Title: Data Management for Deep Learning

11:15 a.m. ~ 12:15 p.m., 19 February 2024 (Monday), The Sukosol Hotel, Bangkok, Thailand

Prof. Lei Chen

Hong Kong University of Science and Technology

Abstract

Deep learning (DL) has made significant progress and found wide application in various fields, like chaptGPT for question answering. However, the success and efficiency of DL models depend on proper data management. Training deep learning-based image classifiers is challenging without labeled data, and efficiency is hindered by large datasets, complex models, and numerous hyperparameters. Lack of validation and explanation limits model applicability. In this presentation, I will discuss three crucial issues in data management for deep learning: 1) effective data preparation for DL, including extraction, integration, and labeling; 2) DL training optimization, involving data compression and computation graph optimization; and 3) the importance of model explanation for robustness and transparency. I will conclude by highlighting future research directions.

Bio

Lei Chen, is a chair professor in the data science and analytic thrust at HKUST (GZ), Fellow of the IEEE, and a Distinguished Member of the ACM. Currently, Prof. Chen serves as the dean of information hub, the director of Big Data Institute at HKUST, MOE/MSRA Information Technology Key Laboratory. Prof. Chen’s research interests include Data-driven AI, knowledge graphs, blockchains, data privacy, crowdsourcing, spatial and temporal databases and query optimization on large graphs and probabilistic databases. He received his BS degree in computer science and engineering from Tianjin University, Tianjin, China, MA degree from Asian Institute of Technology, Bangkok, Thailand, and PhD in computer science from the University of Waterloo, Canada. Prof. Chen received the SIGMOD Test-of-Time Award in 2015, Best research paper award in VLDB 2022, .The system developed by Prof. Chen’s team won the excellent demonstration award in VLDB 2014. Prof. Chen had served as VLDB 2019 PC Co-chair. Currently, Prof. Chen serves as Editor-in-chief of IEEE Transaction on Data and Knowledge Engineering and an executive member of the VLDB endowment.