Luke Snow
I'm a 4th-year PhD Candidate in the Electrical & Computer Engineering Department at Cornell University, grateful to be advised by Prof. Vikram Krishnamurthy. In 2021 I graduated from Clemson University with a B.S. in electrical engineering and a minor in mathematics. My research interests are broadly in statistical signal processing, stochastic analysis and its application to machine learning, and algorithmic game theory. See my research page for more details.
I am a member of the Cornell Statistical Signal Processing Lab, and am affiliated with the Foundations of Informations, Networks and Decision Systems (FIND) research collective.
I have professional experience in radar and intelligent systems analysis through internships with the U.S. Army Research Laboratory (2022), MIT Lincoln Laboratory (2021), and Leidos Dynetics (2019).
Here's my Google Scholar, and Linkedin.
Email: las474[at]cornell[dot]edu
Highlighted Publications
Please refer to publications for the full list.
Finite-Sample Bounds for Adaptive Inverse Reinforcement Learning using Passive Langevin Dynamics
IEEE Transactions on Information Theory, 2023
[pdf]
Efficient Neural SDE Training using Wiener-Space Cubature
arXiv:2502.12395, 2025
[pdf]
Adaptive Mechanism Design using Multi-Agent Revealed Preferences
63rd IEEE Conference on Decision and Control, 2024
[pdf]
Quickest Detection for Human-Sensor Systems using Quantum Decision Theory
IEEE Transactions on Signal Processing, 2024
[pdf]
Statistical Detection of Coordination in a Cognitive Radar Network through Inverse Multi-Objective Optimization
26th International Conference on Information Fusion, 2023
[pdf]
Awards
[2024] IEEE Signal Processing Society Scholar
[2021] NSF Graduate Research Fellow
[2021] Clemson University 'W.M. Riggs Award' for the most outstanding senior in electrical engineering