Academic Experience
Education & POST EDUCATION
2019.09 – 2021.12
Postdoctoral Research Scientist, Grossman Center for the Statistics of Mind, Columbia University
Advisor: Prof. Liam Paninski and Prof. John Cunningham
2015.09 – 2019.09
Doctor of Philosophy in Princeton Neuroscience Institute, Princeton University.
Minor certificate: Quantitative and Computational Neuroscience
Minor certificate: Statistics and Machine Learning (news about me from CSML Princeton)
Advisor: Prof. Jonathan Pillow
Ph.D. Dissertation title: “Bayesian latent structure discovery for large-scale neural recordings”
2011.08 – 2014.05
Master of Science in Computer Science Department in Viterbi School of Engineering, University of Southern California.
Advisor: Prof. Cauligi Raghavendra
2007.09 – 2011.07
Bachelor of Science in the School of Electronics and Information Engineering, Harbin Institute of Technology (HIT), Harbin, P.R. China.
Advisor: Prof. Daren Yu
Selected Awards and Honors
[Oct 2018] Rising Star in EECS by MIT.
[Apr 2018] Google PhD fellowship nomination by Princeton University. (2 nominees out of 10 university-wise fields)
[2015 - 2019] Conference awards & financial supports: NeurIPS2015, NeurIPS2017, NeurIPS2018, NeurIPS2020, COSYNE2016, COSYNE2018 (20 out of 366 presenters), COSYNE2019, BNP2017, ICLR2019.
[2015 - 2016] First Year Fellowship in Natural Sciences and Engineering, Princeton University.
[2011 - 2013] Chevron Fellowship in Viterbi Engineering of School, University of Southern California.
[Dec 2010] CASIC Scholarship in Electronic Information Engineering, HIT.
[Feb 2010] Honorable Mention, MCM/ICM Contest.
[2009 - 2010] BESTA Scholarship in Electronic Information Engineering, HIT.
[2008 - 2010] First/Second Grade Scholarships, HIT.
Teaching
Guest lecturer for Neuro-AI class at UFL.
Teaching assistant (remote) for the 10th Computational & Cognitive Neuroscience (CCN) Summer School, July 17-August 8 2021, in Suzhou, China.
Tutorial lecturer. Neuromatch Academy 2020, Summer 2020.
NEU-314: Mathematical Tools for Neuroscience, Fall 2017.
NEU-314: Mathematical Tools for Neuroscience, Fall 2016.
Service
Workshop
Co-organizer. Interpretable computational neuroscience: What are we modeling and what does it have to do with the brain? Cosyne 2020 workshop.
Session Host
Sessions in Theme D: Cognition, Motivation and Emotion and Theme E: Computational modeling and Techniques at Neuromatch 3.0.
Area Chair/Meta Reviewer
Asian Conference on Machine Learning (ACML) 2022
International Conference on Machine Learning (ICML) 2022
Neural Information Processing Systems (NeurIPS) 2022
The International Conference on Learning Representations (ICLR) 2023
Program Committee & Reviewer
Bayesian Deep Learning (BDL), NeurIPS 2021 workshop
Bayesian Nonparametric (BNP), NeurIPS 2018 workshop
Artificial Intelligence and Statistics (AISTATS) 2018, 2020
Neural Information Processing Systems (NeurIPS) 2016, 2019, 2021
International Conference on Machine Learning (ICML) 2019, 2020
Association for Uncertainty in Artificial Intelligence (UAI) 2020, 2021
Asian Conference on Machine Learning (ACML) 2019, 2020, ACML Journal Track
The International Conference on Learning Representations (ICLR) 2020-2022
AAAI Conference on Artificial Intelligence (AAAI) 2020
Computational and Systems Neuroscience (Cosyne) 2022
Journal of Machine Learning Research (JMLR)
PLOS Computational Biology
Neurons, Behavior, Data analysis, and Theory
IEEE Transactions on Signal Processing
Nature Methods
Neurocomputing
Membership
IEEE brain