The Tiwary Group at
University of Maryland, College Park
Current research highlight
Our new algorithm RAVE (Reweighted autoencoded variational Bayes) iterates between rounds of deep learning and molecular dynamics to learn both (a) an approximate but physically interpretable reaction coordinate and (b) probability distribution along this reaction coordinate. On the left, we show RAVE applied to the unbinding of a model ligand-cavity system in explicit water.
Reference: Ribeiro, Bravo, Wang & Tiwary, J Chem Phys (in press)
See previous research highlights on our research page
The Tiwary group does inter-disciplinary theoretical and computational research to model and predict thermodynamics, dynamics and their interplay in complex real-world systems, relevant to biophysical, chemical and materials sciences. A common theme across these diverse systems is that many of these are plagued with hard to model rare events. To tackle these we develop and use theoretical and computational tools drawing primarily from statistical mechanics, information theory and machine learning.
ABOUT PRATYUSH TIWARY:
I am an Assistant Professor at the University of Maryland, College Park. I have a joint position in the Department of Chemistry and Biochemistry and the Institute for Physical Science and Technology. I am also an affiliated faculty member of the Chemical Physics program and the Biophysics program. I can be reached on my office phone 301 405 2148. My office address is Room 1115A, Institute for Physical Science and Technology (Building 085), University of Maryland, College Park, MD 20742.
I am a theoretical and computational chemist interested broadly in kinetics and its interplay with thermodynamics in biological and material systems plagued with slow to sample rare events. I received my PhD and MS in Materials Science from Caltech, working with Axel van de Walle, and finished my undergraduate degree in Metallurgical Engineering at the Indian Institute of Technology, Banaras Hindu University, Varanasi. Prior to starting my tenure-track position, I have been a postdoc in the Department of Chemistry at Columbia University, where I worked with Bruce Berne, and at the Department of Chemistry & Applied Biosciences at ETH Zurich, where I worked with Michele Parrinello.
This year (2017-2018) I am co-organizing the Informal Statistical Physics seminar series with Chris Jarzynski. Please email me if you have suggestions for speakers!
- April 19, 2018: 3 students will be joining us for summer research: (i) Danielle Sidelnikov is a sophomore towards double major in Neurobiology & Physiology and History. (ii) Netsanet Woldegerima is a 1st year Medicine student at the University of Maryland, School of Medicine, and a winner of the competitive UM Scholars Program. (iii) Kliment Ziko is an incoming 1st year graduate student in Chemistry. Welcome to all three young scientists!
- March 13, 2018: Our new manuscript "Reweighted autonecoded variational Bayes for enhanced sampling (RAVE)", which is an iterative deep learning- molecular dynamics scheme to enhance sampling of molecular systems, is accepted for publication in Journal of Chemical Physics. Pre-print: arXiv
- February 28: The paper "Predicting reaction coordinates in energy landscapes with diffusion anisotropy" by Tiwary and Berne has been selected as a 2017 Editor's choice paper at the Journal of Chemical Physics
- February 19: We have received a start-up grant comprising GPU/CPU hours to use RAVE on the national supercomputing resource Bridges maintained by XSEDE
- February 16: Pratyush gave an invited talk at the National Cancer Institute-University of Maryland Annual Symposium
- December 7-10: Chris Jarzynski (Maryland), K Srihari (Kanpur), Nisanth Nair (Kanpur) and Pratyush organized a 3-day international conference on Recent Advances in Modeling Rare Events (RARE) in Agra, India. With 84 participants drawing from over 10 countries, the conference was a huge success.
- November 22, 2017: Pratyush has won the Research and Scholarship Award (RASA) from the Graduate School at the University of Maryland. The objective of the RASA is to support faculty research, scholarship and creative activity, while enhancing graduate student mentoring.