Hello! I am a Ph.D. student in a Research Chair at AIMS Rwanda, studying Information Theory and Deep Learning Theory. I am working under the supervision of Jan Hązła. The chair is funded by the Alexander von Humboldt Foundation.
I have the privilege to be supported by the DAAD project "Probability, Combinatorics and Applied Stochastic Analysis" in cooperation with Justus Liebig University Giessen.
In information theory, my research investigates when good performance of a code on one channel guarantees reliable decoding on another. In particular, I have be interested in leveraging properties of codes over the erasure channel (BEC) to obtain decoding properties over symmetric channel (BSC).
In parallel, I study learning theory, aiming to understand which problems are provably hard for stochastic gradient descent under specific neural network architectures.
Publications:
Donald Kougang-Yombi, Jan Hązła. Weight distribution bounds to relate minimum distance, list decoding, and symmetric channel performance. preprint 2026 [arxiv].
Emmanuel Abbe, Elisabetta Cornacchia, Jan Hązła, Donald Kougang-Yombi. Learning High-Degree Parities: The Crucial Role of the Initialization. ICLR 2025 [arxiv] [short video] [poster].
Donald Kougang-Yombi, Jan Hązła. A Quantitative Version of More Capable Channel Comparison. ISIT 2024 [arxiv] [IEEE Xplore]