Ju Sun (孙举)
4-192 Keller Hall
200 Union Street SE
Minneapolis, MN 55455
Assistant Professor
Computer Science & Engineering
Data Science Graduate Faculty
Institute for Health Informatics (Affiliate Faculty)
Institute for Engineering in Medicine (Affiliate Faculty)
University of Minnesota, Twin Cities
Research Interests: machine learning, data sciences, and numerical optimization, computer vision, signal/image processing, and computational imaging, healthcare. See my [CV].
Contact
- Email: jusun@umn.edu \ \ sunjunus@gmail.com
- Office: 5-225E, KHKH
- Phone: 612-301-2729
- Webpage: http://sunju.org
- Office Hour: 5 – 6pm Tue/Thur (2020 Fall)
Seminars
What’s new
Upcoming
Past
- Media: An AI-based diagnostic system for COVID-19 based on chest x-rays developed by our group has been deployed and tested in M Health Fairview, and goes live in their decision-support system today! See this UMN, M Health Fairview, and Epic joint press release, CSE news article and this coverage by StarTribune. (Oct 01, 2020)
- Talk: “运筹千里”纵横论坛 organized by Operation Research Society of China (Sep 27, 2020) [Slides]
- Talk: IMA Data Science Seminar at UMN (Sep 08, 2020)
- Talk: AIME2020: International Conference on Artificial Intelligence in Medicine (Hosted virtually by UMN, Aug 25–28, 2020) [Slides]
- Grant approval: DOE: FAIR Framework for Physics‐Inspired Artificial Intelligence in High Energy Physics (Co-PI, Aug 10, 2020)
- Grant approval: NSF 2038403: CPS: Medium: Smart Tracking Systems for Safe and Smooth Interactions Between Scooters and Road Vehicles, as covered by UMN CSE news (Co-PI, Aug 04, 2020)
- Service: To be an Area chair for AISTATS 2021 (Jul 18, 2020)
- Talk: SIAM Conference on Imaging Science Virtual Conference (Jul 6–17, 2020) [Slides]
- Grant approval: OVPR COVID19 Rapid Response Grant # 10: Rapid detection and severity trajectory of COVID19 using X-ray images and artificial intelligence (May 01, 2020)
- Talk: SIAM Conference on Mathematics of Data Science at Cincinnati, Ohio (postponed for the BEERvirus, 2020)
- Paper release: our new paper Inverse Problems, Deep Learning, and Symmetry Breaking is on arXiv. We show how symmetries in nonlinear inverse problems can cause a significant difficulty for the end-to-end deep learning approach, and how to address it by breaking the symmetry (Mar 20, 2020).
- Talk: Workshop on Numerical Algebra in High-Dimensional Data Analysis at Tianyuan Mathematical Center in Southeast China (TMSE), Xiamen, China (Dec 27–29, 2019)
- Talk: INFORMS Annual Meeting 2019 at Seattle (Oct 20–23, 2019)
- Join CS&E @ UMN as an assistant professor! (Jul 01, 2019)
Archive
- Stanford years (2016 – 2019)
- Columbia years (2011 – 2016)