Vijay Balasubramanian

Vijay Balasubramanian
Standing Faculty

Cathy and Marc Lasry Professor

Research Areas: High Energy Physics, Biophysics

(215) 573-0982

2N3A, David Rittenhouse Laboratory

I am interested in how natural systems manipulate and process information, producing new forms of self-organization.

As a theoretical physicist, I pursue questions about the fundamental nature of space and time.  I have worked on the the apparent loss of quantum information in the presence of black holes and the origin of entropy and thermodynamics in gravitating systems.  I have discussed how the familiar smooth structure of space-time can emerge as a long-distance effective description of more complex underlying physical constructs.  I have shown how some dimensions of space can be regarded as emergent, arising from the quantum entanglement and information structure of an underlying lower-dimensional theory.

As a biophysicist I pursue these questions primarily in neuroscience.  I think about the brain as a statistical computational device and seek to uncover the principles that underlie the organization of neural circuits across scales from cells to the whole brain.   I have worked on systems in the brain that support many different functions: vision, audition, olfaction, spatial cognition, motor control and decision making.   Applying lessons about adaptive molecular sensing from the olfactory system, I have also written about the functional organization of the adaptive immune system in vertebrates and bacteria (CRISPR). Visit our Lab Website for more details.
Finally, I have written on problems in statistical inference and machine learning, and in particular on “Occam’s Razor”, i.e., the tradeoff between simplicity and accuracy in quantitative models.  I am interested in this question because all scientific theories involve fitting models to data, and there is a fundamental tradeoff between the complexity of models and their ability to generalize correctly to new situations.  This tradeoff influences how scientists infer models of the world, how machines learn the structure in data, and how living things from the scale of single cells to entire organisms with brains adapt to their environment over timescales from milliseconds to evolutionary time.


Ph.D. in Theoretical Physics from Princeton University
M.S. in Computer Science from M.I.T.
B.S. degrees in Physics and Computer Science from M.I.T.

Research Interests

High Energy Physics, String Theory, Biophysics, Neuroscience

Selected Publications

String theory

Balasubramanian, V., Kraus, P., & Lawrence, A. (1999). Bulk versus boundary dynamics in anti–de Sitter spacetime. Physical Review D, 59(4), 046003.
Balasubramanian, V., & Kraus, P. (1999). A stress tensor for anti-de Sitter gravity. Communications in Mathematical Physics, 208(2), 413-428.
Balasubramanian, V., De Boer, J., & Minic, D. (2002). Mass, entropy, and holography in asymptotically de Sitter spaces. Physical Review D, 65(12), 123508.
Balasubramanian, V., Berglund, P., Conlon, J. P., & Quevedo, F. (2005). Systematics of moduli stabilisation in Calabi-Yau flux compactifications. Journal of High Energy Physics, 2005(03), 007.
Balasubramanian, V., Marolf, D., & Rozali, M. (2006). Information recovery from black holes. International Journal of Modern Physics D, 15(12), 2285-2292.
Balasubramanian, V., Bernamonti, A., de Boer, J., Copland, N., Craps, B., Keski-Vakkuri, E., ... & Staessens, W. (2011). Holographic thermalization. Physical Review D, 84(2), 026010.
Balasubramanian, V., Chowdhury, B. D., Czech, B., de Boer, J., & Heller, M. P. (2014). Bulk curves from boundary data in holography. Physical Review D, 89(8), 086004.
Balasubramanian, V., Chowdhury, B. D., Czech, B., & de Boer, J. (2015). Entwinement and the emergence of spacetime. Journal of High Energy Physics, 2015(1), 48.
Balasubramanian, V., Fliss, J. R., Leigh, R. G., & Parrikar, O. (2017). Multi-boundary entanglement in Chern-Simons theory and link invariants. Journal of High Energy Physics, 2017(4), 61.
Balasubramanian, V., DeCross, M., Kar, A., & Parrikar, O. (2020). Quantum complexity of time evolution with chaotic Hamiltonians. Journal of High Energy Physics, 2020(1), 134.
Balasubramanian, V., Kar, A., Parrikar, O., Sárosi, G., & Ugajin, T. (2020). Geometric secret sharing in a model of Hawking radiation. arXiv preprint arXiv:2003.05448.


Balasubramanian V, Berry MJ, Kimber D (2001) Metabolically Efficient Information Processing.  Neural Computation, Vol. 13, No.4 299-816. PMID:11255570

Koch K, McLean J; Segev R, Freed MA, Berry MJ II, Balasubramanian V, Sterling P (2006) How much the eye tells the brain. Curr Biol 16:1428-1434. PMCID:PMC1564115

Ratliff CP, Borghuis BG, Kao YH, Sterling P and Balasubramanian V (2010).  Retina is structured to process an excess of darkness in natural scenes. PNAS 2010 107 (40) 17368-17373. PMCID: PMC2951394.

Perge J,  Niven JE,  Mugnaini E,  Balasubramanian V, and Sterling P (2012). Why do axons differ in caliber? J. Neuroscience 32(2):626-638. PMCID: PMC3571697.

Wei, X-X, Prentice J, and Balasubramanian V (2015). A principle of economy predicts the functional architecture of grid cells. eLife 4 (2015): e08362.  PMCID: PMC4616244.

Keinath, A. T., Epstein, R. A., & Balasubramanian, V. (2018). Environmental deformations dynamically shift the grid cell spatial metric. Elife, 7, e38169.  PMCID: PMC6203432

Mayer, A., Balasubramanian, V., Mora, T., & Walczak, A. M. (2015). How a well-adapted immune system is organized. Proceedings of the National Academy of Sciences, 112(19), 5950-5955.
Glaze, C. M., Filipowicz, A. L., Kable, J. W., Balasubramanian, V., & Gold, J. I. (2018). A bias–variance trade-off governs individual differences in on-line learning in an unpredictable environment. Nature Human Behaviour, 2(3), 213-224.
Singh, V., Murphy, N. R., Balasubramanian, V., & Mainland, J. D. (2019). Competitive binding predicts nonlinear responses of olfactory receptors to complex mixtures. Proceedings of the National Academy of Sciences, 116(19), 9598-9603.
Bradde, S., Nourmohammad, A., Goyal, S., & Balasubramanian, V. (2020). The size of the immune repertoire of bacteria. Proceedings of the National Academy of Sciences, 117(10), 5144-5151.
CV (file)