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Liqiang Wang

Department of Computer Science
University of Central Florida
Orlando, FL 32816
HEC 332

Tel: (407) 823-3187
Fax: (407) 823-5835
E-mail: lwang AT

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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 a professor 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