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Research Scientist at OpenAI
I am a research scientist at OpenAI. My research focuses on developing and scaling up algorithms and methods for improving LLM's ability to interact with and reason about the world. I am currently most excited about RL as the next big avenue for significant improvements in LLMs. Previously, I was part of the Program Synthesis team where I focused on LLMs for code. Before OpenAI, I graduated with a PhD from the computational and biological learning group at the University of Cambridge, where I was supervised by Drs. Miguel Hernandez Lobato and Richard Turner. My research there focused on combining deep learning with probabilistic latent variable models.
University of Cambridge
Master’s Degree, Machine Learning, Speech and Language Technologies
January 1, 2016 – January 1, 2017
Ben-Gurion University of the Negev
Master's Degree, Engineering/Industrial Management
January 1, 2014 – January 1, 2016
Ben-Gurion University of the Negev
Bachelor of Engineering (BEng), Industrial Engineering
January 1, 2011 – January 1, 2015
OpenAI
Research Scientist
December 1, 2020 – Present
San Francisco Bay Area
Facebook AI
Research Intern
July 1, 2019 – October 1, 2019
Greater Paris Metropolitan Region
Microsoft
Research Internship
June 1, 2018 – September 1, 2018
Greater Boston
University of Cambridge
PHD Student in Machine Learning
September 1, 2017 – February 1, 2021
Greater Cambridge Area
Coursera Machine Learning Course
Coursera Course Certificates
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's extensive research background at academic institutions and leading AI companies (OpenAI, Facebook AI, Microsoft) indicates a strong fit for innovation-driven, research-intensive environments. However, the target role is 'Data Analyst', which may not fully align with a pure research profile. The lack of explicit project details makes it difficult to assess practical application of skills in a typical data analyst context. The candidate's profile suggests a strong academic and research culture fit, but a potential mismatch with a more operational data analyst role.
Soft Skills & Operational Fit
The candidate's background in research at top-tier organizations suggests strong problem-solving, analytical thinking, and independent work capabilities. However, the provided data does not offer specific insights into communication, teamwork, or stress handling beyond the general nature of research roles.