Nandan Kumar

Dr. Nandan Kumar is a Postdoctoral Researcher in the Department of Grain and Food Science at Kansas State University, USA, where he works under the supervision of Prof. Yonghui Li. He received his Ph.D. in Computational Biology from CSIR-Indian Institute of Chemical Technology (CSIR-IICT), Hyderabad, India, under the guidance of Prof. G. Narahari Sastry, with research focused on molecular modeling & simulations, and computational drug discovery. He was also awarded a Gold Medal for securing first rank in his M.Sc. in Bioinformatics from the Central University of South Bihar, India.

His research lies at the intersection of computational structural biology, artificial intelligence, molecular biophysics, and protein science, with a focus on understanding how protein sequence, structure, dynamics, and environmental factors collectively govern protein function. He integrates protein language models, machine learning, explainable artificial intelligence (XAI), molecular dynamics simulations, and structural bioinformatics to investigate biomolecular recognition, protein aggregation, membrane selectivity, protein–protein interactions, and conformational dynamics.

At Kansas State University, his research focuses on protein biophysics, particularly the molecular behavior of gluten proteins, protein-ice interactions, antifreeze proteins, and bioactive peptides. His work aims to elucidate the molecular mechanisms underlying protein stability, self-assembly, solvent-dependent conformational changes, and functional properties relevant to food science and biotechnology. Dr. Kumar has developed computational frameworks based on pretrained protein language models and deep learning architectures for peptide discovery and protein function prediction, including pLM4CPPs, an AI-driven platform for identifying cell-penetrating peptides. By combining interpretable artificial intelligence with atomistic molecular dynamics simulations, he seeks to bridge predictive modeling with mechanistic understanding, enabling more reliable and biologically meaningful computational discoveries.

He has authored more than 30 peer-reviewed publications in leading international journals. His contributions have been recognized through several honors, including the Outstanding Postdoctoral Research Associate Award from Kansas State University and the DST-INSPIRE Fellowship from the Government of India. His long-term research vision is to establish an independent multidisciplinary research program that integrates artificial intelligence, molecular simulations, and experimental validation to accelerate discoveries in protein and peptide science. He is particularly interested in developing interpretable computational methods that bridge molecular mechanisms with practical applications in food science, biotechnology, pharmaceutical research, and biomolecular engineering.

Research interests

• Artificial Intelligence and Machine Learning for Biomolecular Systems
• Computational Structural Biology
• Multiscale Modeling and Simulation
• Protein Language Models
• Protein Aggregation and Conformational Dynamics
• Cell-Penetrating, Antimicrobial, and Bioactive Peptides
• Food Protein Biophysics
• Protein–Protein and Protein–Membrane Interactions
• Non-covalent Interactions and Molecular Recognition