The Faculty



2004 B.S., (Mathematics), California Institute of Technology

2009, PhD, (Physics) Princeton University

2009-2012, Visiting Researcher, Rockefeller University

2009-2012, Member, Institute for Advanced Study

2012-2015, Postdoc, Harvard University

2015-present Assistant Professor, University of Chicago

Research Interests

Recent advances in computational intelligence have relied on emergent collective behavior of simulated dynamical and statistical systems. Can such smart collective behaviors in `software’ (error correction, pattern recognition, associative memory) be implemented directly in ‘hardware’ (biochemical reactions, self-assembly, robotics)?

Bringing such emergent behavior back home to real physical and chemical systems can shed light on such learning and adaptive behaviors, reveal completely novel behaviors and lead to new forms of designer matter.

Current work includes:
1. Olfaction, molecular recognition and discrimination and an information theory of `shape'. 
2.  Disordered marginal mechanics with 'association' and 'recognition' abilities of neural networks.  Connections to kinetic architectures, soft actuators and problems of control.
3. Non-equilibrium dynamics and error correction, driven chemical reaction networks, relationship to search and exploration strategies.

Selected publications

Learning to control active matter
M. Falk, V. Alizadehyazdi, H. Jaeger, A. Murugan

Roadmap on biology in time varying environments
A. Murugan et al
Physical Biology 2021

Proofreading through spatial gradients
Vahe Galstyan, Kabir Husain, Fangzhou Xiao, Arvind Murugan+, Rob Phillips+
eLife 2020; 9:e60415

Physical constraints on epistasis
K. Husain, A. Murugan
Molecular Biology and Evolution (MBE) (2020) ,  arxiv

Continual learning of multiple memories in mechanical networks 
M. Stern, M. Pinson, A. Murugan
Physical Review X (Aug 2020)   (arxiv version)

Supervised learning through physical changes in a mechanical system
M. Stern, C. Arinze, L. Perez, S. Palmer, A. Murugan
PNAS (in press, 2020) 

Tuning environmental timescales to evolve and maintain generalists
V. Sachdeva*, K. Husain*, J. Sheng, S. Wang+, A. Murugan+
PNAS (April 2020) 

Non-equilibrium statistical mechanics of continuous attractors
W. Zhong, Z. Lu, D.J.Schwab+, A. Murugan+
Neural Computation (2020) 

Kalman-like Self-Tuned Sensitivity in Biophysical Sensing 
K Husain, W Pittayakanchit, G Pattanayak, M J Rust, A. Murugan
Cell Systems 2019, 459–465.e6

Temporal pattern recognition through analog molecular computation
 J O'Brien, A. Murugan
ACS Synthetic Biology (March 2019)
Popular summary by MIT Tech Review

Bioinspired nonequilibrium search for novel materials
A. Murugan, H. Jaeger 
MRS Bulletin 44(2):96-105      

Information content of downwelling skylight for non-imaging visual systems
 with: R. Thiermann, A. Sweeney
bioRxiv (Sep 2018) 

Shaping the topology of folding pathways in mechanical systems
with: M. Stern, V. Jayaram,
Nature Communications 9:4303 (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)