Muah Kim

I am a Ph.D. student working with Prof. Dr.-Ing Rafael F. Schäfer in the Chair of Information Theory and Machine Learning at Technische Universität Dresden. Before starting my Ph.D. program, I worked at Korea Institute of Science and Technology in Europe (KIST-Europe) as a research assistant (related work). I received B.S. and M.S. degrees in electrical engineering from KAIST in 2017 and 2019 respectively. For my master's thesis, I studied coding for distributed computing with Prof. Jaekyun Moon. My research interests are how communications and machine learning enhance each other. The recent focus is to make use of deep learning for communications.

E-mail: muah.kim@tu-dresden.de / muah.kim@tu-berlin.de

Publications

M. Kim, T. Jahani-Nezhad, S. Li, R. F. Schaefer, G. Caire, "Short-Length Code Designs for Integrated Sensing and Communications using Deep Learning" accepted to IEEE International Conference on Communications (ICC), Denver, Colorado, Jun. 2024.
M. Kim, R. Fritschek, R. F. Schaefer, "Robust Generation of Channel Distributions with Diffusion Models" accepted to IEEE International Conference on Communications (ICC), Denver, Colorado, Jun. 2024.
M. Kim, R. Fritschek, R. F. Schaefer, "Learning End-to-End Channel Coding with Diffusion Models," accepted to ITG Workshop on Smart Antennas (WSA) and Conference on Systems, Communications, and Coding (SCC), Braunschweig, Germany, Mar. 2023. (Paper 📄)
M. Kim, O. Günlü, R. F. Schaefer, "Effects of Quantization in Federated Learning with Local Differential Privacy," accepted to IEEE Global Communications Conference (Globecom), Rio de Janeiro, Brazil, Dec. 2022. (Paper 📄)
O. Günlü, P. Trifonov, M. Kim, R. F. Schaefer, V. Sidorenko, "Privacy, Secrecy, and Storage with Nested Randomized Polar Subcode Constructions," accepted to IEEE Transactions on Communications, 2021. (Paper 📄)
M. Kim, O. Günlü, R. F. Schaefer, "Federated Learning with Local Differential Privacy: Trade-offs between Privacy, Utility, and Communications," accepted to IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Toronto, Canada, June 2021. (Paper 📄, Full Version 📄, Presentation Materials 🪄📰)
O. Günlü, P. Trifonov, M. Kim, R. F. Schaefer, V. R. Sidorenko, "Randomized Nested Polar Subcode Constructions for Privacy, Secrecy, and Storage," accepted to International Symposium on Information Theory and Applications (ISITA), Kapolei, Oahu, Hawai‘i, Oct. 2020. (Paper 📄, Full Version 📄)
M. Kim, J-y. Sohn and J. Moon, “Coded matrix multiplication on a group-based model,” accepted to IEEE International Symposium on Information Theory (ISIT), Paris, France, June 2019. (Paper 📄, Full Version 📄)

Tutorials

M. Kim, R. Fritschek, R. F. Schaefer, "Applications of Diffusion Models in Communications" presented at IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN), Stockholm, Sweden, May 2024. (Github💻 , Slides 🛝🗒️)

Teaching Experience

Dep. of Electrical Engineering and Computer Science, Technical University of Dresden, Germany

Seminar in Information Theory and Machine Learning (Oberseminar)
Intoduction to Machine Learning (Einführung in das maschinelle Lernen)

Dep. of Electrical Engineering and Computer Science, University of Siegen, Germany

DKT1 Digital Communication Technology I
DMFS Digital Mobile Network

Dep. of Electrical Engineering, KAIST, South Korea

- EE326 Introduction to Information Theory and Coding
- EE202 Signals and Systems

Dep. of Humanity and Social Science, KAIST, South Korea

- HSS193, HSS491, HSS587 Korean for International Students
- HSS143 Introduction to Contemporary China
- HSS250 Geopolitics and Development in East Asia
- HSS252 Issues in Urban and Regional Development
- HSS258 Geography of International Development

Honor

South Korean Governmental Scholarship for 2012~2013 and 2017~2018

National Science and Technology Excellence Scholarship of South Korea for 2014~2015

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