0009-0003-3220-6492) that catalogs her research output. Her academic work includes 3 published documents, which have been cited 6 times, resulting in an h-index of 1. Khadija’s research profile is also connected to Mendeley, providing further access to her publications and collaborations within the academic community.

Education

Khadija earned her Bachelor’s Degree in Nursing Sciences from the Higher Institute of Health Sciences – Settat, equipping her with both theoretical knowledge and practical clinical skills. She is currently pursuing a PhD in Health Sciences at the Higher Institute of Health Sciences – Hassan, where she focuses on interaction analysis in health education settings. Prior to this, she completed her Baccalaureate with honors in the Science Track, demonstrating a strong academic foundation and commitment to scientific research from an early stage in her education.

Research Focus

Her research centers on the psychometric evaluation and application of the Roter Interaction Analysis System (RIAS) in Moroccan health education contexts, aiming to better understand communication dynamics between educators and students. She investigates how these interactions influence health education outcomes and behavior change. Additionally, Khadija explores the role of advanced nursing practice in palliative care, conducting rapid reviews to identify best practices and improve patient care delivery. Her work bridges the gap between communication theory and healthcare practice.

Experience

Since 2018, Khadija has worked as a teacher under the Ministry of National Education in the Province of Settat, Morocco. In this capacity, she delivers health education, develops curricula, and fosters effective communication skills among students. Her teaching approach is enriched by her multilingual abilities: she is a native Arabic speaker and proficient in French and English (both at C1 level), with intermediate proficiency in Spanish (B1). This linguistic versatility enables her to engage a diverse student body and adapt educational content to varied audiences.

Research Timeline

Khadija’s research trajectory includes several key scholarly contributions. In 2024, she published a scoping review on educator-student communication patterns in health education, followed by a rapid review on advancing palliative care through advanced nursing practice. Her most recent publication in 2025 focuses on the psychometric properties of the Roter Interaction Analysis System within Moroccan schools, reflecting her ongoing commitment to enhancing health communication research. These publications highlight her consistent academic productivity throughout her doctoral studies.

Awards & Honors

Throughout her academic career, Khadija has consistently demonstrated excellence, graduating with honors in her Baccalaureate Science Track. Her research has been recognized through multiple peer-reviewed journal publications, establishing her reputation as a dedicated and impactful scholar in health sciences. She continues to strive for academic and professional excellence, contributing valuable insights to health education and nursing practice research in Morocco and internationally.

Top-Noted Publication

One of Khadija’s most significant works is “Psychometric characteristics of Roter Interaction Analysis System (RIAS) in the context of health education in a Moroccan school,” published in PEC Innovation in 2025. Co-authored with Khaoula Jounaidi and Abdellah Gantare, this study evaluates the reliability and validity of RIAS as a communication assessment tool in Moroccan health education settings. The publication has important implications for improving educator training and patient communication strategies, offering a culturally relevant perspective that enhances health education effectiveness in Morocco and similar contexts.

Top-Noted Publication

Khadija’s landmark publication, “Psychometric characteristics of Roter interaction analysis system (RIAS) in the context of health education in a Moroccan school,” published in PEC Innovation in 2025, offers critical validation of an established communication analysis tool within a unique cultural context. This work has significant implications for improving health educator training and optimizing communication strategies to enhance patient outcomes in Morocco and similar settings.

  • Psychometric characteristics of Roter Interaction Analysis System (RIAS) in the context of health education in a Moroccan school

    • Journal: PEC Innovation

    • Date: June 2025

    • DOI: 10.1016/j.pecinn.2025.100403

    • ISSN: 2772-6282

    • Contributors: Khadija Daoudi, Khaoula Jounaidi, Abdellah Gantare

  • Advancing Palliative Care through Advanced Nursing Practice: A Rapid Review

    • Journal: Indian Journal of Palliative Care

    • Date: 2024

    • DOI: 10.25259/IJPC_308_2023

    • ISSN: 1998-3735, 0973-1075

    • Contributors: K. Jounaidi, M. Hamdoune, K. Daoudi, N. Barka, A. Gantare

  • Exploring Educator-Student Communication Patterns in Health Education Settings: A Scoping Review

    • Journal: Pakistan Journal of Life and Social Sciences

    • Date: 2024

    • DOI: 10.57239/PJLSS-2024-22.1.00375

    • ISSN: 2221-7630, 1727-4915

    • Contributors: Khadija Daoudi, Abdellah Gantare

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

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

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