Hi! I am an Assistant Professor at the School of Mathematics, University of Birmingham. I am also a visiting scholar at the Cambridge Image Analysis Group, University of Cambridge. My research interests include large-scale optimization, statistical learning theory, explainable AI, with applications in many areas of data science, such as inverse problems in computational and medical imaging. Most recently, my research has been focusing on the theoretical foundations of non-convex optimization in computational imaging with deep-learning image priors, and efficient deep unrolling networks for medical imaging. Meanwhile, I am also diving into the research of large-scale optimization and machine learning for computational social science and financial applications.
In 2019, I completed my Ph.D in the University of Edinburgh under the supervision of Prof. Mike Davies and my research was fully funded by EU H2020 project MacSeNet Innovative Training Network. Prior to that, I had 4 wonderful years in Sichuan University, China as a undergrad majoring in Communication Engineering from 2010 to 2014.
Email: j.tang.2[AT]bham.ac.uk
PhD students:
Guixian Xu (9/2024-now, University of Birmingham) Principal supervision. Research areas: Optimization, Unsupervised Learning, Inverse Problems
Hong Ye Tan (3/2022-5/2025, University of Cambridge) Co-supervision. Thesis: “Designing Provably Convergent Algorithms from the Geometry of Data” — Defended without correction.
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Teaching:
Bayesian Inference and Computation (Module-Lead)
[Lecture notes][slides_1][slides_2][slides3][slides4][slides5][slides6][problem_sheet1][ps2][A1][seed]
Nonlinear Programming I (Module-Lead).
[gradient_method_example1][example_2][example_3][example_4][example_5]
[Newton’s method example][example_2][software] .
Algebra and Combinatorics (Module-Lead)..
JT 