Welcome to Defu Cao’s Homepage
Defu Cao /dəfu: tsaʊ/ is a Ph.D. student in the Thomas Lord Department of Computer Science at the University of Southern California, working with Prof. Yan Liu at the USC Melady Lab. He is also working with Prof. Angela Zhou from USC Marshall Data Sciences and Operations.
Prior, he earned his Master’s Degree at the School of EECS Peking University, where he was co-advised by Prof. Xu Cheng and Prof. Xianhua Liu.
Cao’s research primarily focuses on developing advanced machine learning and data mining algorithms for structured data, with a particular emphasis on time series foundation models. His work aims to create models that demonstrate a deep understanding of temporal patterns and dynamics in various domains, including spatio-temporal and relational data. To this end, his research aims to integrate causal inference, graph neural networks, spectral domain representation, interpretability, and robustness.
In addition, he is also interested in causal representation learning and pre-training large language models. He has published his research in top conference proceedings including NeurIPS, CVPR, ICLR, ICRA, ICDM, and NAACL.
News
- 10/2024: Invited talk on Time Series Foundation Model in QuantLLM Community!
- 10/2024: Invited talk on Time Series Foundation Model in Lehigh University!
- 09/2024: Invited talk on Time Series Foundation Model in Emory University!
- 09/2024: One paper on Simulator Calibration with Google Research accepted by NeurIPS!
- 06/2024: Defu Cao started his summer internship at Cubist as a Quantitative Researcher in Foundation Models!
- 04/2024: Time Series Foundation Model - TEMPO (ICLR 2024) published on Github and Hugging Face!
- 04/2024: Defu Cao has been selected for the 2024 Best Research Assistant Award in USC! (1 per department)
- 03/2024: Defu Cao awarded a Graduate School Endowed Fellowship for the academic year!
- 01/2024: One paper accepted by WWW and two papers accepted by ICLR!
- 12/2023: One paper on multi-modal time series foundation model accepted by AAAI Mentored Undergraduate Research Program!
- 10/2023: One paper on Financial Time-Series Forecasting accepted by ICAIF as Oral paper!
- 06/2023: Joined MBZUAI as a visiting scholar, working with Prof. Kun Zhang!
- 06/2023: Invited talk at Google Sustainable Urban Mobility: Simulation and Optimization Workshop! slides.
- 02/2023: One paper on Representation Learning accepted by CVPR!
- 01/2023: One paper on Neural Operator accepted by ICLR!
- 12/2022: One paper on Time-Series Forecasting accepted by SDM!
- 11/2022: One paper on Causal Inference accepted by AAAI!
- 10/2022: One paper on Out-of-distribution benchmark accepted by NeurIPS DistShift!
- 09/2022: One paper on Causal Inference accepted by NeurIPS!
- 07/2022: One paper on Causal Inference accepted by ICML Continuous time workshop!
- 05/2022: One paper accepted by IEEE ICCCAS!
- 04/2022: One paper accepted by NAACL main conference!
- 03/2022: Published the pre-print survey paper of ‘Physics-Informed Machine Learning’!
- 02/2022: Accepted the Research Scientist Intern offer at Adobe Research!
- 01/2022: One paper accepted by PAKDD!
- 11/2021: Organized ICAIF 2021 workshop - Time Series in Finance!
Internships & Research Experience
- Summer 2024: Quantitative Researcher in Foundation Models at Cubist Systematic Strategies
- Summer 2023: Research Assistant at MBZUAI, working with Prof. Kun Zhang and Prof. Biwei Huang on causality
- Summer 2022: Research Intern at Adobe Research, mentored by Dr. Zhaowen Wang
- Previous: Research Intern at Microsoft Research Lab Asia (MSRA) (twice), working with Dr. Yujing Wang and Alibaba Damo Academy’s Data Analytics and Intelligence Lab, advised by Dr. Jingren Zhou
- First Internship: Baidu, 7 years ago
Awards
- 2024, Best Research Assistant Award
- 2024, Endowed Fellowship
- 2021, Annenberg Fellowship
- 2021, MSRA Stars of Tomorrow Internship Program Award
- 2020, National Scholarship for Graduate Students
- 2020, Huawei Scholarship
- 2019, Intel Scholarship