Doctorate Shashi Bhushan: Senior Lecturer at University Teknologi PETRONAS, Malaysia
Dr. Shashi Bhushan is a highly accomplished Associate Professor at Universiti Teknologi PETRONAS (UTP), Malaysia, affiliated with the Centre for Intelligent Signal and Imaging Research (CISIR). With a robust background in computer science and computational intelligence, he has established himself as a leading researcher in biomedical image processing and signal analysis. Over the years, Dr. Bhushan has developed an interdisciplinary research portfolio that integrates artificial intelligence, deep learning, and medical diagnostics. His work is dedicated to solving real-world problems in healthcare, focusing on automated systems for disease detection, classification, and decision support. He actively collaborates with national and international institutions and contributes as a reviewer and editor for several high-impact scientific journals.
Online Profiles
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Citations: 703
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h-index: 17
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i10-index: 26
Dr. Shashi Bhushan maintains an active online academic presence through several platforms. His UTP official profile provides detailed information on his teaching, research interests, and institutional contributions. His Scopus profile showcases his indexed publications and citation metrics, reflecting the impact of his research. Through his Google Scholar page, readers can track his h-index, i10-index, and recent scholarly contributions. On ResearchGate, Dr. Bhushan actively shares preprints, project updates, and engages with the broader research community. These platforms collectively reflect his research influence and collaborative efforts.
Education
Dr. Bhushan holds a Doctor of Philosophy (Ph.D.) in Computer Science with a specialization in computational and biomedical systems. His doctoral work focused on the development of hybrid intelligent algorithms for image classification and signal processing, particularly in the domain of healthcare analytics. Prior to his Ph.D., he earned a Master’s degree and a Bachelor’s degree in Computer Science and Engineering, where he laid the foundational knowledge in programming, machine learning, and embedded systems. His academic training has enabled him to bridge the gap between traditional computing and next-generation intelligent systems for practical, high-impact applications.
Research Focus
Dr. Bhushan’s research primarily lies in the areas of computational intelligence, machine learning, biomedical image processing, and intelligent signal interpretation. His key interests include the development of AI algorithms for early disease detection, such as brain tumors, breast cancer, and neurodegenerative conditions. He also investigates EEG and ECG signal analysis for predictive diagnostics and real-time monitoring. His recent work focuses on convolutional neural networks (CNNs), hybrid feature extraction techniques, deep belief networks (DBNs), and fuzzy logic systems. With a commitment to practical relevance, his research often results in prototype systems and software tools for medical professionals and researchers.
Experience
Dr. Bhushan brings over 15 years of academic and research experience to his role as Associate Professor at Universiti Teknologi PETRONAS. Throughout his career, he has taken on responsibilities as a lecturer, supervisor, research leader, and technical committee member. He has supervised multiple Ph.D. and Master’s students, and he has published extensively in reputed journals and conferences. Dr. Bhushan has secured numerous research grants and has led projects involving AI-based healthcare applications and intelligent signal systems. Beyond research, he is also active in academic governance, curriculum development, and mentoring young researchers, contributing holistically to academic excellence.
Research Timeline
Dr. Bhushan’s research trajectory reflects continuous growth and innovation. From 2010 to 2015, during his Ph.D. years, he developed hybrid intelligent models for image processing. Between 2016 and 2019, he expanded his work into biomedical applications, specifically targeting brain imaging and EEG-based analysis. From 2020 onward, his focus has been on integrating deep learning with classical signal processing techniques to enhance the accuracy and speed of automated diagnostic systems. His recent work also includes AI-powered frameworks for real-time healthcare monitoring and cross-disciplinary projects involving industrial and academic partners.
Awards & Honors
Dr. Bhushan has received several accolades in recognition of his scholarly contributions. He has been awarded multiple Best Paper Awards at international IEEE and Scopus-indexed conferences. His innovative work in biomedical signal classification earned him research excellence awards from UTP and other collaborating institutions. He has also received prestigious grants and funding from government and industry for leading-edge projects in artificial intelligence and healthcare technology. His research impact is acknowledged globally through invitations as keynote speaker, session chair, and editorial board member of reputed journals.
Top-Noted Publication
Among Dr. Bhushan’s impactful publications, his paper titled “A hybrid model for brain tumor classification using convolutional neural networks and handcrafted features” published in Biomedical Signal Processing and Control stands out. This work combines deep learning with traditional feature extraction to create a robust diagnostic tool capable of classifying complex brain tumor types with high accuracy. The study is widely cited and has influenced subsequent research in AI-assisted medical imaging. It demonstrates Dr. Bhushan’s unique ability to merge theory with clinical relevance, leading to improved decision support tools in radiology and oncology.
- Code-Switching ASR for Low-Resource Indic Languages: A Hindi-Marathi Case Study
Authors: H Palivela, M Narvekar, D Asirvatham, S Bhusan, V Rishiwal, U Agarwal
Published in: IEEE Access, 2025 - Design and Study of Single Array and 2 x 2 Array Patch Array Antenna
Authors: AR Sharmila, AK Singh, S Bhushan
Published in: Proceedings of the 4th International Conference on Machine Learning, Advances in …, 2025 - Beyond Blockchain: Reviewing the Impact and Evolution of Decentralized Networks
Authors: RKYMK Shashi Bhushan, Sharmila Arunkumar, Neha Goel
Published in: 2024 - DeepSplice: A Deep Learning Approach for Accurate Prediction of Alternative Splicing Events in the Human Genome
Authors: M Abrar, D Hussain, IA Khan, F Ullah, MA Haq, MA Aleisa, A Alenizi, …
Published in: Frontiers in Genetics, 2024 - Design and Study of Single Array and 2× 2 Array Patch Array Antenna
Authors: A Rajeev, AK Singh, S Bhushan, DD Dominic
Published in: International Conference on Machine Learning, Advances in Computing …, 2024