- Columbia University E6894: Deep Learning for Computer Vision, Speech, and Language, guest lecturer (Fall 2018)
- UIUC NPRE 451: Radiation Detection & Instrumentation Laboratory (Fall 2013)
- UIUC NPRE 451: Radiation Detection & Instrumentation Laboratory (Spring 2013)
- UIUC NPRE 451: Radiation Detection & Instrumentation Laboratory (Fall 2012)
- Tsinghua University, part-time lecturer at Work-Study Center (2005-2009)
Grant Review Panel
- National Institute of Food and Agriculture, United States Department of Agriculture (USDA-NIFA), 2018
Program Organizing Committee
- Workshop on Real-World Recognition from Low-Quality Images and Videos, ICCV, 2019
- Workshop on Weakly Supervised Learning for Real-World Computer Vision Applications, CVPR, 2019
- The 1st Learning from Imperfect Data Challenge, CVPR, 2019
- IEEE Workshop on Analysis and Modeling of Faces and Gestures, ICCV, 2017
- Huang Symposium, UIUC, 2016
- Frontiers in Big Data, ICT and Digital Humanities
- IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
- IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
- IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
- IEEE Transactions on Multimedia (TMM)
- Springer Multidimensional Systems and Signal Processing (MULT)
Conference Technical Program Committee
- Neural Information Processing Systems (NIPS)
- International Conference on Machine Learning (ICML)
- IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
- IEEE International Conference on Computer Vision (ICCV)
- IEEE International Conference on Image Processing (ICIP)
- International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)
- International Conference on Information Fusion (FUSION)
I suggest all my students follow this as well.
- What are you trying to do? Articulate your objectives using absolutely no jargon.
- How is it done today, and what are the limits of current practice?
- What is new in your approach and why do you think it will be successful?
- Who cares and why?
- If you’re successful, what difference will it make? What applications are enabled as a result?
- What are the risks?
- How much will it cost? How long will it take?
- What are the midterm and final check points to evaluate progress towards success?