Tze-Yang Tung
Tze-Yang Tung
Tze-Yang Tung is a PhD student at the Intelligent Systems and Networks Group at ÌìÃÀ´«Ã½ since September 2019. He previously received his BEng degree from the department of Electrical and Electronic Engineering also from ÌìÃÀ´«Ã½. Subsequently, he received his MSc degree from the University of Southern California in Electrical and Computer Engineering where he researched in molecular communications. His current research is in joint source-channel coding for wireless image and video transmission with emphasis on utilising deep learning techniques as well as context-aware effective communications in multi-agent reinforcement learning. He is interesting in the junction between machine learning and the communication schemes that enable machine learning algorithms to succeed. A tight integration between machine learning and communications is essential for future AI developments.
Below is a list of his publications.
Publications
Journals
→ T. Tung, and D. Gunduz, , IEEE Communications Letters, Vol. 22 - No. 12, 2018.
→ T. Tung, S. Kobus, J. Roig Pujol, and D. Gunduz, A joint learning and communication framework formulti-agent reinforcement learning over noisy channels, IEEE Journal on Selected Areas in Communications (JSAC), Special Issue on Machine Learning in Communications and Networks, 2021
→ M. Boloursaz Mashhadi, M. Jankowski, T.-Y. Tung, S. Kobus, and D. Gündüz, ‌‌,&²Ô²ú²õ±è;IEEE Wireless Communications Letters, 2021.
→ T.-Y. Tung, J. Roig Pujol, S. Kobus, and D. Gündüz, Effective communications: A joint learning and communication framework for multi-agent reinforcement learning over noisy channels‌‌‌‌,&²Ô²ú²õ±è;IEEE Journal on Selected Areas in Communications, Vol. 39, No. 8, Aug. 2021.
→ T.-Y. Tung and D. Gündüz, "DeepWiVe: Deep-learning-aided wireless video transmission‌",&²Ô²ú²õ±è;submitted, Nov. 2021.
Conferences
→ T. Tung, and U. Mitra, , International Symposium on Turbo Codes & Iterative Information Processing, Dec., 2018.
→ T. Tung, U. Mitra, , IEEE International Conference on Communications (ICC), May, 2019.
→ T.-Y. Tung, D.B. Kurka, M. Jankowski, and D. Gündüz, DeepJSCC-Q: Channel input constrained deep joint source-channel coding‌, IEEE International Conference on Communications, May 2022.
