连德富

· Personal Information

E-Mail:


Contact Information:liandefu@ustc.edu.cn


Professional Title:特任教授


Supervisor of Doctorate Candidates


Supervisor of Master's Candidates


Discipline: Computer Science and Technology
Academic 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...

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· 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 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.