· Personal Information
E-Mail:
Contact Information:liandefu@ustc.tsg211.com
Professional Title:Special Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates
Discipline: Computer Science and TechnologyAcademic Honor 2020 National outstanding youth fund winner
· Other Contact Information:
Email:
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· Personal Profile
Defu Lian is a professor from University of Science and Technology of China. His main research interest lies in data mining and deep learning. He has published more than 160 papers at prestigious conferences and journals, and received a best paper runner-up in APWeb 2016, best paper candidate in WWW 2021 and best paper award in WISE 2022. He developed a highly-modularized recommender system (Re...
· Education Experience
- 2009.9 ~ 2014.6
- University of Science and Technology of China - Computer Applications Technology - Doctoral Degree in Engineering - With Certificate of Graduation for Doctorate Study
- 2005.9 ~ 2009.6
- University of Science and Technology of China - Computer Science and Technology - Bachelor's Degree - University graduated
· Work Experience
- 2018.10-2022.12
- University of Science and Technology of China - Research Professor, Professor
- 2014.7-2018.10
- University of Electronic Science and Technology of China - Lecture, Associate Professor
· Social Affiliations
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· Research Focus
· Research Group
· Name of Research Group:AI Decision Group
Description of Research Group:investigate high-dimensional similarity search, retrieval-augmented generation, and large model agents, with applications in smart cockpits, computational advertising, and intelligent chemistry/engineering
· Name of Research Group:AI Theory Group
Description of Research Group:investigate AI fundamental methods and theories, including but not limited to long-tail learning, learning to rank, extreme classification, extreme arm bandits, combinatorial optimization, graph machine learning, continual learning, and multi-task learning.
· Name of Research Group:AI Model Group
Description of Research Group:Investigate the design of AI models for scenarios involving time-series data, recommendation data, graph data, text data, and more. This includes universal embedding models, large multimodal models, and large-scale time-series models
· Name of Research Group:Trustworthy AI Group
Description of Research Group:investigate interpretability, robustness, computational auditing, unlearning, privacy protection, invariant representation learning, fairness, and compositional generalization of AI algorithms.