I am an Assistant Professor of Computer Science at Brandeis University. My research interests are artificial intelligence, machine learning, and data mining, in particular graph mining and learning, and AI for social good.
Recently, I focus on developing resource-efficient and trustworthy graph learning theories and algorithms. I also use AI to combat the opioid crisis, improve food and nutrition service, enhance social and information infrastructure security, and advance interdisciplinary studies.
- Looking for self-motivated PhD students and interns.
- 01/2023 - Three papers were accepted to ICLR'23.
- Service: SPC for KDD'23, IJCAI'23
- 11/2022 - Selected for the AAAI'23 New Faculty Highlights.
- 10/2022 - Top reviewer of NeurIPS'22.
- 09/2022 - Two papers were accepted to NeurIPS'22.
- Recent Talk: Resource-efficient graph representation learning [slide]
- 08/2022 - Received NSF D-ISN grant.
- Service: SPC for AAAI'23, WSDM'23, SDM'23
- 05/2022 - Five papers were accepted to KDD'22 research track.
- 05/2022 - KDD'22 Tutorial: Towards graph minimally-supervised learning
- Recent Talk: Few-shot learning on graphs [slide] [survey]
- Service: SPC for KDD'22, AAAI'22, CIKM'22
- 11/2021 - RxNet won the best paper award at CIKM'21 (1 out of 1251 submissions).
- 09/2021 - One paper was accepted to NeurIPS'21.
- 05/2021 - Received Brandeis provost research grant.
- Service: SPC for AAAI'21, IJCAI'21
- General: Artificial Intelligence, Machine Learning, Data Science
- Focus: Graph Mining and Learning, AI for Social Good, Resource-efficient AI, Trustworthy AI
- Applications: Public Health, Social and Information Systems, Food and Nutrition, Interdisciplinary Studies, Recommendation
Last update in 01/2023