Assistant Professor | Dibrugarh University | India
Dr. Subrata Sinha is a distinguished researcher and academic affiliated with Brainware University, Kolkata, India, specializing in computational biology, bioinformatics, and machine learning applications in biomedical research. His expertise spans the development and application of advanced computational models, including convolutional neural networks for brain tumor classification, in silico pharmacophore modeling, and network pharmacology analyses for therapeutic discovery. Dr. Sinha has contributed significantly to bridging computational techniques with practical biomedical applications, demonstrating a strong commitment to translational research that benefits both scientific advancement and societal health outcomes. Over his career, he has published extensively in peer-reviewed journals, fostering collaborations with a wide network of international co-authors and research groups. His work emphasizes precision medicine, predictive modeling, and integrative approaches that combine molecular insights with computational strategies to address complex biomedical challenges. Dr. Sinha’s research not only advances academic understanding but also holds potential for real-world applications in diagnostics, drug discovery, and healthcare technology development. His contributions are recognized for their methodological rigor, innovative approach, and relevance to pressing global health issues. Dr. Sinha’s academic influence and research productivity are reflected in his metrics: 78 citations, 36 documents, and an h-index of 4.
Featured Publications
Akermi, S., Chaari, M., Elhadef, K., Sharma, A., Dey, A., Choudhary, A., Sinha, S., Festuccia, R., Mellouli, L., & Smaoui, S. (2025). Bioactive compounds and cancer prevention: A nutritional approach. In Unleashing the Power of Functional Foods and Novel Bioactives (pp. xx–xx). Elsevier.
Sinha, S., Mali, S., Pathak, A. K., & Rajkhowa, S. (2025). BRAIN-SCN-PRO: A machine learning model for the classification of brain tumors using a convolutional neural network architecture. Biomedical Signal Processing and Control.
Akermi, S., Sharma, A., Dey, A., Chaari, M., Elhadef, K., Choudhary, A., Sinha, S., Mellouli, L., & Smaoui, S. (2025). Functional foods and aging and antiaging: A recipe for longevity. In Unleashing the Power of Functional Foods and Novel Bioactives (pp. xx–xx). Elsevier.
Sinha, S., Mali, S., & Rajkhowa, S. (2025). High-precision lung cancer classification with custom CNN: Evaluation and transfer learning for broader cancer types. Procedia Computer Science.
Mali, S., & Sinha, S. (2025). Histopathological image processing for lung carcinoma classification: A comparative study of stain normalization methods for CNN-based analysis. In 6th IEEE International Conference on Recent Advances in Information Technology (RAIT 2025) (pp. xx–xx). IEEE.
