• Statistical Signal Processing
  Compressive Sensing, Detection Theory, Estimation Theory, Sensor Fusion

• Statistical Mechanics and Statistical Learning Theory
  Replica Method, Information-theoretic Interpretation of Physical Models, Large Deviations Theory, Mean-field Theory, Random Matrix Theory

• Theory of Machine Learning and Artificial Intelligence
  Bayesian Inference, Machine Learning, Regression, Approximate Message Passing, Federated Learning

• Computation and Communications
  Computation Coding, Distributed Coded Computing

• Information Theory
  Network Information Theory, Information Theoretic Secrecy, Secret Key Agreement

• Wireless Communications
  MIMO Precoding, Signal Processing for Communications

• [Feb 2022] I am joining the Wireless Computing Lab (WCL) in the Department of Electrical and Computer Engineering at the University of Toronto

• [Nov 2022] The book "Compressed Sensing in Information Processing" has been published. This book has been prepared throughout the last phase of the DFG-funded special session Compressed Sensing in Information Processing (CoSIP). Checkout our contribution in Chapter 5. In this chapter, we have given a comprehensive introduction to the replica method and its application to asymptotic analysis of Bayesian-type algorithms.

• [Jul 2022] I am giving an invited talk at the Random Matrices and Random Landscapes (RMRL 2022) conference in honor of Yan Fyodorov's 60th birthday. The talk is entitled "Bayesian Inference with Nonlinear Generative Models". The slides of my presentation can be found here.

The lecture materials of my courses at FAU can be accessed through StudOn. You can also download the lecture-notes here. The lecture-notes have been updated last time on Winter 2022-23. The version on GitHub is the final version, and hence could contain some changes compared to the older versions on the StudOn pages of previous semesters.