Ran Raz is a researcher affiliated with Princeton University in the United States. Their work is primarily situated within the field of Computer Science, with a focus on subfields such as Artificial Intelligence, Computational Theory and Mathematics, Information Systems, Computer Networks and Communications, and Atomic and Molecular Physics, and Optics.
Their main research themes encompass Complexity and Algorithms in Graphs, Quantum Computing Algorithms and Architecture, Computability, Logic, AI Algorithms, Cryptography and Data Security, Quantum Information and Cryptography, Machine Learning and Algorithms, and Blockchain Technology Applications and Security.
Several frequent collaborators have contributed to their research, including Uma Girish, Wei Zhan, Yael Tauman Kalai, Kunal Mittal, and Justin Holmgren.
Ran Raz has published in various scientific venues, with a notable presence in arXiv (Cornell University) and Leibniz-Zentrum für Informatik (Schloss Dagstuhl). Other significant publication venues include Journal of the ACM, COMBINATORICA, and Computational Complexity.
Recent papers by Ran Raz include:
Additional coauthor-related papers relevant to the context include works by Yael Tauman Kalai and Uma Girish published in venues such as the Journal of the ACM, COMBINATORICA, and Leibniz-Zentrum für Informatik (Schloss Dagstuhl).
Ran Raz;Shmuel Safra
Ran Raz
Cyril Gavoille;David Peleg;Stéphane Pérennes;Ran Raz
Ran Raz;Pierre McKenzie
Maria Luisa Bonet;Toniann Pitassi;Ran Raz
I. Dinur;G. Kindler;R. Raz;S. Safra
Ran Raz
Ran Raz;Omer Reingold;Salil Vadhan
Ran Raz
Ran Raz
Dmitry Gavinsky;Julia Kempe;Iordanis Kerenidis;Ran Raz
Ran Raz;Avi Wigderson
Dana Moshkovitz;Ran Raz
Ran Raz
Ran Raz;Avishay Tal
Yevgeniy Dodis;Ariel Elbaz;Roberto Oliveira;Ran Raz
Ariel Gabizon;Ran Raz
Ran Raz;Amir Shpilka
Kai-Min Chung;Yael Tauman Kalai;Feng-Hao Liu;Ran Raz
Ran Raz;Amir Yehudayoff
Dmitry Gavinsky;Julia Kempe;Iordanis Kerenidis;Ran Raz
Dana Moshkovitz;Ran Raz
If you think any of the details on this page are incorrect, let us know.
As you consider studying Computer Science in the USA, it’s worth exploring flexible online degrees that can boost your skills and open new career paths. Many professionals advance quickly by enrolling in online MBA programs, which combine tech expertise with essential business management skills.
For those aiming to earn a credential rapidly, there are excellent 1 year master's programs available online, allowing you to specialize in areas like data science, information technology, or cybersecurity without a lengthy time commitment.
If your goal is to enter the workforce fast, you might look into short careers that pay well. These programs offer targeted training for high-demand roles in tech and related fields, helping you start your career sooner.
Finally, with AI revolutionizing the industry, pursuing an ai degrees online is a strategic move. These specialized programs prepare you for roles in machine learning, automation, and big data.
University of Southampton
Université Paris Cité
National Institute for Astrophysics
Umeå University
University of Massachusetts Amherst
Brookhaven National Laboratory
National Institutes of Health
Konkuk University
University of Pennsylvania
Arizona State University
University of Toronto
Université Paris Cité
University Health Network
Lund University
Cooper University Hospital
Toyota Motor Corporation (Japan)
