1. Publications: Multiple papers published in top conferences and journals such as ICML, ICLR, NeurIPS, covering areas like probabilistic inference, density ratio estimation, high-frequency function learning, etc. 2. Project Contributions: Involved in several research projects such as Dr. SoW, LAB, InstructLab CLI, etc.
Research Experience
1. Research Scientist at the Red Hat AI Innovation Team and MIT-IBM Watson AI Lab. 2. Original member of the TuringLang team, working on building the Turing probabilistic programming language in Julia. 3. Led the initial development of the InstructLab CLI in the open-source LLM project InstructLab. 4. Worked at Hazy, a startup on synthetic data generation, for 9 months after his PhD.
Education
PhD: Institute for Adaptive and Neural Computation, University of Edinburgh, Advisor: Charles Sutton; Master's: Cambridge Machine Learning Group, University of Cambridge, Advisor: Zoubin Ghahramani.
Background
Research Interests: Practical probabilistic methods, learning, inference, and alignment methods for deep probabilistic models and their real-world applications. Professional Field: Machine Learning, Probabilistic Programming Languages. Brief Introduction: Research scientist at the Red Hat AI Innovation Team and MIT-IBM Watson AI Lab, original member of the TuringLang team, involved in the open-source LLM project InstructLab.