Joshua Ong

PhD Student @ Imperial College London.

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I am a second-year PhD student at Imperial College London and a 2026 Google PhD Fellow, fortunate to be advised by Eleonora Giunchiglia, Shay Cohen and Wenda Li. I am also a visiting researcher at the Institute of Foundation Models, part of the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI). Prior to joining Imperial College London, I was a visiting researcher at the University of Edinburgh, where I obtained my BSc in Mathematics and Statistics.

My research focuses on Large Language Model (LLM) Reasoning and theorem proving, with a particular interest in understanding and improving the mathematical reasoning capabilities of LLMs. Currently, my interests lie in generating verifiable synthetic data for LLMs [1], and training reasoning models for both formal and informal mathematics [2]. I am also part of the AI for Math Grant, where our main focus lies in advancing theorem proving autoformalisation within LLMs.

I am actively looking for internship opportunities for 2027. Feel free to reach out to me if there are any interesting or suitable positions!

news

Nov 13, 2026 Honoured to announce that I have been awarded the 2026 Google PhD Fellowship (Natural Language Processing Track). A huge thanks to Google, and my amazing supervisors who supported me throughout my research 💙
Oct 28, 2026 We are proud to announce that Pythagoras-Prover: Advancing Efficient Formal Proving via Augmented Lean Formalisation has been awarded the Best Paper Award at the EMNLP MathNLP Workshop 🎉. Here are the slides for the presentation [slides].
Oct 21, 2026 AoA: Theorem Proving Agent over Abstract Syntax Tree of Redesigned Language has been accepted at ICSE 2026.
Oct 10, 2026 I will be attending EMNLP 2026 in Budapest, presenting Pythagoras-Prover: Advancing Efficient Formal Proving via Augmented Lean Formalisation🔥. Feel free to reach out if you’d like to meet or discuss interesting topics!
Sep 25, 2026 SCOPE: Self-Play via Co-Evolving Policies for Open-Ended Tasks has been accepted at NeurIPS 2026.
Sep 11, 2026 🚀🚀🚀 We are pleased to release Magenta, an end-to-end formal-informal self-correction pipeline that achieves 100% mathematical benchmarks, marking the first time a fully open-source model has achieved a perfect score. In addition, when using a 7B model for informal reasoning, the pipeline achieved a perfect score on IMO 2026, making it the smallest model to date to do so. For more details, please see our recent work, Magenta: Closing the Loop Between Mathematical Reasoning and Lean Verification🔥.
Jun 12, 2026 🚀🚀🚀 We are pleased to release Pythagoras-Prover, a family of theorem-proving models (4B and 32B). It includes the smallest model to date for theorem proving (4B), as well as the first diffusion-based model capable of theorem proving. For more details, please see our recent work, Pythagoras-Prover: Advancing Efficient Formal Proving via Augmented Lean Formalisation🔥.
Jun 01, 2026 I will be attending ICML 2026 in Seoul 🇰🇷. Feel free to reach out if you’d like to meet or discuss interesting topics!
May 01, 2026 Can I Have Your Order? Monte-Carlo Tree Search for Slot Filling Ordering in Diffusion Language Models has been accepted at ICML 2026.
Apr 07, 2026 PiCSAR: Probabilistic Confidence Selection And Ranking for Reasoning Chains has been accepted at ACL 2026 (Findings).