Scholar
Jiaqi Leng
Google Scholar ID: Rr83RUsAAAAJ
University of California, Berkeley
Citations & Impact
Citations
206
H-index
8
i10-index
6
Publications
17
Co-authors
21
list available
Publications
Resume (English only)
Academic Achievements
- Publications:
- - 'Operator-Level Quantum Acceleration of Non-Logconcave Sampling' Preprint, 2025
- - 'Expanding hardware-efficiently manipulable Hilbert space via Hamiltonian embedding' published in Quantum, 2025
- Talks:
- - 2025 INFORMS Annual meeting, talk on 'quantum-accelerated algorithms for (classical) Gibbs sampling'
- - Keynote talk titled 'Gradient Flows in Quantum Optimization' at the Purdue Quantum AI Workshop, organized by the Edwardson School of Industrial Engineering at Purdue University
- Workshop Acceptance:
- - 'Quantum-Inspired Hamiltonian Descent for Mixed-Integer Quadratic Programming' accepted by the NeurIPS 2025 Workshop ScaleOPT: GPU-Accelerated and Scalable Optimization as a poster
Research Experience
- Currently a Simons Quantum Postdoctoral Fellow at the Simons Institute for the Theory of Computing at UC Berkeley, hosted by Umesh Vazirani and Lin Lin.
Education
- Ph.D. from the University of Maryland in 2024, advised by Xiaodi Wu.
Background
- Research interests lie at the intersection of machine learning and quantum computing. Designs quantum algorithms inspired by core principles in modern ML, such as optimization, sampling, and differentiable programming. Builds scalable and automated toolchains for their simulation and deployment on current and near-term quantum computers. Recently, also interested in quantum-inspired methods amenable to large-scale acceleration on today’s classical processors.
Miscellany
- On the job market in the academic year 2025-26.
