People

Principal Investigator

Hyeji Kim

Hyeji Kim is an Assistant Professor in the Department of Electrical and Computer Engineering at The University of Texas at Austin. She is an affiliate of the Machine Learning Laboratory (MLL) and a member of the Wireless Networking & Communications Group (WNCG). Before joining UT Austin, she held research positions as a postdoctoral scholar at the University of Illinois at Urbana-Champaign and as a researcher at Samsung AI Research Cambridge in the UK. She earned her PhD in Electrical Engineering from Stanford University in 2016.

Dr. Kim’s research lies at the intersection of information theory and machine learning. Her work leverages machine learning to tackle complex problems in information theory, focusing on developing advanced codes for communication and compression in challenging scenarios, such as high-dimensional channels and distributed data systems. Conversely, she applies principles of information theory to machine learning by constructing theoretical frameworks that uncover fundamental limits and provide deep insights into learning processes.

Graduate Students

Sravan Ankireddy

Sravan Ankireddy is a PhD candidate in the department of ECE at the University of Texas at Austin, supervised by Prof. Hyeji Kim. He received his Bachelors and Masters in Electrical Engineering from IIT Madras, India, in 2019 and worked as Wireless Systems Engineer at Qualcomm Research India. His research interests include development of new channel codes using deep learning and robust representation learning for high dimensional data. He is also interested in efficient fine tuning of foundation models for various downstream applications, including wireless communications.

Alliot Nagle

Alliot Nagle is a PhD student in the ECE department at the University of Texas at Austin. He earned his Bachelor’s and Master’s degrees in ECE from the University of Wisconsin–Madison in 2019 and 2022, respectively. His research lies at the intersection of information theory and machine learning, with a focus on applications to large language models. Specifically, he is interested in representation learning and developing methods for efficient training and inference. Outside of academia, Alliot enjoys weightlifting and playing the drums.

Taekyun Lee

Taekyun Lee is a PhD candidate at the University of Texas at Austin in the Department of Electrical Engineering. He is jointly supervised by Prof. Jeffrey Andrews and Prof. Hyeji Kim. Taekyun received his B. S. in Electrical Engineering from Seoul National University, Korea in 2022. His research interests lie mainly in the intersection between wireless networks and machine learning, especially deep generative models.

Heasung Kim

Heasung Kim is a Ph.D. candidate in the Department of Electrical and Computer Engineering at the University of Texas at Austin, under the supervision of Prof. Hyeji Kim and Prof. Gustavo de Veciana. He earned his B.S. degree in Computer and Communication Engineering from Korea University, South Korea, in 2017, and his M.S. degree in Electrical and Computer Engineering from Seoul National University (SNU) in 2019. Before pursuing his doctoral studies, he worked as a Machine Learning Engineer at Samsung Electronics. His research interests encompass the estimation of information-theoretic quantities, generative models, lossy compression, federated learning, and their applications in wireless communications and networks.

Karl Chahine

Karl Chahine is a PhD candidate in the Department of Electrical and Computer Engineering at the University of Texas at Austin, where he is supervised by Prof. Hyeji Kim. He received his bachelor’s degree in Computer and Communications Engineering from the American University of Beirut in 2020. His research interests include developing new channel codes using deep learning and image watermarking for diffusion models.

Sijie Li

Sijie Li is a PhD student in the ECE department at the University of Texas at Austin. He earned his Bachelor of Science degree in Mathematics and Information Engineering from the Chinese University of Hong Kong with the First Honor in 2022. His research interest lies in the fundamental limits of communication and compression. Currently, he is interested in solving the rate-distortion functions for the networked control system. He is also interested in the Gaussian channel with feedback problems.