| Aug 01, 2026 | I’m excited to share that our team, Artephi Computing, has been selected as a Stage 2 Milestone 1 winner of the NIH Quantum Computing Challenge, with an award of up to $150,000 to advance our work toward implementation on quantum hardware! |
| May 03, 2026 | I am going to attend the workshop “Beyond Gate-Based Quantum Computing” at the Kavli Institute for Theoretical Physics in UCSB. I will give a talk on some new progress on super-polynomial quantum speedups for optimization. Please let me know if you want to catch up! |
| Apr 24, 2026 | Our paper “Accelerating quantum Gibbs sampling without quantum walks” has been posted on arXiv. Check it now! |
| Mar 17, 2026 | Our paper “Towards End-to-End Quantum Estimation of Non-Hermitian Pseudospectra” has been posted on arXiv. Check it now! |
| Mar 15, 2026 | I am going to attend the APS March Meeting in Denver and give a talk titled “Resource-efficient quantum simulation of transport phenomena via Hamiltonian embedding”. I will also chair the session “Digital Quantum Simulation IV: Applications and Methods”. Please let me know if you want to catch up! |
| Dec 30, 2025 | Our paper “Operator-Level Quantum Acceleration of Non-Logconcave Sampling” has been accepted by PNAS. Many thanks to my collaborators: Zhiyan Ding, Zherui Chen, and Lin Lin! |
| Nov 08, 2025 | AWS Quantum Technologies Blog features our work on near-term quantum simulation of high-dimensional dynamics (via Hamiltonian embedding). Check it out! |
| Oct 27, 2025 | I will give a talk about quantum-accelerated algorithms for (classical) Gibbs sampling at the 2025 INFORMS Annual meeting (INFORMS 25), in Session MC02 “Advances in Quantum Computing Optimization” (10/27, 2:00 - 2:15 pm, Building A Level 3 A302). |
| Oct 24, 2025 | I am invited to give a 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. Check the talk details here. |
| Sep 21, 2025 | Our submission “Quantum-Inspired Hamiltonian Descent for Mixed-Integer Quadratic Programming” has been accepted by the NeurIPS 2025 Workshop ScaleOPT: GPU-Accelerated and Scalable Optimization as a poster. |
| Sep 03, 2025 | My collaborators (Yuxiang Peng, Lei Fan, and Xiaodi Wu) and I organize a tutorial titled “Step-by-Step Guide to Solving Nonlinear Optimization with Quantum Computers” at the IEEE Quantum Week (QCE25). Check it out if you are attending! |
| Jul 24, 2025 | I chair a session “Quantum Methods for Optimization and Sampling” at the International Conference on Continuous Optimization (ICCOPT 2025), in which I also give a talk on a new quantum algorithm for Gibbs sampling with continuous potentials. |
| May 20, 2025 | Our paper “Quantum Optimization via Gradient-Based Hamiltonian Descent” has been posted on arXiv. Check it now! |
| May 14, 2025 | I am invited to speak in a minisymposium on “Dynamical Systems for Machine Learning” in SIAM Conference on Applications of Dynamical Systems (DS25), organized by Yuqing Wang, Boumediene Hamzi, and Molei Tao. |
| May 08, 2025 | Our paper “Operator-Level Quantum Acceleration of Non-Logconcave Sampling” has been posted on arXiv. Check it now! |
| Apr 21, 2025 | Our paper “(Sub)Exponential Quantum Speedup for Optimization” has been posted on arXiv. Check it now! |
| Oct 22, 2024 | I am thrilled to chair a session “Advancements in Quantum Computing and Collaboration” at the 2024 INFORMS Annual Meeting (INFORMS 2024), in which I also give a talk on quantum-inspired algorithms for nonlinear programming. |
| Oct 08, 2024 | I’m invited to give a talk at the 1st workshop on Advancing Quantum Computing Beyond Gate-Model (BGM2024), hosted by QuICS. Here is the link to my talk. |
| Aug 14, 2024 | I’m invited to give a talk on quantum algorithms for optimal control at Modeling and Optimization: Theory and Applications (MOPTA 24) conference, hosted by the Department of Industrial and Systems Engineering (ISE) at Lehigh University. |
| Jul 01, 2024 | I am thrilled to join UC Berkeley as a postdoctoral researcher at the Simons Institute for the Theory of Computing! |
| Apr 04, 2024 | I defended my Ph.D. dissertation. Details of my defense can be found here. |
| Mar 22, 2024 | I’m invited to give a talk about quantum algorithms for nonconvex optimization at the 2024 INFORMS Optimization Society Conference (IOS 24). |
| Mar 01, 2024 | I’m invited to visit the Institute for Quantum Information and Matter (IQIM) at Caltech and give a talk at the IQIM seminar. |
| Jan 16, 2024 | Our paper “Expanding hardware-efficiently manipulable Hilbert space via Hamiltonian embedding” has been posted on arXiv. Check it now! |
| Sep 10, 2023 | I am a long-term core participant at Program on Mathematical and Computational Challenges in Quantum Computing, hosted by IPAM at UCLA (end of visit: December 15, 2023). |
| Jun 27, 2023 | I am excited to receive the Unitary Fund microgrant (co-PI: Yuxiang Peng) to build an open-source software package QHDOPT for nonlinear optimization. Quantum Hamiltonian Descent (QHD) is a quantum algorithm for continuous optimization. QHD can be implemented on spin-glass simulators (e.g., D-Wave) and demonstrates a significant advantage for solving non-convex problems. QHD can also be readily integrated into a branch-and-bound framework and leads to powerful commercial solvers. Despite the significant interest from the operations research community, implementing QHD on quantum hardware remains challenging for researchers without systematic training in quantum computing. We propose to develop QHDOPT, an end-to-end QHD-based nonlinear programming OPTimizer that eliminates the technical barrier of using QHD for the broader scientific computing community. In the ecosystem, only a few projects (e.g., ToQUBO.jl) target nonlinear optimization by directly reducing continuous problems to discrete ones regardless of the continuity structure. To our best knowledge, QHDOPT will be the first of this kind in the field. |