Ph.D. Students

For students seeking PhD admission to my group: 

My PhD students do serious math courses in real analysis, measure theoretic probability, nonlinear systems and statistical learning theory in the first year of the PhD program. The PhD student can enrol either in Electrical & Computer Engineering, or the Center for Applied Math or Mechanical & Aerospace Engineering. My current areas of interest include:

  • Behavioral Economics, Statistical Signal Processing & Machine Learning- The human sensor interface: How does human decision making interface with signal processing algorithms? How to optimize sensing with human behavioral constraints? Stochastic Optimization, Partially Observed Markov Decision Processes (POMDPs), RL and Computational Game Theory
  • Social Network Analytics and Sensing – Network Science with Reinforcement Learning: How to use social networks as a real time adaptive sensor? How to  model & control the dynamics of information flow in social networks?
  • Adversarial Sensing and Inverse Reinforcement Learning: How should cognitive radars autonomously reconfigure their measurement modes based on their Bayesian estimates? How to calibrate your adversary’s sensors capabilities and intent? How to detect cognition? We use micro-economics and inverse re-inforcement learning

Current PhD Students. Check out our new lab website 

  • Shashwat Jain (did undergraduate/masters at IIT Kharagpur)
  • Luke Snow (did undergraduate at Clemson Univ, NSF Fellowship)
  • Adit Jain (did undergraduate at IIT Gawahati)
  • Yiming Zhang (did MEng at Cornell)

Alumni.

I am fortunate to have worked with amazing PhD students who have gone on to outstanding careers in academia and industry. You can download many of the PhD theses by clicking on the links below.

Andrew Logothetis (1998) EM Algorithms for State and Parameter Estimation Chief Engineer, Airspan, U.K.
Jonathan Manton (1998) Optimal Estimation and Identification of Linear Systems — Stochastic and Algebraic Approaches Future Generation Professor, University of Melbourne
Kenneth Tan (1997) Nonlinear Signal Processing Techniques based on the EM algorithm  
Jamie Evans (1998) Studies in Nonlinear Filtering Theory – Random Parameter Linear Systems, Target Tracking and Communication Constrained Estimation Professor and Pro-Vice-Chancellor, University of Melbourne
Leigh Johnston (2000) Iterative Algorithms for Estimation of Nonlinear Stochastic Dynamical Systems Professor, Biomedical Engineering, University of Melbourne.
S. Singh (2003) Optimization Issues in DS/CDMA Wirless Networks Associate Professor, Cambridge Univ
Sam McLaughlin (2006) Data Incest in Decentralized Estimation Systems ADI Thales Limited, France
Arsalan Farrokh (2007) Stochastic Resource Allocation in Wireless Networks Quant Research,  RBC Global Asset Management
Minh Ngo (2007) Cross Layer Adaptive Transmission Scheduling in Wireless Networks Quant Research,  RBC Global Asset Management
Michael Maskery (2007) Game Theoretic Methods for Networked Sensors and Dynamic Spectrum Access Patent Engineer, MBM Intellectual Property Law
Laxminarayana Pillutla (2008) Resource Management in Wireless Networks Apple , USA
Hassan Mansour (2009) Modeling of Scalable Video Content for Multi-user Wireless Transmission Mitsubishi Electric Research Labs
Farhad Ghassemi (2009) Sensor Management with Applications in Localization and Tracking Microsoft, USA
Alex Wang (2009) Meta-level Tracking with Stochastic Grammar Amazon
Jane Huang (2011) Application of Game Theory in Wireless Communication Networks Meta
Kevin Topley (2012) Average Consensus in Two-time Scale Markovian Systems  
Maryam Abolfath-Beygi (2013) Biosensor Arrays for Molecular Source Identification in Mass-Transport Systems Senior Data Scientist, Nike, Portland.
Omid Namvar (2015) Stochastic Approximation Methods for Decision Making in Non-stationary Uncertain Environments Quant Finance,  CPP Investment Board, Toronto
Mustafa Fanswala (2015) Meta-level Pattern Analysis for Target Tracking Principal Software Engineer, Autonomous Vehicles, NVIDIA
William Hoiles (2015) Biosensing and Electrophysiological Response Principal AI Scientist, Katerra, Toronto
Maziyar Hamdi (2015) Statistical Signal Processing on Dynamic Graphs with Applications in Social Networks Quant Finance, CPPP Investmens, Toronto
Mohammad Ghasemi (2016) Planning and Operation of Active Smart Grids  Senior Scientist, Amazon
Anup Aprem (2017) Detection, Estimation and Control in Online Social Media Assistant Professor, National Institute of Technology, Calicut
Tanzil Shahrear (2018) Mobile Edge Cloud: Computation and Caching Technical Leader, Machine learning or 6G, Ericsson, Sweden
Sujay Bhatt (2019) @Cornell Controlled Social Sensing: A POMDP Approach AI Research lead, Morgan Stanley, New York.
Buddhika Nettasinghe (2022) @Cornell Statistical Modeling and Inference in Social Networks Assistant Professor, U Iowa, Tippie College of Business
Rui Luo (2023) @Cornell

Social Network Segregation: Measurement, Estimation and Mitigation

Assistant Professor, City Univ of Hong Kong
Kunal Pattanayak (2023) @Cornell

Inverse Reinforcement Learning: A Micro-economics based approach 

Goldman Sachs, New York