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Our Alumni

2 000+ graduates building a better science

Our alumni community spans 12 summer schools and includes students who have gone on to pursue graduate studies, research careers, and leadership roles at universities and institutions in Vietnam and around the world.

Alumni Stories

Dr. Nguyen Bao Huy

Dr. Nguyen Bao Huy

School Year 2013 • Lecturer, Hanoi University of Science and Technology

Dr. Nguyen Bao Huy received his PhD from the University of Lille (France) and the University of Sherbrooke (Canada) in 2019 and is currently a lecturer in the School of Electrical and Electronic Engineering at Hanoi University of Science and Technology. His research focuses on power electronics control and electric drives, with applications in electric and hybrid vehicles and power-electronics-dominated grids, and he has authored over 30 publications in leading international journals and conferences.

Nguyen Thi Phuong Nghi

Nguyen Thi Phuong Nghi

School Year 2018 • PhD Student at Stanford University

Nguyen Thi Phuong is a PhD candidate in Bioengineering at Stanford University, with a Chevening Scholarship–funded Master’s degree in Therapeutic Sciences from the University of Cambridge. Her research focuses on biomaterials, tissue engineering, and cell-based therapies, and she has authored publications in international scientific journals while holding an academic position at the International University, Vietnam National University Ho Chi Minh City. She was a participant of Vietnam Summer School of Science 2018.

Dr. Phuong Dao

Dr. Phuong Dao

School Year 2013 • Assistant Professor at The University of Texas at Austin

Dr. Phuong Dao is an Assistant Professor at The University of Texas at Austin and Principal Investigator of the Remote Sensing and Environmental Intelligence Lab (ReSEIL), specializing in remote sensing, geospatial science, and plant ecology. He holds a dual PhD in Physical Geography and Environmental Studies from the University of Toronto (Connaught International Fellowship), with research integrating remote sensing, molecular methods, and machine learning to understand plant health and disturbance dynamics.