I am always looking to hire talented PhD students. Please contact me zzhang15@wpi.edu.

Vision, Intelligence, and System Laboratory (VISLab) at Worcester Polytechnic Institute (WPI) is led by Prof. Ziming Zhang. The aim of the lab is to engage in the state-of-the-art research into the mathematical foundation of computer vision (CV) and artificial Intelligence (AI), as well as the hardware design and engineering that meets the needs of society. Current research focus is TEAM-Efficient Learning:

  • Training Efficiency: Improving the convergence and training speed of learning algorithms.
  • Inference Efficiency: Developing real-time algorithms for broader applicability.
  • Data Efficiency: Training (deep) models using small amount of (even no) training samples.
  • Model Efficiency: Developing hardware-friendly lightweight (deep) models & algorithms.

About Me

Dr. Ziming Zhang is an assistant professor at Worcester Polytechnic Institute. Before joining WPI he was a research scientist at Mitsubishi Electric Research Laboratories (MERL) in 2016-2019. Prior to that, he was a research assistant professor at Boston University, a postdoc at Boston University working with Prof. Venkatesh Saligrama and a postdoc at UNC Chapel Hill working with Prof. Dinggang Shen (now at the ShanghaiTech University). Dr. Zhang received his PhD in 2013 from Oxford Brookes University, UK, under the supervision of Prof. Philip H. S. Torr (now at the University of Oxford). His research areas lie in computer vision and machine learning, especially in deep learning, zero-shot learning, optimization, 2D/3D object recognition/detection/segmentation, person re-identification, video retrieval, point cloud processing, IoT, autonomous driving, and time-series data analysis. His works have appeared in PAMI, CVPR, ICCV, ECCV, ICLR, NIPS, ACM MM, ICDM. He serves as a review/PC member for top conferences (e.g. CVPR, ICCV, ECCV, NIPS, ICML, ICLR, AAAI, AISTATS, IJCAI) and journals (e.g. PAMI, IJCV, JMLR).

His work “Deep Learning-based Water Detector” won the R&D100 Award 2018.

Recent News

  • 03/03/2021. One paper was accepted to CVPR 2021.
  • 02/23/2021. One paper was accepted to IEEE Robotics and Automation Letters.
  • 01/28/2021. Welcome Yuping Shao to join our lab!
  • 01/09/2021. Our 2nd workshop Vision Applications & Solutions to Biased or Scarce Data at WACV 2021 was held successfully.
  • 11/10/2020. One paper was accepted to ACS Sensors.
  • 10/11/2020. Three papers were accepted to ICPR 2020.
  • 09/25/2020. One paper was accepted to NeurIPS 2020.
  • 08/31/2020. Welcome Yun Yue to join our lab!
  • 08/20/2020. One paper was accepted to ICDM 2020.
  • 08/14/2020. Grateful to receive an NSF award for Knowledge Integrated Data-Efficient Deep Learning.
  • 07/28/2020. One paper was accepted to MICCAI ASMUS 2020.
  • 07/28/2020. One paper was accepted to ACM MM 2020.
  • 07/01/2020. Our team achieved Rank-1 in the leaderboard of AI City Challenge 2020 Track3: City-Scale Multi-Camera Vehicle Re-Identification. See our demo video for visual analysis.
  • 03/13/2020. One paper was accepted to CVPR 2020 as oral.
  • 03/05/2020. Our workshop Vision Applications & Solutions to Biased or Scarce Data at WACV 2020 was held successfully.
  • 03/01/2020. Two papers were presented at WACV 2020.
  • 01/31/2020. I gave a talk at United Imaging Intelligence (UII), Cambridge, MA.
  • 01/15/2020. I gave a talk at Wayfair, Boston, MA.
  • 12/19/2019. One paper was accepted to ICLR 2020 as poster.
  • 11/22/2019. Two proposals were funded by GDMS’s University RFP program.
  • 10/01/2019. Joined in WPI as assistant professor.

Funding Sponsors

We sincerely appreciate the support from

  • National Science Foundation (NSF)
  • General Dynamics Mission Systems (GDMS)