Sébastien Bubeck

Sébastien Bubeck is affiliated with Microsoft in the United States and has contributed extensively to the field of computer science, with a focus on artificial intelligence and related subfields. Their research encompasses a range of topics that include optimization and search problems, advanced bandit algorithms, complexity and algorithms in graphs, machine learning and algorithms, stochastic gradient optimization techniques, topic modeling, and adversarial robustness in machine learning.

Their recent papers demonstrate an active engagement with developments in artificial general intelligence and medical applications of AI. Among notable works are "Sparks of Artificial General Intelligence: Early experiments with GPT-4" published in 2023 in arXiv (Cornell University), "Benefits, Limits, and Risks of GPT-4 as an AI Chatbot for Medicine" from the same year appearing in the New England Journal of Medicine, "Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone" published in 2024 in arXiv (Cornell University), "Textbooks Are All You Need" from 2023 in arXiv (Cornell University), and "Textbooks Are All You Need II: phi-1.5 technical report" also in 2023 in arXiv (Cornell University).

• Mark Sellke
• Ronen Eldan
• Yuval Rabani
• Suriya Gunasekar
• Christian Coester

Bubeck's frequent coauthors include Mark Sellke, Ronen Eldan, Yuval Rabani, Suriya Gunasekar, and Christian Coester.

• arXiv (Cornell University)
• SIAM Journal on Computing
• New England Journal of Medicine
• Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
• Journal of the ACM

The main venues for their publications are arXiv (Cornell University), SIAM Journal on Computing, New England Journal of Medicine, Leibniz-Zentrum für Informatik (Schloss Dagstuhl), and the Journal of the ACM.

• Computer Science

Their primary field of study is Computer Science.

• Artificial Intelligence
• Management Science and Operations Research
• Computer Networks and Communications
• Computational Theory and Mathematics
• Computer Vision and Pattern Recognition

Within computer science, subfields addressed include Artificial Intelligence, Management Science and Operations Research, Computer Networks and Communications, Computational Theory and Mathematics, and Computer Vision and Pattern Recognition.

• Optimization and Search Problems
• Advanced Bandit Algorithms Research
• Complexity and Algorithms in Graphs
• Machine Learning and Algorithms
• Stochastic Gradient Optimization Techniques
• Topic Modeling
• Adversarial Robustness in Machine Learning

The scientist explores topics such as optimization and search problems, advanced bandit algorithms research, complexity and algorithms in graphs, machine learning and algorithms, stochastic gradient optimization techniques, topic modeling, and adversarial robustness in machine learning.

In 2015, Sébastien Bubeck was named a Fellow of the Alfred P. Sloan Foundation.