Zonghe Shao

Zonghe Shao

Mphil student at Huazhong University of Science and Technology (HUST)

About me

Hi, I am Zonghe Shao. I am currently a third-year MPhil student at Huazhong University of Science and Technology (HUST), supervised by Prof. Renzhi Lu, and I expect to graduate in June 2027. I received my B.Sc. in Artificial Intelligence from HUST in 2024. I am currently an intern at Taobao & Tmall Group, Alibaba. Before that, I interned at Kuaishou Technology and TikTok, ByteDance.

My research interests include Reinforcement Learning (RL), Large Language Models (LLMs), and their applications in Recommender Systems (RS). Within RL, I mainly focus on:

  • Enabling RL agents to autonomously learn rewards, similar to how humans do (published in Nature Communications and in Research)

  • Developing more accurate value function estimations to support decision-making (under review at TPAMI)

If you want to contact me, or if you are interested in collaborating with me, please drop me an e-mail using my Gmail: zongheshao17[AT]gmail.com.

News

  • [2026.10] UGR is available on arXiv !
  • [2026.10] I was awarded the National Scholarship !
  • [2026.02] One paper accepted by Research !
  • [2025.10] One paper accepted by Nature Communications !
  • [2024.07] One paper accepted by IEEE Transactions on Industrial Informatics !

Publications

Methodology overview of: UGR: Unified Generative Ranking for Heterogeneous E-commerce Recommendation

UGR: Unified Generative Ranking for Heterogeneous E-commerce Recommendation

Zonghe Shao, Huabin Chen, Sitong Lu, Fangmei Zhu, Yingcai Ma, Ge Fan, Jinguo Gao, Wei Shi, Yanfang Liu & Huiping Chu

arXiv preprint arXiv:2610.39426, 2026

Work done during an internship at Taobao & Tmall Group of Alibaba.

Methodology overview of: Uncertainty as Remedy: Mitigating Satisfaction Label Bias in Short Video Multi-Objective Ensemble Ranking

Uncertainty as Remedy: Mitigating Satisfaction Label Bias in Short Video Multi-Objective Ensemble Ranking

Zonghe Shao, Tiantian He, Xiaoxiao Xu, Jiaqi Yu, Minzhi Xie, Jinfang Gu, Yongqi Liu, Kaiqiao Zhan & Kun Gai

arXiv preprint arXiv:2607.17092, 2026

Work done during an internship at Kuaishou Technology.

Methodology overview of: Deep Reinforcement Learning for Real-World Humanoid Robot Locomotion Control with Automatic Reward Learning

Deep Reinforcement Learning for Real-World Humanoid Robot Locomotion Control with Automatic Reward Learning

Renzhi Lu, Jie Wang, Zonghe Shao, Ruijuan Chen, Lijun Zhu, Yuzhi Jiang, Yunyi Pang, Dongfang Liang, Yang Shi & Han Ding

Research, 9, 1123, 2026

Methodology overview of: Discovery of the reward function for embodied reinforcement learning agents

Discovery of the reward function for embodied reinforcement learning agents

Renzhi Lu, Zonghe Shao, Yuemin Ding, Ruijuan Chen, Dongrui Wu, Housheng Su, Tao Yang, Fumin Zhang, Jun Wang, Yang Shi, Zhong-Ping Jiang, Han Ding & Hai-Tao Zhang

Nature Communications, 16(1), 11064, 2025

Methodology overview of: A Novel Data-Driven LSTM-SAF Model for Power Systems Transient Stability Assessment

A Novel Data-Driven LSTM-SAF Model for Power Systems Transient Stability Assessment

Zonghe Shao, Qichao Wang, Yuzhe Cao, Defu Cai, Yang You & Renzhi Lu

IEEE Transactions on Industrial Informatics, 20(7), 9083-9097, 2024 (IF=11.3)

Educations

  • 2024 - 2027, Mphil, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology
  • 2020 - 2024, Bachelor, Artificial Intelligence, Huazhong University of Science and Technology

Internships

Service

  • Reviewer for conferences: ICLR, KDD, AAAI
  • Reviewer for journals: IEEE Transactions on Power Systems (TPS), IEEE Transactions on Industrial Informatics (TII), and IEEE Transactions on Consumer Electronics (TCE)