The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Elad Hazan sits on this spectrum.
This scientist: 191 publications — 43rd percentile
43% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 991 publications or more.
The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Elad Hazan sits on this spectrum.
This scientist: 60 D-Index — 78th percentile
78% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
Elad Hazan is a researcher affiliated with Princeton University in the United States. Their primary fields of study include Computer Science, Engineering, and Decision Sciences, with a significant focus on several subfields such as Artificial Intelligence, Management Science and Operations Research, Control and Systems Engineering, Computational Mechanics, and Computer Networks and Communications.
The main topics that characterize Hazan's body of research comprise Advanced Bandit Algorithms Research, Stochastic Gradient Optimization Techniques, Sparse and Compressive Sensing Techniques, Reinforcement Learning in Robotics, Advanced Control Systems Optimization, Machine Learning and Algorithms, and Respiratory Support and Mechanisms.
Hazan has contributed extensively to the academic literature, with frequent publications appearing predominantly in arXiv (Cornell University), accounting for 48 papers. Other venues include bioRxiv (Cold Spring Harbor Laboratory) and Quantum, with one publication each in these venues.
Among recent papers authored or co-authored by Hazan are:
Frequent collaborators in Hazan's research projects include the following individuals:
Hazan's work intersects multiple areas of advanced computational research, focusing on algorithm development and optimization techniques relevant to control systems and machine learning. Projects involving reinforcement learning, sparse sensing methods, and optimization in dynamic and uncertain environments are central themes in their research portfolio.
John Duchi;Elad Hazan;Yoram Singer
Elad Hazan
Elad Hazan;Amit Agarwal;Satyen Kale
Sanjeev Arora;Elad Hazan;Satyen Kale
Jacob D Abernethy;Elad Hazan;Alexander Rakhlin
Zeyuan Allen-Zhu;Elad Hazan
Sanjeev Arora;Nadav Cohen;Elad Hazan
Elad Hazan;Adam Kalai;Satyen Kale;Amit Agarwal
Amit Agarwal;Elad Hazan;Satyen Kale;Robert E. Schapire
Elad Hazan;Satyen Kale
Elad Hazan;Alexander Rakhlin;Peter L. Bartlett
Elad Hazan;Shmuel Safra;Oded Schwartz
Naman Agarwal;Zeyuan Allen-Zhu;Brian Bullins;Elad Hazan
Elad Hazan
Elad Hazan;Satyen Kale
Elad Hazan;C. Seshadhri
Dan Garber;Elad Hazan
S. Arora;E. Hazan;S. Kale
Elad Hazan;Robert Krauthgamer
Elad Hazan;Satyen Kale
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