Bootstrap Image Preview

Liqiang Wang

Associate Professor, Graduate Coordinator
Department of Computer Science
University of Central Florida
Orlando, FL 32816
HEC 437E

Tel: (407) 823-3187
Fax: (407) 823-5835
E-mail: lwang AT cs.ucf.edu


Bootstrap Image Preview

Latest News


  • 12/2021: Congratulations to Bingbing Rao, Ehsan Kazemi, and Yifan Ding for their paper "CTIN: Robust Contextual Transformer Network for Inertial Navigation" accepted by AAAI 2022 (with acceptance rate of 15%)!
  • 09/2021: "Education in Advanced Artificial Intelligence" ($50,000) was awarded by Facebook!
  • 08/2021: Congratulations on the graduations of Yandong Li and Muhammad A. Jamal! Yandong joined Google Research, and Muhammad joined Intuitive Surgical.
  • 07/2021: Congratulations to Muhammad A. Jamal for his paper "A Lazy Approach to Long-Horizon Gradient-Based Meta-Learning" accepted by ICCV 2021!
  • 07/2021: Congratulations to Bingbing Rao for his paper "SODA: A Semantics-Aware Optimization Framework for Data-Intensive Applications Using Hybrid Program Analysis" accepted by IEEE Cloud Computing 2021!
  • 03/2021: Congratulations to Yandong Li for his paper "Ranking Neural Checkpoints" accepted by CVPR 2021!
  • 03/2021: Our deep learning based COVID-19 model has been included in the CDC COVID-19 Forecasting Hub (UCF Today News).
  • 01/2021: Our project on Deep Learning based Motion Tracking was funded by ARMY!

  • Short Bio

    Liqiang (Eric) Wang is an associate professor and the Graduate Coordinator in the Department of Computer Science at the University of Central Florida. He is the director of Big Data Lab. He was a faculty member (2006-2015) in the Department of Computer Science at the University of Wyoming . He received Ph.D. in Computer Science from Stony Brook University in 2006. He was a visiting Research Scientist in IBM T.J. Watson Research Center during 2012-2013.

    His research focuses on big data computing and analytics techniques in the following aspects: (1) improving accuracy and security of big data analysis models; (2) optimizing performance and scalability of big data processing and parallel computing systems, including multi-threading, HPC, Cloud and GPU platforms; (3) using program analysis and deep learning techniques to detect and prevent programming errors and execution anomaly in big data and/or parallel programs.

    He received NSF CAREER Award in 2011, Castagne Faculty Fellowship (2013-2015), and Mid-Career Refresh Award (UCF, 2020).

    Research Hightlight