Pankaj Mehta

Professor of Physics 

Faculty of Computing and Data Science

Biological Design Center

Center for Regenerative Medicine

Boston University

Office: SCI 323

Phone: 617-358-6303

Boston University 

Department of Physics

590 Commonwealth Avenue,

Boston, MA 02139

Email: pankajm AT

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. 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 running interest in problems at the intresection of machine learning and statistical physics.

I am a theoretical physicist but the group's research in quite inter-disciplinary. I am part of the new Faculty of Computing and Data Science, the BU Microbiome Initiative, BU Bioinformatics, the 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. You can also check out my Google Scholar page.

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 also part of the Gracie Barra Boston community.

All our recent codes can be found on our Github repository Emergent Behaviors in Biology. Older code generated by the group can be found here.

Group Members:

Krishna Rijal (Postdoc), Maria Yampolskaya (Graduate Student), Zhijie "Sarah" Feng (Graduate Student), Emmy Blumenthal (Post Bac Researcher), Brock Ewing (undegrad).


Postdocs: Charles Fisher (Founder/CEO of machine learning start-up unlearn.AI, San Francisco, CA), Bobby Marsland (Theology Ph.D.,Pontifical University of the Holy Cross), Alex Golden, Jason Rocks (AI/ML Research Scientist, Dayhoff Labs)

Graduate Students: Javad Noorbakhsh (Computational Scientist II, Broad Institute), Alex Lang ( Director of Perception-Prediction at Motional), Alexandre Day (Lead Data Scientist, Afiniti), Ching-Hao Wang (Machine Learning Scientist, GSK), Wenping Cui (KITP Fellow, UCSB).

Undergrads: Joseph Sarmiego-Evans (Graduate school at Colorado Physics), Steven (Wooseok) Ahn, Maddie Dickens (NSF Graduate Fellowship, Berkeley Physics), Owen Howell (NSF Graduate Fellowship, Chicago Physics)

Honorary Group Members: Marin Bukov (Junior Group Leader and Marie Sklodowska-Curie fellow at the Physics Department, Sofia University), Josh Goldford (Physics of Living Systems Fellow, MIT), Ed Reznik (MSKCC Computational Oncology Faculty)

Other Friends/Regular Collaborators of the group:

Caleb Bashor, Laertis Ikonomou, Kirill Korolev , Arvind Murugan, Anatoli Polkovnikov, Sanchez Lab, David Schwab, Dries Sels, Segrè Lab, Anirvan Sengupta, Allyson Sgro, Ned Wingreen.

Videos of selected talks:

  1. Randomness, Complexity, and the Biological Frontier, ICAM Week of Science (Dec, 2023): video

  2. Towards a theory of microbial ecosystems, Imperial College Londoan Physics of Life Seminar (Dec, 2021): video

  3. Statistical Physics and Machine Learning approaches to biological networks, HHMI Workshop:4D Cellular Physiology Reimagined: Theory as a Principal Component (Sep, 2021): video

  4. Randomness, complexity, and the Biological Frontier, UCR Physics Colloquium (May, 2021): video

  5. Broad MIA Talk on Microbiomes and Metabolism with Josh Goldford, Broad Institute: Models, Inference, and Algorithms seminar (Dec, 2020): video

  6. Towards a Statistical Mechanics of Microbiomes, ICTP Workshop on Systems Biology and Molecular Economy of Microbial Communities (Dec, 2018): video

  7. Towards a Statistical Mechanics of Microbiomes, PCTS Bridging Theory and Experiment in Microbial Communities (Dec, 2018): video

  8. From Reinforcement Learning to Spin Glasses: The Many Surprises in Quantum State Preparation, PhysicsNext Workshop (Oct, 2018): video

  9. Statistical physics approaches to community ecology, KITP (Aug, 2017): video

  10. Energy, information, and computation in cells at the ICTS Winter school on quantiative biology (Dec.2015): Part 1,Part 2, Part 3

  11. Adventures at the interface of physics and Biology, KITP (Jan 2015): video

  12. Dictyostelium populations exploit noise to control collective behavior, BIRS Workshop on Stochasticity in Biochemical Reaction Networks, (Sept 2013): video


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


Our work is supported primarily by the NIH and previously the Simons Foundation. We have also received support from the Scialog:Molecules come to Life Program (run by the Research Corporation and Moore Foundation) and a Sloan Fellowship in Physics.

(Some) Popular Press:

Geonome Web
MIT Technology Review
Quanta Magazine (2014), reprinted in Wired
Quanta Magazine (2018), reprinted in Wired
Physics (2020)


Spring 2023: PY580:Machine Learning for Physics

Fall 2022: PY541:Statistical Physics

Spring 2022: PY580:Machine Learning for Physics

Fall 2021: PY541:Statistical Physics

Spring 2021: PY571:Biophysics

Fall 2020: PY895:Machine Learning for Physicists

Spring 2016:  PY410: Statistical and Thermal Physics

Fall 2015: BE700-PY895: Methods and Logic in Quantitative Biology 

Spring 2013: PY 106: Elementary Physics 

Fall 2012:  PY501: Mathematical methods for Physicists

Spring 2013: PY 106: Elementary Physics