I am a first-year PhD student in the Department of Computer Science at the University of Hong Kong (HKU), supervised by Prof. Reynold Cheng. I also work closely with Prof. Sihem Amer-Yahia from the CNRS and Prof. Laks V.S. Lakshmanan from UBC. My research focuses on Graph Hypothesis Testing, and I have a strong interest in exploring various graph-related problems. I am open to research cooperation and welcome any collaboration invitations via email.
I graduated with a first-class honours degree in Mathematics and Decision Analytics from the University of Hong Kong. My graduation project was supervised by Dr. Adela Lau from the Department of Statistics and Actuarial Science. Additionally, I participated in the 2022 RIPS program organized by NUS IMS, where I conducted research with Grab.
🔥 News
- 2024.06: 🎉🎉 Our first graph hypothesis testing paper is accepted by VLDB 2024.
- 2024.03: 🎉🎉 One demo paper is accepted by WWW 2024.
📝 Publications
A Sampling-based Framework for Hypothesis Testing on Large Attributed Graphs
Yun Wang, Chrysanthi Kosyfaki, Sihem Amer-Yahia, Reynold Cheng
HINCare: An Intelligent Helper Recommender System for Elderly Care
Carrie Wang, Wentao Ning, Xiaoman Wu, Reynold Cheng
Knowledge-Based SystemsUsing a novel clustered 3D-CNN model for improving crop future price prediction, Liege Cheung, Yun Wang, Adela S M Lau, Rogers M C Chan
🎖 Honors and Awards
- 2023-2027 HKU Postgraduate Scholarship
- 2021-2022 Dean’s Honors List
- 2020-2021 Yu Kam Tim Chan Siu Hing Award in Artificial Intelligence and Data Science
- 2018-2022 HKU Foundation Entrance Scholarship
- 2018-2019 Dean’s Honors List
- 2016-2018 First prize in the MOMENTUM Social Innovation Contest
📖 Education
- 2023.08 - 2027.06 (now), PhD, The University of Hong Kong, Hong Kong.
- 2018.09 - 2023.01, Undergraduate, Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong.
- 2015.01 - 2018.06, Cambridge International Exam Center in Shanghai Experimental School, Shanghai.
👩🏫 Teaching
- Fall 2024: Introduction to Database Management Systems
- Spring 2024: Big Data Management
- Fall 2020: Probability and Statistics I