News
22 August 2024
I serve as the invited reviewer for Information Processing & Management (IPM).
28 July 2024
I'm honored to receive the China Scholarship Council (CSC) Joint Doctoral Scholarship.
25 March 2024
One first-author paper is accepted by SIGIR, on medication recommendation. Thanks for all co-authors!
29 June 2024
I serve as the invited reviewer for IEEE Transactions on Knowledge and Data Engineering (TKDE).
01 October 2023
One first-author paper is accepted by TKDE on Recommendation Debias. Thanks for all co-authors!
16 September 2023
I serve as the invited reviewer for ACM International Conference on Information and Knowledge Management (CIKM).
18 November 2022
I serve as the invited reviewer for ACM Transactions on Information Systems (TOIS).
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Zihao Zhao
PhD Student
Department of Electronic Engineering and Information Science • GitHub • Google Scholar • CV • Blog
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I'm currently pursuing my PhD at University of Science and Technology of China (USTC) under the guidance of Prof. Xiangnan He and Prof. Fuli Feng. Prior to this, I obtained my Bachelor's degree in Electronic Information from USTC under the supervision of Prof. Xiangnan He. Now, my research interest lies in AI4Healthcare and Large Language Models.
Especially, I want to explore AI models such as LLMs with the ability to effectively analyze and interpret complex medical data, assist in diagnostics, and enhance patient communication.
I have two publications that appeared in the top conference SIGIR (ACM Special Interest Group on Information Retrieval) and journal TKDE (IEEE Transactions on Knowledge and Data Engineering).
Moreover, I have served as invited reviewer for ACM TOIS, ACM CIKM, ACM TKDE, IPM, etc.
Publications
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Leave no patient behind: Enhancing medication recommendation for rare disease patients
Zihao Zhao, Yi Jing, Fuli Feng, Jiancan Wu, Chongming Gao & Xiangnan He ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024, Full) pdf Codes Blog |
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Popularity Bias is not Always Evil: Disentangling Benign and Harmful Bias for Recommendation
Zihao Zhao*, Jiawei Chen, Sheng Zhou, Xiangnan He, Xuezhi Cao, Fuzheng Zhang & Wei Wu
IEEE Transactions on Knowledge and Data Engineering (TKDE 2023, Full) pdf Code |
Experiences
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Data Science Intern, Intuit Inc., Mountain View, U.S., June 2024 - August 2024 Advisor: Dr. Hilaf Hasson (Intuit), Dr. Jing Hu (Intuit), Dr. Shankar Sankararaman (Intuit) |
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Research Intern, Kuaishou Inc., Beijing, China, March 2020 - May 2023 Advisor: Prof. Xiangnan He (USTC), Prof. Wenqiang Lei (SCU), Dr. Peng Jiang (Kuaishou) |
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Summer Research Intern, University of Florida, Gainesville, U.S., July 2019 - September 2019 Advisor: Prof. Joel B. Harley (UF) |
Projects & Research
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Project: Explore Interest of Cold-Start Users by Conversational Recommendation Period : Mar. 2020 - Dec. 2020 Advisor: Prof. Xiangnan He (USTC), Prof. Wenqiang Lei (SCU), Prof. Qingyun Wu (PSU), Prof. Tat-Seng Chua (NUS) - Actively asking users' preferences through conversations helps to efficiently capture the interest of cold-start users. - Propose a holistic framework to seamlessly solve all conversation policy questions in an end-to-end manner. - Apply Thompson Sampling to conversational recommendation for keeping EE balance in cold-start scenario. |
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Project: Explore Trustworthy Evaluation for Conversational Recommendation Systems Period : Mar. 2021 - Dec. 2021 Advisor: Prof. Xiangnan He (USTC), Prof. Wenqiang Lei (SCU), Dr. Peng Jiang (Kuaishou Inc.) - Collect a fully-observed dataset for the first time from the social video-sharing mobile App, Kuaishou, with millions of user-item sequential interactions. - Study the effect of different exposure rates and various biases on the evaluation of conversational recommendation systems (CRSs). - Investigate the effect of matrix completion, i.e., estimating the missing values, on the evaluation of CRSs. |
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Project: Implement Reinfocement Learning in Real-World Short Video Recommendation Period : Mar. 2022 - Jul. 2022 Advisor: Prof. Xiangnan He (USTC), Dr. Yuan Zhang (Kuaishou Inc.) - Design an actor-critic based RL model for online recommendation of short videos on Kuaishou App. - Train the model in an offline RL manner by building and interacting with a user simulator. - Implement the RL model for re-ranking task in real-world recommendation application, achieving significant improvement on users' total watch time and diversity of recommended videos. |
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Project: Burst Filter Bubbles by Counterfactual Interactive Recommender System Period : Nov. 2021 - Jul. 2022 Advisor: Prof. Xiangnan He (USTC), Prof. Wenqiang Lei (SCU), Prof. Jiawei Chen (ZJU) - Analyze filter bubbles in interactive recommendation, focusing on the overexposure effect on user satisfaction. - Integrate causal inference into offline Reinforcement Learning to burst filter bubbles. |
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Project: Predict the Growth and Boundaries of Grains in Microstructure Period : Jul. 2019 - Sep. 2019 Advisor: Prof. Joel B. Harley (UF) - Analyze the problem in a reinforcement learning framework, defining corresponding state and action space for RL. - Process and decode the pictures of microstructure into low-dimension expression, while denoising for the vagueness of these pictures. |
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Project: Recommend Best Parameters Instantly for Base Stations Period : Sep. 2018- Jan. 2019 Advisor: Prof. Cong Shen (USTC, now in UVA) - Apply active learning and reinforcement learning to optimize the decision policy in changing environments. - Filter the data with the highest information entropy to train the DQN network, then adapt the model with real-time feedback signals. |
Education
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University of Sicence and Technology of China (USTC) PHD in Electronic and Information Engineering, School of Information Science and Technology Sep 2022 - Present, Hefei, China Advisor: Prof. Xiangnan He & Prof. Fuli Feng |
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University of Sicence and Technology of China (USTC) Master in Electronic and Information Engineering, School of Information Science and Technology Sep 2020 - Jul 2022, Hefei, China Advisor: Prof. Xiangnan He & Prof. Fuli Feng |
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University of Sicence and Technology of China (USTC) Bachelor in Electronic Information, School of Information Science and Technology Sep 2016 - Jul 2020, Hefei, China Advisor: Prof. Xiangnan He |
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Henan Tongxu county senior high school Sep 2013 - Jun 2016, Kaifeng, China |
Services & Awards & Patents
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PC Member for the 28th, 29th, and 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022, 2023, 2024),
the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2024 (ECML-PKDD 2024),
the 15th International Conference on Web Search and Data Mining (WSDM 2022), and the 1st Workshop on Recommendation with Generative Models on CIKM 2023. |
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Invited Reviewer for ACM Transactions on Information Systems (TOIS),
ACM Transactions on the Web (TWEB),
ACM Transactions on the Recommender Systems (TORS), the 38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024), and ACM International World Wide Web Conference (WWW 2022). |
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UT Austin Engineering Fellowship, 2023 & 2024
- Graduate School at the University of Science and Technology of China at Austin, U.S. |
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Illinois Distinguished Fellowship, 2023
- Graduate Colledge at the University of Illinois at Urbana-Champaign, U.S. (declined) |
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Outstanding Graduate Scholarship, 2023
- University of Science and Technology of China, China |
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National Scholarship, 2022
- Ministry of Education of China, China (for top 2% students) |
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First Class Academic Scholarship, 2020 & 2021 & 2022
- University of Science and Technology of China, China |
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Outstanding Student Scholarship, 2017 & 2018 & 2019
- University of Science and Technology of China, China |
Useful Links
| USTC Lab for Data Science |
| Prof. Fuli Feng |
| Prof. Xiangnan He |
Webpage template borrowed from Prof. Xiangnan He.