👋 Hello there!

About Me:

👦 Name:
      🅰️ First Name: Hong Kiat,
      🅱️ Last Name: Tan,
      🆎 Listed Name: Hong Kiat Tan.
      🍵 “Drinks/US” Name: Max.
      👨‍👨‍👦‍👦 Pronouns: He/Him/His.

👨‍🎓 I’m a final-year Ph.D. student in Mathematics at UCLA, advised by Andrea Bertozzi.

📚 I did my undergraduate studies at the National University of Singapore majoring/minoring in:
      📗 Primary Major: Applied Mathematics,
      📕 Secondary Major: Physics,
      📘 Minor: Statistics.

Research Experiences & Interests:

My research interests have always been driven by following interesting problems that combine deep mathematical theory with real-world applications. My current research interests include:

📊 Machine Learning/Deep Learning/Statistics:

• LLMs (Mechanistic Interpretability, AI Safety, Agentic Systems, RL),
• Causal Inference/Causal Machine Learning/Causality, and
• Mathematical/High-dimensional/Applied Statistics.

Differential Topology and Geometry:

• Genericity & Transversality + Applications (to math/data science/machine learning).
• Riemannian & Neural Geometry + Applications (to mechanistic interpretability/AI safety/alignemnt).

These have evolved from earlier work as a graduate and an undergraduate student, where I have worked on projects involving:

• Hyperbolic PDEs and conservation laws,
• Mathematical general relativity,
• Bayesian modeling in nuclear astrophysics, and
• Numerical methods in quantum field theory.

Throughout, I think of myself as a “full stack mathematician” — I take projects end-to-end, from theory and modeling through implementation and simulation to production-scale systems whenever possible!

✉️ I am always happy to discuss the projects/publications I have worked on in more detail. If you have any questions with regard to any of my publications, feel free to contact me via my email below!

CV:

📃 You can access my resume/CV here. (Updated Aug 2026.)

I’m currently working as an Applied Scientist Intern at Amazon (Summer 2026)!

☕ I am currently located in SF/Bay Area this summer, so feel free to reach out for a coffee chat!

I’m mentoring for two SPAR projects with David Williams-King and Linh Le in Fall 2026! Project details:

• Interpretability Techniques for Scheming and
• Interpretability Techniques for Unspoken Collusion.

I worked as a Research Fellow with SPAR on a mechanistic interpretability project. (Spring 2026)

I worked as a Quantitative Research Intern at WorldQuant on their Intraday team (Fall 2025).

I worked as a Data Scientist Intern at Amazon on the Search Data Science and Economics team (Summer 2025).

💼 I am currently looking for a full-time early career/new grad role as a/an:

• Research/Applied/Data Scientist/Member of Technical Staff,
• Research/Machine Learning/AI Engineer, and/or
• Research Fellow.

Feel free to contact me via my email below!

Teaching:

🧑‍💻 Teaching Experiences:

• You can access them here.

Contact Me:

📩 maxtanhk@math.ucla.edu
🏢 MS6161