Pankaj Mehta

Associate Professor of Physics 

Boston University

Office: SCI 323

Phone: 617-358-6303

Boston University 

Department of Physics

590 Commonwealth Avenue,

Boston, MA 02139

Email: pankajm AT bu.edu

Aspiring to be the J Dilla of theoretical biophysics

Cirriculum vitae

Research Interests:

I am interested in theoretical problems at the interface of physics and biology (and more and more these days Machine Learning).  I want to understand how large-scale, collective behaviors observed in biological systems emerge from the interaction of many individual components -- whether it be molecules that allow cells to do complex computations, the emergence of cell fate in development, or trying to identify and explain the emergence of universal statistical behaviors in microbial ecosystems. I also have a deep interest in unsupervised learning methods in Machine Learning.

I am a theoretical physicist but the group's research in quite inter-disciplinary. I am part of the BU Microbiome Initiative, BU Bioinformatics Program, the BUMC Center for Regenerative Medicine (CReM), and the BU Biological Design Center. To find out more about my research please look at my publications with links to pdf files.
Beyond science, I have a running interest in radical politics, sociology, and political economy (much of which I have learned from some wonderful teachers). Some of my writings can be found here.I am a member of Scientists for Bernie and the Boston chapter of Science for the People.

Code generated by the group can be found here.

Group Members:

Bobby Marsland (Biophysics Theory Group Postdoc), Alex Golden (Biophysics Theory Group Postdoc), Wenping Cui (Graduate), Alexandre Day (Graduate), Ching-Hao Wang (Graduate)

Machine Learning Review

Our new Machine Learning review is finally done! Check it out and the 20 Python Notebooks here.

Reinforcement Learning agent learns about Quantum Mechanics

These movies are fun, especially this overview movie.

Alumni:

Postdocs: Charles Fisher (Founder/CEO of machine learning start-up unlearn.AI, San Francisco, CA)
Graduate Students: Javad Noorbakhsh (Senior Research Scientist, Jackson Laboratory in CT), Alex Lang (Deep Learning Scientist, Nutonomy)
Undergrads: Joseph Sarmiego-Evans (Graduate school at Colorado Physics), Steven (Wooseok) Ahn, Maddie Dickens (Berkeley Physics)
Honorary Group Members: Marin Bukov (Betty and Gordon Moore Postdoc, Berkeley), Josh Goldford (Computational Biologist at Agios), Ed Reznik (MSKCC Computational Oncology Faculty)

Other Friends/Regular Collaborators of the group:

Ariel Amir, BU CReM, Balazsi Lab, Caleb Bashor, Claudio Chamon, Kirill Korolev , Arvind Murugan, Anatoli Polkovnikov, Ed Reznik, Sanchez Lab, David Schwab, Dries Sels, Segrè Lab, Anirvan Sengupta, Allyson Sgro, Ned Wingreen.

Current projects:

Collective behavior in Dictyostelium 

Information Processing in Synthetic Biology  

Cellular reprogramming and cell fate 

Quantitative microbial ecology 

Statistical mechanics, machine learning, and large biological data sets

Physics problems inspired by biological systems

Nonequilibrium statistical physics

Videos of recent talks:

Towards a Statistical Mechanics of Microbiomes, PCTS Bridging Theory and Experiment in Microbial Communities (Dec,2018): video
From Reinforcement Learning to Spin Glasses: The Many Surprises in Quantum State Preparation, PhysicsNext Workshop (Oct,2018): video
Statistical physics approaches to community ecology, KITP (Aug, 2017): video

Energy, information, and computation in cells at the ICTS Winter school on quantiative biology (Dec.2015): Part 1,Part 2, Part 3
Adventures at the interface of physics and Biology, KITP (Jan 2015): video
Dictyostelium populations exploit noise to control collective behavior, BIRS Workshop on Stochasticity in Biochemical Reaction Networks, (Sept 2013): video

Publications:

To find out more about my research please look at my publications with links to pdf files.

Funding: