Zeying Gong's Personal Homepage

Introduction

Zeying Gong is currently pursuing his MPhil in Artificial Intelligence at the Hong Kong University of Science and Technology (Guangzhou) under the guidance of Prof. Junwei Liang. His research primarily revolves around time-series forecasting, specifically developing algorithms for forecasting electricity demand and weather precipitation.
Before embarking on his MPhil journey, Zeying spent over a year as a 5G network engineer at Huawei. There, he played a pivotal role in the Jiangxi provincial high-speed rail 4G & 5G base station project and was actively involved in the technical development of MetaAAU and the ultra-long coverage features of 700M antennas. Zeying earned his Bachelor's degree in Electronic Information Science and Technology from Sun Yat-sen University, supervised by Prof. Bin Rao.

His current research interests include Time Series Analysis and AI4Science.

Latest News

2023.10: Heading to HKUST for a Cross-Campus Study, honored to have Prof. Prof. Dit Yan Yeung as my host supervisor.
2023.09: I submitted two academic papers to the top AI conference ICLR'24.
2023.07: Our team won the Excellence Award in 0-24 hours Precipitation Nowcasting Challenge

Awards and Recognitions

[2023] - Won the Excellence Award in 0-24 hours Provincial Precipitation Nowcasting Challenge.
[2023] - Won the Campus Squash Championship at HKUST(GZ).
[2022] - Won the "Outstanding Individual Award of Jiangxi Office" at Huawei in 2022 H1.
[2021] - Won the "Star of Tomorrow" at Huawei.
[2020] - Undergraduate thesis published at CIE International Conference on Radar.
[2019] - Won the 3rd Prize in the Provincial Electronic Design Competition.

Publications

[1] Z Gong, B Rao. "Cluster Unmanned Aerial Vehicle Electromagnetic Calculations and Applications" 2021 CIE International Conference on Radar, 1196-1199 [ bib | DOI | Patent ]

[2] Z Gong, Y Tang, J Liang. "PatchMixer: A Patch-Mixing Architecture for Long-Term Time Series Forecasting". arXiv preprint, 2023, URL: arxiv.org/abs/2310.00655 [ bib | DOI | Code ]

[3] Y Tang, J Zhou, X Pan, Z Gong, J Liang. "PostRainBench: A comprehensive benchmark and a new model for precipitation forecasting". arXiv preprint, 2023, URL: arxiv.org/abs/2310.02676 [ bib | DOI | Code ]