My research interests focus on advancing the application and foundational frameworks of Quantum Information and Computation, with a particular emphasis on Quantum Machine Learning, Quantum Circuit Synthesis, and Quantum Communication Networks.
Currently, I am working on developing a novel framework for Quantum Federated Learning (QFL). My approach includes a loss-aggregation mechanism designed to overcome the challenges associated with non-IID (non-independent and identically distributed) data while significantly improving communication efficiency compared to existing QFL methods. Additionally, I am researching the qubit mapping problem, aiming to devise an effective heuristic algorithm for mapping logical qubits to physical qubits on quantum hardware. This research targets optimizing circuit operation time and minimizing circuit depth to enhance overall efficiency.
I am always open to collaboration opportunities, so feel free to reach out! 😃
Undergraduate Researcher | Nov 2023 - Present
Research on robot learning and artificial intelligence.
Undergraduate Researcher | Aug 2023 - Present
Research on speech processing and machine learning applications.
Research Intern | Jul 2023 - Oct 2023
Research internship at IIS, Academia Sinica.
Undergraduate Researcher | Feb 2022 - Jun 2023
First undergraduate research position focusing on wireless and mobile networking.