About
Van Tien Nguyen
Quantum algorithms, optimization, and machine learning
I am a doctoral candidate in Electrical Engineering at The University of Texas at San Antonio. I develop and evaluate quantum and hybrid quantum–classical methods for learning and optimization.
About my work
I am interested in how quantum algorithms can address problems in optimization and machine learning, and how algorithm design shapes their performance. My work brings together variational quantum methods, structured learning models, and measurement-based approaches.
I work in the Machine Learning Optimization and Systems (MILOS) Lab, advised by Prof. Panagiotis P. Markopoulos. I combine mathematical analysis with simulations and quantum-hardware experiments to understand the capabilities and resource requirements of these methods.
Background
My background is in computer science and machine learning. I earned a B.S. (Honors) in Computer Science from Vietnam National University HCMC–University of Information Technology. Before beginning my Ph.D., I worked as a Research Engineer at Viettel High Technology Industries Corporation, developing natural-language-processing systems and supporting their deployment.
Teaching and community
I serve as a Graduate Teaching Assistant for EE 3233: System Programming for Engineers, helping students build their programming and problem-solving skills.
I also take part in the quantum-computing community as a Qiskit Advocate. I have supported the Qiskit Global Summer School as a mentor and am organizing Qiskit Fall Fest at UT San Antonio.
Outside research
I enjoy science fiction and detective stories, running, volleyball, and strength training.