Home page of Anirvan M. Sengupta |
Position: | Professor |
Email address: | anirvans@physics.rutgers.edu |
Telephone: | (848) 445-3880 |
Office: | Serin E258 |
Mailing address: | Anirvan M. Sengupta Department of Physics and Astronomy Rutgers, The State University of New Jersey 136 Frelinghuysen Road Piscataway, NJ 08854-8019 USA |
For the last few years, I have worked on Machine Learning with the goal of understanding how the brain forms useful representations of the world. In particular, I have explored how matching the similarity of inputs and the similarity of internal representations gives rise to algorithms that can be implemented by neuronal circuits. This work relies upon my experience in Statistical Field Theory as well as on decades developing tools in Machine Learning and Signal Processing for applications motivated by Bioinformatics and Systems Biology.
My work in cellular systems was inspired by questions concerning biological information processing, be it in cell signaling or in gene regulatory networks. Before my time at Rutgers, while at Bell Laboratories, I have also studied engineered information networks. In particular, I am quite fond of our work applying Random Matrix Theory to Information Theory of MIMO wireless systems.
During my time at Ecole Normale Superieure, Paris, and in my early days at Bell Labs, I wrote several papers on Quantum Condensed Matter Physics. These papers brought in tools from Quantum Field Theory, like Bosonization, Large N expansion and Renormalization Group, for analyzing, among other things, Quantum Impurity Problems. My PhD work from Tata Institute of Fundamental Research was on String Theory, analyzing non-critical strings in 1+1 dimension. In particular, that work pointed to a stringy black hole solution. This solution has been used as a toy model for exploring many aspects of black hole physics.
For current information on me, please visit: Personal Home Page.
For my ancient Rutgers home page, please visit: Old Rutgers Home Page.
Link to the research group on Biological Physics.
Revised Aug 3, 2020