Nguyen Nam Hai, born in 2003, graduated with Distinction in Data Science and AI from Hanoi University of Science and Technology (HUST).

He first learned about AI from a chemistry teacher in 11th grade, and in 12th grade chose HUST’s Data Science and AI program because it matched his strengths in mathematics and programming.

At university Hai spent many hours on math and programming courses, supplementing lectures with YouTube videos, books and online problem sets, which helped him consistently earn A or A+ grades.

In his second year he joined an AI research lab under Dr. Ngo Van Linh and Assoc. Prof. Than Quang Khoat, where he regularly read scientific papers and re‑implemented their algorithms.

During his third year Hai worked part‑time at VinAI Research, noticing the gap between classroom theory and real‑world AI research and keeping up with rapid advances in the field.

After his first conference paper was rejected, Hai felt sad and stressed, wondering if research was right for him. He said, “I was quite sad and stressed, even wondering whether I am truly suited for a research path.”

Instead of quitting, he and his collaborators revised the work, resubmitted it, and the paper was later selected as a spotlight paper at the conference. Hai explained that rejection is normal and that controlling emotions and learning from mistakes are key.

By the end of his undergraduate studies Hai co‑authored three papers as co‑first author at the top AI conferences ICLR and ICML, giving him valuable publication experience.

In late 2025 Hai prepared his study‑abroad portfolio and completed multiple interview rounds with U.S. universities. By February 2026 he received acceptance letters from nine PhD programs, including Cornell, Virginia Tech, Vanderbilt, Rice, Northeastern, NYU, UT Austin, Johns Hopkins and UC San Diego.

He was awarded honor scholarships from Cornell, Vanderbilt and Northeastern for his achievements.

Hai chose Cornell, which offered a financial support package worth $432,895 over five years, covering tuition, health insurance and a living stipend. He is now a first‑year PhD candidate focusing on AI interpretability.