About me: Hello world! I am Quan Pham. I am an undergrad at HUST, Vietnam, and also an AI Resident at Qualcomm AI Research. I am an incomming PhD student at National University of Singapore (NUS). I was mentored by Prof. Trung Le (previously at VinAI Research), and I currently work closely with Dr. Tung Pham and Dr. Hung Bui at Qualcomm AI Research.

I like to play with large language models, then ask why they work. I am especially interested in the theory behind LLM abilities: what principles explain the behaviors we observe, and how we can make them more reliable.

Outside of research, I love traveling to collect new experiences (and photos) as my little way to “save” memories. You can take a look at my blog

Updates

• [Feb 2026] I received an offer of admission and a research scholarship from the National University of Singapore (NUS).

• [Dec 2025] I am actively looking for a PhD position. Good luck to me!

• [Jun 2025] I will attend ICML 2025. Let’s connect!

• [May 2025] I got 2 papers accepted at ICML 2025.

• [Apr 2025] I officialy joined Qualcomm AI Research as an AI Resident.

• [Dec 2024] I achieved an IELTS Academic band score of 7.0!

• [Aug 2024] I joined VinAI Research as an AI Resident.

• [Apr 2024] My first paper was accepted at ICASSP 2024.

Research Interests

My research lies at the intersection of statistical machine learning, large language models (LLMs), and efficient inference. I am interested in developing principled foundations for understanding how overparameterized models learn, generalize, and reason, and in translating these insights into robust and efficient AI systems.

A central theme of my work is to bridge statistical theory and modern foundation models. In particular, I focus on:

• Developing probabilistic inference methods for foundation models, with an emphasis on improving reasoning capabilities in LLMs.
• Advancing scientific understanding of LLMs by investigating the fundamental statistical properties that govern how models learn and reason.