contact: las474@cornell.edu
I am a third-year PhD student in the Electrical & Computer Engineering Department at Cornell University. I’m a member of the Cornell Statistical Signal Processing Laboratory and am grateful to be advised by Professor Vikram Krishnamurthy. In May 2021 I graduated from Clemson University with a B.S. in electrical engineering and a minor in mathematics.
My research interests broadly include statistical signal processing, stochastic optimization, inverse reinforcement learning, game theory and network science.
Specifically, my research interests are in:
Social Sensing: We address the interface between human decision making and signal processing, sensing and control strategies. I’ve studied several human-sensor interface frameworks utilizing a ‘quantum decision’ model, which exploits the structure of quantum probability to generalize traditional decision-making models.
- Relevant Publications:
- Quickest Change Detection using Time Inconsistent Anticipatory and Quantum Decision Modeling, V. Krishnamurthy, L. Snow, 58th Allerton Conference on Communication, Control, and Computing, 2022
- Lyapunov based Stochastic Stability of Human-Machine Interaction: A Quantum Decision System Approach, L Snow, S Jain, V Krishnamurthy, 61st IEEE Conference on Decision and Control, 2022
- Quickest Detection for Human-Sensor Systems using Quantum Decision Theory, L. Snow, V. Krishnamurthy, B. M. Sadler, arXiv preprint arXiv:2208.08583 (Accepted to IEEE Transactions on Signal Processing), 2022
- Lyapunov based Stochastic Stability of a Quantum Decision System for Human-Machine Interaction, L Snow, S Jain, V Krishnamurthy, arXiv preprint arXiv:2205.12378 (Submitted to Automatica), 2022
Multi-agent Intelligent Systems: We are interested in detecting agent coordination (or “collective rationality”) from incomplete or noisy group observations. This can be accomplished using tools from microeconomic Revealed Preference Theory, and can find application in e.g., detecting and predicting adversarial group strategies or detecting multi-objective optimizing cognitive radar.
- Relevant Publications:
- Statistical Detection of Coordination in a Cognitive Radar Network through Inverse Multi-objective Optimization, L. Snow, V. Krishnamurthy, 26th IEEE International Conference on Information Fusion, 2023
- Identifying Coordination in a Cognitive Radar Network – A Multi-Objective Inverse Reinforcement Learning Approach, L. Snow, V. Krishnamurthy, B. M. Sadler, IEEE International Conference on Acoustics, Speech, and Signal Processing, 2023
MCMC and Adaptive Inverse Learning: We are generally interested in algorithmic techniques for accomplishing adaptive inverse reinforcement learning, i.e., given sequential argument evaluations from a forward learning agent, can we reconstruct the cost function being optimized (in real-time)? We have developed and analyzed a passive stochastic gradient Langevin dynamics algorithm, which acts as a Markov chain Monte-Carlo (MCMC) sampler to reconstruct this cost function.
- Relevant Publications:
- Finite-Sample Bounds for Adaptive Inverse Reinforcement Learning using Passive Langevin Dynamics, L. Snow, V. Krishnamurthy, arXiv preprint arXiv:2304.09123 (to appear in Proceedings of the 62nd IEEE Conference on Decision and Control), 2023
Cornell Coursework
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- MATH 6230: Differential Games and Optimal Control
- MATH 6160: Partial Differential Equations
- MATH 7740: Statistical Learning Theory
- ECE 5412: Bayesian Estimation and Stochastic Optimization
- MATH 7710: Limits of Discrete Random Structures
- MATH 6710: Probability Theory I
- ECE 5330: Quantum Physics and Engineering
- ORIE 6500: Applied Stochastic Processes
Professional Experience
- U.S. Army Research Laboratory, Summer Research Intern, May – August 2022
- Grateful to be mentored by Dr. Brian Sadler
- MIT Lincoln Laboratory, Summer Research Intern, May – August 2021
- Dynetics, Engineering Intern, May – August 2019
Awards
- 2021: NSF Graduate Research Fellowship recipient
- 2021: Clemson University ‘W.M. Riggs Award’ for the most outstanding senior in electrical engineering
Education
- Ph.D. Electrical Engineering, Cornell University (2021 – present)
- Thesis Committee: Vikram Krishnamurthy, Laurent Saloff-Coste, Lang Tong
- B.S. Electrical Engineering, Clemson University (2021)
- Minor, Mathematics
- Summa Cum Laude & Departmental Honors
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