Weilin Li

Weilin Li is an Assistant Professor in the Department of Mathematics at the City College of New York (CUNY). His research focuses on applied and computational harmonic analysis, with emphasis on super-resolution, quantization methods, and signal processing. He holds a PhD in Mathematics from the University of Maryland, College Park, and was previously a Courant Instructor at New York University.

Education

• PhD in Mathematics, University of Maryland, College Park (201X)
• Courant Instructor, New York University, 201X-201X

Research Interests

Dr. Li's work bridges pure mathematics and applied sciences, with key areas including nonharmonic Fourier analysis, spectral super-resolution, and compressed sensing. His methods address challenges in signal reconstruction under quantization constraints and subspace estimation techniques.

Recent Trends in Publications

Recent work explores optimality of spectral estimation algorithms (e.g., Gradient-MUSIC), stability of Fourier matrices, and applications of scattering transforms in hyperspectral imaging. His research often intersects with machine learning, particularly in understanding approximation capabilities of neural networks under quantization.

Awards & Grants

• Recipient of the 2021 Charles Chui Young Researcher Best Paper Award
• Funded by NSF, PSC-CUNY, and City College Foundation grants

Academic Engagement

Co-organizer of the One World MINDS Seminar, CUNY GC Harmonic Analysis and PDE Seminar, and CUNY analysis learning seminars. Active in mentoring graduate students, including Ben Tupper who joined the PhD program in 2025.