Group Members

Krishna Narayanan

Co-director, Professor, Electrical and Computer Engineering

• AI-native wireless networks

• PHY/MAC, information theory

Srinivas Shakkottai

Co-director, Professor, Electrical and Computer Engineering

• AI-native wireless systems

• Reinforcement learning, Robotics

Jean-Francois Chamberland

Professor, Electrical and Computer Engineering

• Statistical signal processing

• Machine learning, AI-native wireless networks

Eman Hammad

Assistant Professor, Engineering Technology & Industrial Distribution,

• Cyber-Physical Systems’ Security, Trust, and Resilience

• Autonomous, Collaborative and Human-in-the-Loop Complex Systems

I-Hong Hou

Professor, Electrical and Computer Engineering

• Cyber-Physical Systems’ Security, Trust, and Resilience

• MAC, AI-native wireless networks

Dileep Kalathil

Associate Professor, Electrical and Computer Engineering

• Reinforcement learning

• Artificial intelligence

Kamran Entesari

Professor, Electrical and Computer Engineering

• Electromagnetics, antennas

• Circuits

P.R. Kumar

Professor, Electrical and Computer Engineering, Member of the National Academy of Engineering

• Stochastic systems and control
• AI-native wireless networks
• Machine learning theory

Srikanth Saripalli

Professor, Mechanical Engineering

• Robotics

• Autonomous systems

Nitesh Saxena

Professor, Computer Science and Engineering

• Security

• Software systems

Chao Tian

Associate Professor, Electrical and Computer Engineering

• Machine learning theory

• Information theory, source coding

Ruowan Ji

Ph.D. Student

• Retreival augmentation generation
• Federated learning
• Distributed Coded Matrix Multiplication

Zaiyan Xu

Ph.D. Student

• Reinforcement learning
• Distributionally robust optimization
• Reinforcement learning from human feedback

Vishnu Teja Kunde

Ph.D. Student

• LLMS for wireless communications
• Diffusion models

Fatemeh Doudi

Ph.D. Student

• Diffusion models
• Transformers and In-context Learning

Mahdi Farahbakhsh

Ph.D. Student

• Diffusion models
• Transformers
• Inverse problems

Sarat Chandra Bobbili

Ph.D. Student

• Reinforcement Learning
• Large language models
• Online learning and Multi-Armed Bandits
• Stochastic Analysis

Jeremy Carleton

Ph.D. Student

• Inference-time alignment of large language models
• Online learning

Kaushik Valmeekam

Ph.D. Student

• AI-native wireless communications
• LLMs and Transformers
• ML based Joint Source Channel Coding

Bhavya Nukapotula

Ph.D. Student

• ML for wireless communications
• Adaptive Gaussian Splatting Methods

Yu-Shin Huang

Ph.D. Student

• LLM-based Steganography
• LLM Watermarking

Debajoy Mukherjee

Ph.D. Student

• Reinforcement learning through Human Feedback
• LLM reasoning

Ujwal Dinesha

Ph.D. Student

• End-to-End Learning for Robotics
• LLM Alignment
• Deep Learning based Video Compression
• Bandit Algorithms

Sushil Vemuri

M.S. Student

• Large Language Models
• Reinforcement Learning

Jamison Ebert, Employment: Qualcomm, Inc.

Michail Gkagkos, Employment: Qualcomm, Inc.