About

Arpit Bansal is a PhD scholar at the State University of New York at Buffalo, where he is pursuing his doctoral degree in Chemical and Biological Engineering. His research interests lie at the intersection of Deep Learning and Statistical Mechanics, and he is currently working under the supervision of Dr. David Kofke and Dr. Johannes Hachmann. Arpit's work involves developing new methods and algorithms to improve the accuracy and efficiency of molecular simulations. Before joining the PhD program, Arpit worked as a Global Statistics Co-op at Bristol Myers Squibb, where he gained valuable experience in statistical analysis and data modeling. He has also worked as a Graduate Research Assistant at the University at Buffalo and as a Summer Research Intern at National Tsing Hua University in Taiwan. Arpit completed his Bachelor of Technology in Chemical Engineering from the Indian Institute of Technology, Roorkee in 2017. He has also completed his high school education from Silver Line School. Arpit's research interests and academic background have given him a strong foundation in deep learning and research science. Arpit's technical skills include deep learning and statistical analysis, and he has relevant experience of 1.20 years. He is a highly motivated individual who is passionate about using his skills and knowledge to solve complex problems in the field of Chemical and Biological Engineering. Overall, Arpit Bansal is a talented and driven PhD scholar with a strong background in chemical engineering and deep learning. His research interests and technical skills make him a valuable asset to any organization in the field of research science.