"Dynamical Transition in Training of Quantum Neural Network: from Optimization to Supervised Learning ", Invited talk at Beyond von-Neumann Computing: Leveraging Novel Physics for the Future of Computation, Aspen Center for Physics, USA (2025).
"Quantum-data-driven dynamical transition in quantum learning", APS Global Physics Summit 2025.
(Poster) "Dynamical transition in controllable quantum neural networks for supervised learning", 1st workshop on Advancing Quantum Computation Beyond Gate-Model (BGM 2024), University of Maryland, College Park. USA (2024).
"Generative quantum machine learning via denoising diffusion probabilistic models”, QAISG seminar (virtual), Singapore (2024).
"Dynamical phase transition in quantum neural networks with large depth", APS March Meeting 2024.
"Generative quantum machine learning via denoising diffusion probabilistic models", USC (2024).
"Entangling remote microwave quantum computers with hybrid entanglement swap and variational distillation", APS March Meeting 2023.
"Computational phase transition in Quantum Approximate Optimization Algorithm-the difference between hard and easy ", APS March Meeting 2022.
(Poster) "Fast suppression of classification error in variational quantum circuits", APS March Meeting 2022.
"Entanglement formation in continuous-variable random quantum networks", APS March Meeting 2021 (virtual).
Journals (alphabetical order): Communication Physics, Future Generation Computer Systems, npj Qunatum Information, The Journal of Chemical Physics.