Dake Bu G X

卜大可・ウラナイタイカ

Phd Candidate, Department of Computer Science, City University of Hong Kong.

Hi! I’m currently a PhD candidate at Optima Group, Department of Computer Science, City University of Hong Kong, advised by Prof. Hau-San Wong and Prof. Qingfu Zhang since 2023 fall. I’m also fortunate to work closely with Prof. Wei Huang and Prof. Andi Han. Before that, I completed my B.S in 2023 in Mathematics at Xi’an Jiaotong University, advised by Prof. Hui Li and mentored by Prof. Jian Sun.

I’m currently an one-year intern at CFAR, A*STAR, where I’m supervised by Prof. Atsushi Nitanda. Prior to this, I spent one year (2024–2025) as a research intern at the University of Tokyo, working at the Deep Learning Theory Team at RIKEN AIP under the supervision of Prof. Taiji Suzuki. From May to June, 2026, I visited the School of Mathematics and Statistics at the University of Sydney as a visiting student, supervised by Prof. Andi Han. Earlier, from January to May 2023, I was a research assistant in the LOGO Lab at The Chinese University of Hong Kong, advised by Prof. Tianshu Yu.

My Research focuses on the theory and algorithms of large-scale machine learning systems, spanning emergent in-context learning, Agentic AI, LLM and diffusion post-training, reinforcement learning, and non-log concave sampling. My aim is to combine theory-grounded algorithm design and reproducible experiments to improve foundation-model training and inference.

News

2026-07 - Our github repo ABRL: A Target-Faithful Autoformalization Harness and Lean 4 Library for Bandit and Reinforcement Learning Theory and Auto-Sampling-Theory-In-Sleep: A Hierarchical Automated Theorem Proving System for Sampling Theory are available. Public lean libraries BanditRLlib and Samplinglib are welcoming contributors! The arXiv preparation is on the way. Please feel free to reach out and provide suggestions!
2026-06 - Attended the Annual Summer School on Mathematical Aspects of Data Science at the Institute for Mathematical Sciences, National University of Singapore.
2026-06 - Our github repo ASPBE:Automatic State Preparation and Block Encoding for Quantum Computing is available, along with public lean library QuantumComputinglib and user-facing website (Under Constuction). The arXiv version is comming soon. Any feedback is welcome!
2026-06 - Our paper on A Plug-in Doob h transform-induced Token-Ordering Module for Diffusion Language Models ([code]) is selected as Oral, and theoretical explanation and solution to exploration dilemma in LLM post-training ([code]) is rewarded as spotlight in ICML 2026 Fogen.
2026-05 to 2026-06 - Visited the School of Mathematics and Statistics at the University of Sydney as a visiting student, supervised by Prof. Andi Han.
2026-05 - Gave a talk titled “Langevin Dynamics with Partial Structure: From Guided Generative Sampling to Mean-Field Feature Learning” at the University of Sydney.
2026-05 - Presented A Plug-in Doob h transform-induced Token-Ordering Module for Diffusion Language Models ([code]) at the AIVP-Joint workshop between A*STAR, RIKEN AIP, and NTU at Nanyang Technological University.
2026-05 - Honor to win the Gold Reviewer Award in ICML 2026.
2026-05 - One paper on Provable benefit of transformer curriculum post-training ([code]) accepted to ICML 2026 ([code]).
2026-04 - Two papers on Slowly Annealed Langevin Dynamics ([code]) and A Plug-in Doob h transform-induced Token-Ordering Module for Diffusion Language Models ([code]) are available online.
2025-11 - One paper on Provable benefit of transformer curriculum post-training ([code]) is available on arXiv.
2025-01 — Two papers on theoretical foundation of task vector in In-Context Learning ([code]), and Multi-objective Reinforcement Learning with Lexicographic Rewards are accepted to ICML 2025.
2024-09 — One paper on In context learning with multi-concept word semantics ([code]) is accepted to NeurIPS 2024.
2024-01 — One paper on theoretical foundation of neural active learning ([code]) accepted to ICML 2024.

Education

Oct. 2023 – Present — PhD Candidate, Department of Computer Science, City University of Hong Kong (CityUHK).
Aug. 2019 – Jun. 2023 — School of Mathematics and Statistics, Xi’an Jiaotong University (XJTU).

Work Experience

Dec. 2025 - Present, - Research Intern, CFAR A*STAR
Dec. 2024 - Oct. 2023 - Research Intern, RIKEN AIP
Jan. 2023- May. 2023 - Research Assistant, The Chinese University of Hong Kong, Shenzhen

Service

Area Chair: ICML 2026 FOGEN; ICLR 2026 DeLTa.
Reviewer: ICML (2024; 2025; 2026); NeurIPS (2024; 2025; 2026); ICLR (2025; 2026).

Contact

Affiliation: Department of Computer Science, City University of Hong Kong
Location: Singapore; Hong Kong; Shenzhen
Email: <dakebu2-c[at]my.cityu[dot]edu[dot]hk>