Research interestsWe work on problems in quantitative biology, non-equilibrium dynamics, and theoretical computer science.
A frequent question is how collective dynamics in physical and biological systems can generalize past experiences, i.e., learn, and respond differently to future inputs. This ability is critical to understanding biology in changing environments and to engineer neuro-inspired functions in matter. Current work includes: 1. Decoding information in time-varying signals using non-equilibrium dynamics (in circadian clocks with the Rust lab, in gene regulation with the Tay lab, in neural networks) 2. Exploiting transients in learning and evolution by time-varying environments (in immunology with the Wang lab, in neural networks) 3. Learning behaviors from examples in soft materials (elastic materials, active systems). Openings: If you are interested in working on such themes as a postdoc, graduate student or undergrad, contact amurugan@uchicago.edu. Funding: Our work is primarily supported by the NSF and a Simons Foundation Investigator award. Lab members have been supported by the James S. McDonnell Foundation and NSF fellowships. |
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Some recent publications (List + summaries here) |
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Learned multi-stability in mechanical networks
with: M. Stern, M. Pinson arXiv (Feb 2019) Temporal pattern recognition through analog molecular computation with: J O'Brien ACS Synthetic Biology (March 2019) Popular summary by MIT Tech Review Bioinspired nonequilibrium search for novel materials with: H. Jaeger MRS Bulletin 44(2):96-105 pdf here Non-equilibrium statistical mechanics of continuous attractors with: W. Zhong, Z. Lu, D.J. Schwab arXiv (Sep 2018) Information content of downwelling skylight for non-imaging visual systems with: R. Thiermann, A. Sweeney bioRxiv (Sep 2018) Biophysical clocks face a trade-off between internal and external noise resistance with: W. Pittayakanchit*, Z. Lu*, J. Chew, M. Rust eLife 2018;7:e37624 High Protein Copy Number Is Required to Suppress Stochasticity in the Cyanobacterial Circadian Clock with: J. Chew, E. Leypunskiy, J. Lin, M. Rust Nature Communications 9:3004 (2018) Shaping dynamical pathways in mechanical systems with: M. Stern, V. Jayaram Nature Communications 9:4303 (2018) The difficulty of folding self-folding origami with: M. Stern, M. Pinson Physical Review X, arXiv link (2017) Self-folding origami at any energy scale with: M. Pinson*, M. Stern*, A Ferrero, T.Witten, E. Chen Nature Communications 8:15477 (2017) Associative pattern recognition through macro-molecular self-assembly with: W. Zhong, D.J. Schwab Journal of Statistical Physics, Volume 167, Issue 3–4, May 2017 Topologically protected modes in non-equilibrium stochastic systems with: S. Vaikuntanathan Nature Communications (Jan 2017) The Information Capacity of Specific Interactions with: M. Huntley, M. Brenner Proceedings of the National Academy of Sciences (May 2016) Receptor arrays optimized for natural odor statistics, with: D. Zwicker, M. Brenner Proceedings of the National Academy of Sciences (Apr 2016) Biological implications of dynamical phases in non-equilibrium reaction networks, with: S. Vaikuntanathan invited contribution, Journal of Statistical Physics (2016, 162 (5)) Undesired usage and the robust self-assembly of heterogeneous structures, with: J. Zou, and M. Brenner Nature Communications 6, 6203 (Jan 2015) Multifarious Assembly Mixtures: Systems Allowing Retrieval of Diverse Stored Structures, with: Z. Zeravcic, S. Leibler and M. Brenner Proceedings of the National Academy of Sciences 112(1) 54-59 (Dec 2014) |