Hi! I’m a 5th year PhD candidate in Economics at MIT. I was previously at Oxford where I did my masters in Maths, and at Cambridge where I did my undergrad in Economics, graduating first in cohort. Here is a CV.

I work on game theory and economic theory. I’m interested in information, learning, and beliefs + how they interact with more ‘non-standard’ aspects e.g., desire, attention, and memory. I’m motivated by applications to the economics of technology — I’d like to better understand incentives to develop new technologies, how these technologies shape welfare, and how we should regulate them. On the side I enjoy writing, pottery, and philosophy; I grew up in Singapore.

I’m on the job market this fall (2025/26).

Job Market Paper

  1. ‘Robust Technology Regulation’
    (with Sivakorn Sanguanmoo; latest draft: Oct 25)
    [pdf] [ssrn]
    Talks: AEA 2025 (‘Policy Implications of Transformative AI’ session), SITE 2025 (‘Dynamic Games’), JHU

    • Adaptive sandboxes for risky technologies are (i) robust when the firm’s learning process is chosen adversarially; (ii) dominant among robust mechanisms; and (iii) uniquely time-consistent among robust mechanisms. Robustness is important, without which society’s payoff can be unboundedly poor.

Journal publications

  1. ‘Capability Accumulation and Conglomeratization in the Information Age’
    Journal of Economic Theory 210 (2023): 105647.
    (with Jun Chen & Matt Elliott)
    [pdf] [link]

    • A Simple explanation for why tech firms have expanded so quickly, into so many new industries.

Under revision

  1. ‘Attention Capture’
    (with Sivakorn Sanguanmoo; latest draft: Sep 24)
    [pdf] [ssrn] [arxiv]
    Revise & resubmit, Journal of Political Economy
    Talks: AEA 2025 meeting session on “Attention and Engagement on Platforms”, National University of Singapore, Singapore Management University

    • Unified analysis of how information captures attention.

  2. ‘Market Segmentation through Information’
    (with Matt Elliott, Andrea Galeotti, & Wenhao Li; latest draft: Feb 25)
    [pdf]
    Revise & resubmit, The Review of Economic Studies

    • Information is a powerful tool for shaping price competition + characterization of all outcomes when a platform controls both access and information.

  3. `An Economy of AI Agents’ (with Gillian Hadfield)
    [arxiv]
    Prepared for the NBER Handbook on the Economics of Transformative AI

    • Survey of recent developments and highlights open questions around how AI agents might interact with each other, shape markets and organizations, and attendant implications for policy.

Working Papers (by last update)

  1. `Balanced Social Learning’ — new!!!
    (with Ricky Li; latest draft: Oct 25)
    [pdf]

    • Tradeoff between speed (learning quickly) and breadth (learning broadly) + complete characterization of when and how balanced learning (= efficiency) is achieved.

  2. `Prices and Symmetries’ — new!!!
    (with Pedro Martinez-Bruera; latest draft: Sep 25)
    [pdf] [ssrn]
    Talks: Network Science in Econ (Stanford)
    • Price interventions dominate quantities when shocks to the network are sufficiently symmetric because the ensuing equilibrium adjusts toward the first-best allocation; vice versa for antisymmetric shocks. Flexible instruments can restore the first-best allocation network-by-network.

  3. `Memory Correlated Equilibrium’ (with Sivakorn Sanguanmoo) — new!!!
    write us for a draft!

    • A framework for modeling (equilibrium concepts & existence) and designing (revelation principle) correlated memory in extensive-form games. Applications to algorithmic cooperation, pricing, coordination.

  4. `Data-Driven Automation' (with Maryam Farboodi and Anchi Xia) — new!!!
    write us for a draft!
    • We analyze data-automation feedback loops: better data drives automation (via reinforcement learning) and better automation drives data accumulation (via equilibrium quantities). Global spillovers (via general equilibrium) and local spillovers (via transfer learning across similar tasks) drive the speed, direction, and limit of automation.

  5. `Flexible Demand Manipulation’
    (with Yifan Dai; draft date: June 25)
    Talks: 2024 Berkeley/Columbia/Duke/MIT/Northwestern IO Theory Conference
    [pdf] [ssrn] [arxiv]

    • How do new persuasive/manipulative technologies (AI, rec systems, …) interact with market power?

  6. `Inertial Coordination Games’
    Extended abstract in 26th ACM Conference on Economics and Computation [EC’25]
    (with Ricky Li & Kei Uzui; draft date: March 25)
    [pdf] [arxiv]

    • Learning speeds determine whether shocks persist vs fizzle out: risk dominance iff posterior precisions grow sub-quadratically; otherwise shocks can propagate and generate self-fulfilling spirals.

  7. `Informational Puts’
    Extended abstract in 25th ACM Conference on Economics and Computation [EC’24] (titled ‘Full Dynamic Implementation’)
    (with Sivakorn Sanguanmoo & Kei Uzui; latest draft: Dec 24)
    [pdf] [arxiv] [ssrn]
    Talks: Nuffield Oxford, Cambridge, EC’24, various Econometric Society meetings

    • How to achieve full implementation in dynamic supermodular games?

  8. ‘Delaying the Deviation’ (with Anna Merotto)
    write us for a draft!

    • Randomizing small transfers across agents and across time (i) uniquely implements regime survival even when attacking is both payoff- and risk-dominant; and (ii) is sequentially optimal. Both kinds of randomization are necessary.

  9. `Persuasion and Optimal Stopping’
    (with Sivakorn Sanguanmoo & Weijie Zhong; latest draft: Dec 24)
    [pdf]
    Talks: Harvard EconCS seminar, SITE 2024 (dynamic games)

    • Unified analysis of optimal dynamic persuasion to implement joint distributions over actions, states, and stopping times. No intertemporal commitment is necessary.

  10. ‘Speed vs Resilience in Contagion’
    To be incorporated into a new paper `    Contagion over Time and Space’ with sparse continuous graphs and heterogeneous thresholds!
    (with Stephen Morris; draft date: Dec 22)
    [pdf] [ssrn] [slides]

    • Threshold contagion is faster in networks where it is harder to initiate contagion. Intermediate links are important bulwarks against contagion.