Vikram Krishnamurthy email@example.com
Professor, Electrical & Computer Engineering, Cornell.
Vikram is also affiliated with Center for Applied Math and Mechanical & Aerospace Engineering at Cornell.
Vikram is a Fellow of IEEE, served as distinguished lecturer for the IEEE Signal Processing Society, Editor in Chief of IEEE Journal Selected Topics in Signal Processing. He was awarded an honorary doctorate from KTH, Sweden in 2013. From 2002-2016, Vikram was a Canada Research Chair professor at University British Columbia, Vancouver.
Vikram’s research interests are in statistical signal processing, stochastic control (POMDPs), stochastic optimization and inverse reinforcement learning with applications in social networks, human decision making and adaptive sensing.
- Click here for all my publications.
- Click here for preprints on arXiv
- Recent papers:
- Behavioral Economics Approach to Interpretable Deep Image Classification, 2021.
- Controllability of Network Opinion in Erdos-Renyi Graphs Using Sparse Control Inputs, SIAM Journal Control & Optimization 2021
- Quickest Change Detection of Time Inconsistent Anticipatory Agents. Human-Sensor and Cyber-Physical Systems, IEEE Transactions Signal Processing, 2021
- Inverse Reinforcement Learning for Identifying Cognitive Radar, IEEE Transactions Signal Processing, 2021.
- Controlled Information Fusion with Social Sensors, IEEE Trans Automatic Control, 2020.
- Rationally Inattentive Inverse Reinforcement Learning explains YouTube Commenting Behavior, Journal of Machine Learning Research, 2020
- Friendship paradox biases perceptions in directed networks, Nature Communications, 2020.
- Convex Dominance in Bayesian Localization, Filtering and Controlled Sensing POMDPs, IEEE Trans Information Theory, 2020.
- Fast Consistent Learning of HMMs by Incorporating Non-consecutive Correlations, ICML 2020.
- Inverse Filtering and Counter-adversarial Systems, IEEE Trans Signal Processing, 2020.
|Fundamental Areas||Application Areas|
|POMDPs & Controlled Sensing||Social Networks (fusion & control)|
|Stochastic Optimization, Game Theory||Cognitive Radar & Intent Inference|
|Stochastic Calculus, filtering (old stuff)||Biosensors, Artificial Membranes|
- Partially Observed Markov Decision Processes book, Cambridge, 2016
- Dynamics of Engineered Artificial Membranes & Biosensors, Cambridge, 2018.