Samrendra Singh

Samrendra Singh is an Adjunct Lecturer in the Department of Computing, Information, Mathematical Sciences, and Technology (CIMST) within the College of Arts & Sciences at Chicago State University. He holds a Ph.D. and M.S. in Biological and Agricultural Engineering from the University of California, Davis, and a B.E. in Agricultural Engineering from Tamil Nadu Agricultural University, India.

Education:

• Ph.D., Biological and Agricultural Engineering, University of California, Davis
• M.Sc., Biological and Agricultural Engineering, University of California, Davis
• B.E., Agricultural Engineering, Tamil Nadu Agricultural University, Trichy, India

His research integrates computational modeling, machine learning, and engineering principles to solve complex problems in materials science, food processing, and thermal systems. He specializes in coarse-grained molecular dynamics, polymer physics, and AI-driven analysis of engineering systems. His work spans from nanomaterials like graphene and MOFs to agricultural product quality assessment using deep learning.

The recent publications (2018–2023) reveal a strong trend in combining machine learning with molecular simulations and food engineering applications. Keywords include computational materials, polymer dynamics, and food process automation, with sub-fields such as thermoresponsive polymers, gas adsorption in MOFs, and neural network-based food grading. His collaborative work emphasizes data-driven discovery and hybrid simulation-AI frameworks.

While no formal scientific awards are listed, his contributions appear in high-impact journals such as The Journal of Physical Chemistry Letters, Macromolecules, Carbon, and Journal of Food Engineering.

He has advised or collaborated on research involving molecular modeling, food quality automation, and thermal system optimization. Though specific grants are not mentioned, his work suggests involvement in interdisciplinary projects at the intersection of computational science and engineering. He has co-authored multiple publications with S.A. Deshmukh and others, indicating strong research team integration.

His research activities involve computational labs focused on molecular dynamics simulations, machine learning model development, and food engineering applications. The use of advanced techniques like convolutional neural networks, particle swarm optimization, and coarse-grained modeling indicates a sophisticated computational research environment.