Projects per year
Personal profile
Personal profile
Dehui Yang earned his PhD from Colorado School of Mines in 2018. Before joining Xi’an Jiaotong-Liverpool University in 2023, he worked as an applied scientist at Uber Technologies Inc from 2021 to 2023, leading several company-wide initiatives in the areas of driver incentives pricing and driver risk modeling. Prior to that, he was one of the founding data scientists at Root Inc from 2018 to 2021, working on insurance pricing and reserving with statistical machine learning methods, telematics-based risk pricing, and more. His interests lie in the general areas of data science, including the recovery of low-dimensional structures from high-dimensional observational datasets, predictive modeling using statistical machine learning techniques, and risk scoring and pricing. He serves as a reviewer for international journals, including IEEE Transactions on Signal Processing, IEEE Transactions on Image Processing, IEEE Transactions on Information Theory, IEEE Signal Processing Letters, IEEE Journal of Selected Topics in Signal Processing, Applied and Computational Harmonic Analysis, and Signal Processing.
[2024/10/15] News: I'm looking for motivated students working directly with me on a few research projects in the areas of mathematical signal processing, modal analysis using signal processing techniques. Prospective students with solid foundation in math, signal processing as well as coding skills are welcome to contact me.
Research interests
Recovery of low-dimensional structures from high-dimensional datasets
Applied machine learning and predictive modeling
Deep learning, LLM, and their applications in science and healthcare
Risk scoring
Experience
Assistant Professor, XJTLU, 2023-Now
Applied Scientist II, Uber Technologies Inc., 2021-2023
Founding Data Scientist, Root Inc, 2018-2021
PhD Research Intern, Technicolor Research AI Lab, 2017
Teaching
MTH013, Calculus for Science and Engineering, XJTLU, Fall 2024
Undergraduate Data Science Reading Group, Spring 2024
MTH416, Neural Networks and Deep Learning, XJTLU, Spring 2024
MTH019, Calculus for Business, XJTLU, Fall 2023
EENG 411 Digital Signal Processing, Colorado School of Mines, Spring 2016
Awards and honours
Best Research Intern Runner-Up (among all PhD interns in US and France), Technicolor Research, 2017
Best Poster and Best Oral Presentation, Computing-Mines Affiliates Partnership Program (C-MAPP) Award Event, Colorado School of Mines, 2016
Best Poster Runner-Up, Computing-Mines Affiliates Partnership Program (C-MAPP) Award Event, Colorado School of Mines, 2015
Departmental Summer Fellowship, Colorado School of Mines, 2013
Education/Academic qualification
Ph.D. in Electrical Engineering, Colorado School of Mines, 2018
B.E. in Communication Engineering, Zhejiang University of Technology, 2011
Person Types
- Staff
Fingerprint
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- 5 Similar Profiles
Projects
- 1 Active
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Physics-Informed Deep Learning Approaches for Parameter Estimation and Super-Resolution
1/07/24 → 30/06/27
Project: Internal Research Project
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Atomic Norm Minimization for Modal Analysis From Random and Compressed Samples
Li, S., Yang, D., Tang, G. & Wakin, M. B., 1 Apr 2018, In: IEEE Transactions on Signal Processing. 66, 7, p. 1817-1831 15 p.Research output: Contribution to journal › Article › peer-review
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Weighted Matrix Completion and Recovery with Prior Subspace Information
Yang, D., Wakin, M. & Eftekhari, A., 16 Mar 2018, In: IEEE Transactions on Information Theory. 64, 6, p. 4044-4071 28 p.Research output: Contribution to journal › Article › peer-review
Open Access -
A super-resolution algorithm for multiband signal identification
Zhu, Z., Yang, D., Wakin, M. B. & Tang, G., 2 Jul 2017, Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. Matthews, M. B. (ed.). Institute of Electrical and Electronics Engineers Inc., p. 323-327 5 p. 8335193. (Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017; vol. 2017-October).Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review
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Atomic norm minimization for modal analysis with random spatial compression
Li, S., Yang, D. & Wakin, M. B., 16 Jun 2017, 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 3251-3255 5 p. 7952757. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review
Open Access
Activities
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SURF-2024-0333: Deep Learning-Based AI Models for Breast Cancer Diagnosis Using Medical Imaging Data: A Case Study
Dehui Yang (Supervisor)
15 Jun 2024 → 28 Aug 2024Activity: Supervision › Completed SURF Project
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SURF-2024-0248: Statistical Learning Approaches for Auto Insurance Pricing
Dehui Yang (Supervisor)
15 Jun 2024 → 28 Aug 2024Activity: Supervision › Completed SURF Project
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2024 Radar Workshop
Dehui Yang (Invited speaker)
13 Jan 2024Activity: Talk or presentation › Presentation at conference/workshop/seminar
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IEEE Transactions on Signal Processing (Journal)
Dehui Yang (Reviewer)
9 Jan 2024 → 18 Sept 2024Activity: Peer-review and editorial work of publications › Publication Peer-review