Research Focus

• Designs formal verification methods for probabilistic programs and AI systems
• Develops safe reinforcement learning algorithms with provable correctness guarantees
• Builds certified learning frameworks for formal verification of machine learning models

Research Interests

Education

• PhD in Computer Science, Institute of Science and Technology Austria (ISTA), 2023
• MMath in Mathematics, University of Cambridge, 2018
• BA in Mathematics, University of Cambridge, 2018

Notable Awards

• Distinguished Tool Paper Award, ATVA 2025
• Distinguished Paper Award, FM 2024
• Outstanding PhD Thesis Award at ISTA, 2024

I am always happy to discuss potential topics that we could collaborate on, or to simply chat about research over a coffee. If any of the above topics sound interesting, please reach out.

Research Focus

• Renovates Bayesian inference procedures for auto-regressive models including LLMs
• Scales causal representation learning to large-scale generative AI models
• Develops scalable algorithms connecting statistical theory with practical ML systems

Research Interests

Education

• PhD in Engineering, University of Cambridge, UK, 2018
• BSc in Mathematics, Sun Yat-Sen University, China, 2013

Happy for chats regarding any topic within machine learning. I’d be happy to explore collaborations within the following topics: - Statistical machine learning - Generative modelling - Structured r...

Research Focus

• Develops spatial intelligence systems enabling machines to understand the 3D world
• Builds neural scene representations using NeRF and 3D Gaussian Splatting
• Designs vision-language-action models for embodied AI and robotics applications

Research Interests

Education

• PhD in Computer Vision, University of Adelaide, 2022
• BSc in Computer Science, Nankai University, 2016

Postdoctoral Experience

• Postdoctoral Researcher, Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), UAE, 2024–2025
• Postdoctoral Researcher, University of Oxford, UK, 2022–2024

I am keen to connect with colleagues whose work touches on world models, embodied AI, or vision-language-action models. This includes people working on robotics and manipulation, autonomous driving...

Research Focus

• Develops sampling methods for probability distributions in Bayesian inference
• Improves classical Monte Carlo techniques with modern generative modelling methods
• Studies particle filters and sequential Monte Carlo for state-space model inference

Research Interests

Education

• PhD in Applied Mathematics, ENSAE Paris, 2022
• MSc in Applied Mathematics, Ecole Polytechnique, 2019

Postdoctoral Experience

• Postdoctoral Research Fellow, Department of Statistics and Data Science, National University of Singapore (NUS), 2024–2025
• Postdoctoral Researcher, Department of Statistics, University of Oxford, UK, 2022–2024

I am actively looking for collaborators in MCMC, diffusion models, Bayesian computation, and inverse problems. Furthermore, I am interested in challenging high-dimensional sampling problems appeari...

Research Focus

• Designs efficient algorithms for statistical estimation with noisy or biased data
• Builds training frameworks for diffusion models using mixed-quality datasets
• Explores theoretical foundations for personalisation of large language models

Research Interests

Education

• PhD in Computer Science, University of California, Berkeley, 2021
• BTech & MTech in Engineering Physics
• Indian Institute of Technology (IIT) Bombay, 2015

Postdoctoral Experience

• Postdoctoral Associate, Massachusetts Institute of Technology (MIT)

I am excited to build collaborations with colleagues working across the theory and practice of machine learning and statistics. I am particularly interested in connections between statistical theor...

Research Focus

• Applies large language models to improve industry classification from text data
• Researches learning analytics and educational data mining using student artefacts
• Develops AI-enhanced feedback systems for computing and data science education

Research Interests

Education

• PhD in Information Systems & Analytics, National University of Singapore (expected 2026)
• MComp in Computer Science, National University of Singapore (NUS), 2019
• BEng (Computer Science) & Bus (Business), Nanyang Technological University (NTU), 2015

I’m keen to connect with and learn from colleagues interested in pedagogical research at the intersection of GenAI and CS/AI education. In particular, I hope to work on (1) learning analytics and e...

Research Focus

• Develops reinforcement learning algorithms for autonomous systems in multi-agent environments
• Builds multi-robot warehouse systems powered by multi-agent reinforcement learning
• Designs LLM-based multi-agent systems for human-AI workflow orchestration

Research Interests

Education

• PhD in Artificial Intelligence, University of Edinburgh, UK, 2015
• MSc in Artificial Intelligence, University of Edinburgh, UK, 2011
• BSc in Computer Science, Technical University of Darmstadt, Germany, 2010

Postdoctoral Experience

• Postdoctoral Fellow, University of Texas at Austin

I am excited to meet all my new colleagues and to explore shared interests! Please do get in touch and I would love to meet.

Research Focus

• Investigates algorithmic graph and hypergraph theory across all publications
• Studies subclasses of acyclic hypergraphs and union join graph computability
• Explores generative AI impacts on computer science education and pedagogy

Research Interests

Education

• PhD in Computer Science (Kent State University, USA, 2017
• MSc in Computer Science (University of Rostock, Germany, 2012

I left my previous teaching position in summer of 2022, before the AI boom. I therefore do not have first-hand experience of how AI affected teaching.