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Current Members

I am very fortunate to work with the following great group of researchers.

Postdocs

Dr. Jy-yong Sohn, co-hosted with Prof. Dimitris Papailiopoulos

Jy-yong is interested in the intersection of machine learning, information theory, and distributed systems. He received his B.S., M.S. and Ph.D. degrees in electrical engineering from KAIST, in 2014, 2016 and 2020, respectively. He is a recipient of the IEEE ICC Best Paper Award, Qualcomm Innovation Awards, KAIST Global Leader Fellowship and KAIST EE Best Research Achievement Award.

PhD students

Changhun Jo (Math)

Changhun is interested in theoretical understanding of machine learning. He obtained his B.S. in Mathematics and B.A. in Economics from Seoul National University in 2016. His awards include the KFAS (Korea Foundation for Advanced Studies) Fellowship and Gold medals at National Mathematics Competition for Undergraduate Students in Korea in 2011 and 2012.

Tuan Dinh (CS)

Tuan’s research interests span over various topics in machine learning, especially representation learning, deep generative models and applied research in biomedical science. He received his B.E. in Computer Sciences from University of Technology, Vietnam National University in 2015.

Nayoung Lee (ECE), co-advised with Prof. Dimitris Papailiopoulos

Nayoung’s research interests include distributed machine learning and the underlying theories. She received her B.S. and M.S. degrees in Electrical and Computer Engineering from Seoul National University, in 2018 and 2020. She is a recipient of the Korean Government Scholarship Program for Study Overseas.

Liu Yang (CS), co-advised with Prof. Rob Nowak and Prof. Dimitris Papailiopoulos

Liu is interested in the theoretical understanding of machine learning. She received her B.E. in Computer Science from Xi’an Jiaotong University in 2020.

Yuchen Zeng (CS)

Yuchen is interested in machine learning, including both theory and algorithms. She completed her M.S at the Department of Statistics, University of Wisconsin-Madison in 2020. Prior to UW-Madison, she received her B.S. in Statistics from Nankai University in 2019.

Ziqian Lin (CS)

Ziqian is interested in trustworthy and scalable ML systems. He received his B.S. in Electronic Engineering from Tsinghua University in 2019.

Joseph Shenouda (ECE), co-advised with Prof. Rob Nowak

Joseph is interested in both developing and theoretically analyzing signal processing and machine learning algorithms, using tools from applied math, optimization and statistics. He is currently interested in machine learning algorithms for graph structured data. He received his B.S. in Electrical and Computer Engineering at Rutgers University-New Brunswick in 2021 and is a recipient of the ECE 2021 Wisconsin Distinguished Graduate Fellowship.

MS students

Ruisu Zhang (ECE)

Ruisu is interested in various topics ranging from theories to applications in machine learning. She received B.S. in Computer Science and Psychology at UW-Madison in 2021. Prior to 2018, she studied in Electronic Science and Engineering at Nanjing University.

Andrew Geng (ECE), co-advised with Prof. Sharon Yixuan Li

Andrew is interested in robust and trustworthy machine learning. He received his B.S. in Computer Science and Mathematics from the UW-Madison in 2020.

Undergraduate students

Michael Gira (CS/Entrepreneurship)

Michael is interested in various topics in machine learning and their application to solve tangible problems in people’s lives. He is a recipient of the 2022–2023 Wisconsin Hilldale Undergraduate/Faculty Research Fellowship.

Bryce Yicong Chen (ECE)

Bryce is interested in developing and improving different machine learning models and algorithms, including theoretical development and practical application.

Alumni

  • Liang Shang (MS, 1/2021 – 11/2021) => PhD student at UW Madison
  • Dr. Daewon Seo (Postdoc, 1/2020 – 7/2021) => Assistant Professor at DGIST

Furry collaborators

Bokdol Lee (Philosophy, Math, and Kinesiology)

Bokdol is a Maltese from South Korea. With his three PhDs, he takes an interdisciplinary approach to search for the perfect doggie life. He muses about the purpose of life, calculates the golden ratio of food/exercise/sleep, and analyzes the biomechanics of running and jumping. He gets his most creative ideas while taking naps.