Arpan Biswas is a research assistant professor with the University of Tennessee-Oak Ridge Innovation Institute’s Clean Manufacturing and Advanced Materials Convergent Research Initiative. His research expertise is in the fields of design and optimization, machine learning/deep learning and statistical analysis, while his teaching focuses on Artificial Intelligence for Quantum Materials. 

His current research interest is the “application of AI in expensive systems” in the form of classical and quantum physics models, and expensive experiments over scanning probe, scanning tunneling microscopes, pulsed laser diffraction, where he identifies the challenges in classical AI in such experimental study and thereby mitigate with design of ML policy, strategy for human-AI interaction and domain knowledge injection. His research goal is to increase efficiency, alignment and robustness towards accelerating material research and discovery through developing 1) autonomous workflows with advanced Bayesian optimization methods and 2) physics informed deep learning models for improved microscopy data analysis.

Before joining UT-ORII, Biswas was a postdoctoral research associate at Oak Ridge National Laboratory in the division of Center for Nanophase Material Science under Data Nano-Analytics Group.  

Education