Mr Pranab Das, NIT Nagaland, India
Pranab Das is an Assistant Professor in the Department of Computer Science at Kumar Bhaskar Varma Sanskrit and Ancient Studies University, Assam. He holds an M.Tech in Computer Science from NIT Meghalaya and has submitted his Ph.D. thesis at NIT Nagaland. His research focuses on computational biology, drug discovery, and machine learning 🧬🤖. With multiple SCIE and SCI-indexed publications in top journals, he has made significant contributions to predicting drug functions and adverse reactions. Additionally, he has presented at international conferences and authored book chapters 📚. He has qualified JRF, NET, and SLET, showcasing his academic excellence.
Publication Profile
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Education
Pranab Das is a dedicated researcher in Computer Science and Engineering (CSE), currently awaiting the completion of his Ph.D. (2021-2024) from the National Institute of Technology (NIT) Nagaland, where he achieved an impressive 9.23 CGPA 🎓. He holds an M.Tech in CSE (2019-2021) from NIT Meghalaya with a 9.27 CGPA 🏆 and a BE in CSE (2015-2018) from Jorhat Engineering College, securing 73.89% 📚. His academic journey began with a Diploma (70%) from Assam Engineering Institute and 10th grade (66.17%) from Barnibari Milan High School. Additionally, he has cleared JRF, NET, and SLET 🔬✅.
Project Work
Pranab Das is an accomplished researcher specializing in computational biology and drug discovery 🔬💊. His latest work, “MLCNNF: A Multi-Label Convolutional Neural Network Framework for Predicting Adverse COVID Drug Reactions”, is published in IEEE Transactions on Computational Biology and Bioinformatics (2025) 📄. He has also co-authored “BRMCF: Binary Relevance and MLSMOTE-Based Computational Framework” (2022) and “Advances in Predicting Drug Functions” (2023). His research extends to machine learning applications in pharmacology, including drug classification and side-effect prediction 🧠📊. With publications in high-impact journals (IF: 2.4-23.8) 📈, Pranab contributes significantly to AI-driven drug discovery 🚀.
Area of Intrest
Pranab Das is deeply passionate about cutting-edge technologies in Artificial Intelligence (AI) 🤖, Machine Learning (ML) 📊, and Deep Learning (DL) 🧠, with a strong focus on their applications in Bioinformatics 🔬. His research explores innovative AI-driven solutions for drug discovery, predictive modeling, and computational biology. By leveraging ML and DL techniques, he aims to enhance drug function prediction, side-effect analysis, and disease modeling. His interdisciplinary approach bridges technology and life sciences, driving impactful advancements in healthcare and pharmaceuticals 💊. Pranab continues to push the boundaries of AI in biomedical research, shaping the future of intelligent drug discovery 🚀.
Research Focus
Pranab Das is a researcher specializing in computational biology, bioinformatics, and artificial intelligence in drug discovery 🧬💻. His work primarily focuses on predicting drug functions, adverse drug reactions, and drug-disease associations using multi-label machine learning and deep neural networks 🤖🧪. He has contributed extensively to the field through innovative frameworks like MLCNNF, K1K2NN, and BRMCF, integrating chemical structures, gene ontology, and biological properties for enhanced drug prediction accuracy 🏥🔬. His research advances COVID-19 drug safety, pharmacology, and computational chemistry, making significant contributions to the intersection of AI and healthcare 🏥📊.
Publication Top Notes