Dr. Cheng LONG

Cheng LONG

Assistant Professor
Data Management @Nanyang Tech
School of Comp Sci and Engineering
Nanyang Technological University

Email: c.long@ntu.edu.sg
Office: N4-2c-94
Address: 50 Nanyang Avenue, Singapore, 639798
Telephone: +65 6790 6822

DBLP profile
Google Scholar profile

Openings: We have openings of Post-Doc, PhD students, visiting scholars/students from time to time. Please contact me via email if you have interest.

Biography: Cheng LONG is currently an Assistant Professor at the School of Computer Science and Engineering, Nanyang Technological University, Singapore. From 2016 to 2018, he worked as an academic lecturer at Queen's University Belfast, UK. He received his PhD degree from the Hong Kong University of Science and Technology, Hong Kong, in 2015, and his BEng degree from South China University of Technology, China, in 2010.

Research Interests: He has research interests broadly in data management and data mining. Specifically, he works in (a) spatial data management with machine learning-based techniques, (b) spatial data mining in the urban domain (e.g., traffic and mobility), (c) graph data mining (namely dense subgraph mining and graphlet mining), and recently in (d) high-dimensional vector data management (e.g., approximate neareast neighbor search). For details of his research, please refer to his research summary and publications.

Selected Awards:

  • Best Paper Award of SIGMOD'20 (Nominee), 2020
  • Fulbright-RGC Hong Kong Research Scholar Award, provided by Research Grants Council (RGC) of Hong Kong, 2014
  • Prof. Francis Chin Research Award (Best Research Award), provided by ACM (HK), 2013
  • Overseas Research Award, provided by HKUST, 2013
  • Professor Samuel Chanson Teaching Assistant Award (Best Teaching Assistant Award), provided by HKUST, 2012
  • Champion in 6th Postgraduate Paper Contest, provided by IEEE (HK) Computational Intelligence Chapter, 2012

Selected Talks:

  • Nearest Neighbor Search on High-Dimensional Vector Data, Huawei Sentosa Software Technology Summit (2023)
  • RL4SpatialDB: On Leveraging Reinforcement Learning for Spatial Data Management, Microsoft Research Lab - Redmond (2023); MUST 2023 (keynote), Southeast U (2023)
  • Dense Subgraph Mining: Applications, Problems, and Algorithms, KDD.SG (2023); Nanjing UST (2023); WeBank (2022)
  • Big Trajectory Data Management and Mining with Reinforcement Learning, BIT (2022); Beihang U (2022)
  • Pre-Processing and Querying Big Trajectory Data with Reinforcement Learning, UrbComp 2022 (keynote); Aalborg U (2021)
  • Spatial and Spatiotemporal Data Analytics and Their Applications in Urban Cities, VISTEC (2019); Huawei (2019); IIT Delhi (2019)