Shaobo Han is a Senior Researcher at NEC Laboratories America, working on the design and development of machine learning and signal processing algorithmic solutions for real-world sensing applications. He is interested in generalizable AI methods that can cope with limitations in data acquisition and domain shifts in deployment environments. He received Ph.D. in Electrical and Computer Engineering and M.S. in Statistical Science from Duke University. His Ph.D. advisor was Lawrence Carin.
His research interest includes:
[2023/05] UAI 2023 Top Reviewer.
[2023/05] Our work on fiber sensing AI was featured by Laser Focus World: Top Stories and Photonics Hot List.
[2023/05] Guest Lecture: Automatic Differentiation and Differentiable Programming, In CS 610: Data Structure and Algorithms, NJIT.
[2023/04] I will serve as a reviewer for NeurIPS 2023.
[2023/02] Our paper Ambient noise-based weakly supervised manhole localization methods over deployed fiber networks “ has been accepted by Optics Express.
[2022/12] I will serve as a reviewer for UAI 2023.
[2022/09] Our paper Using Global Existing Fiber Networks for Environmental Sensing” has been accepted by Proceedings of the IEEE.
[2022/07] Received Outstanding Performance Award 2022, Global Innovation Unit, NEC Corporation.
[2022/06] I will serve as a reviewer for ICLR 2023.
[2022/01] Two papers accepted to ICLR 2022. Topics include (i) test-time policy adaptation under ordinal reward, and (ii) zero-shot domain adaptation with multiway categorical domain descriptor.
[2021/06] Two AI-based fiber sensing solutions have been commercialized: NEC’s press release.