Xuan (Tan Zhi Xuan)

I am an Assistant Professor in the National University of Singapore’s Department of Computer Science with a joint appointment at the A*STAR Institute of Advanced Intelligence & Computing (IAIC).

I run the Cooperative Intelligence & Systems (CoSI) lab, which is focused on scaling cooperative intelligence via rational, model-based AI engineering.

Previously, I completed my PhD in the the MIT Probabilistic Computing Project and Computational Cognitive Science lab, advised by Vikash Mansinghka and Josh Tenenbaum.

I publish under the name “Tan Zhi-Xuan”. This means an APA citation should look like (Zhi-Xuan, YYYY). “Tan” is my surname (transliterated from Hokkien), “Zhi Xuan” is my given name (in Mandarin / pinyin), and “Xuan” (pronounced ɕɥɛn / sh-yen) is the name I usually go by. I use they/them or she/her pronouns.

research interests

My research on cooperative intelligence sits at the intersection of Bayesian modeling, AI alignment, and cognitive science, asking questions like:

• How can we specify rich yet structured generative models of human reasoning, decision-making, and value formation?^1,2,3,4,5
• How can we efficiently perform Bayesian inference over such models, in order to accurately learn human goals^1,6,7, values, and norms^4,8?
• How can we reverse engineer the computational foundations of human cooperation and human normativity^4,8?
• How can we engineer AI systems using these foundations, so that that act reliably in accordance with human goals³ and norms⁴?

To answer these questions, my work includes the development of infrastructure for probabilistic programming^9,10 and model-based planning^11,12, so as to enable fast and flexible Bayesian inference over complex models of agents and their environments. By developing engineering platforms for more auditable AI systems with stronger algorithmic guarantees, I hope to support the growth of well-founded and human-compatible AI.

I see the ultimate goal of this research as steering the development and deployment of AI towards beneficial and equitable outcomes for all, despite our plural and often divergent values. For more on my views regarding AI alignment, safety, and the importance of cooperation in an increasingly automated future, see my talks and interviews on scaling cooperative intelligence and the limitations of preference-based alignment. I also serve in advisory role to several AI alignment non-profits (PIBBSS; Meaning Alignment Institute), and as an editorial board member for the magazine Pax Machina.

mentoring & teaching

If you are interested in working with me, please see my recruiting page!

I am fortunate to work with an amazing group of researchers, who collectively form the Cooperative Intelligence & Systems (CoSI). See our lab’s people page for more information about them! I also sometimes serve as a mentor for the PIBBSS Summer Fellowship.

Since Fall 2025, I have been teaching a graduate seminar on Rational Approaches to Cooperative Intelligence. This seminar’s format is inspried greatly by the time I was a teaching assistant for the Spring 2022 graduate seminar on Bayesian Modeling and Inference taught by Tamara Broderick.

I am committed to promoting diversity, equity, inclusion, and justice (DEIJ) in computer science. To that end, I have been an organizer for groups such as Julia Gender Inclusive. If you are an underrepresented student in computer science looking for support or advice, feel free to reach out!