The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Assaf Zeevi sits on this spectrum.
This scientist: 105 publications — 13th percentile
13% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 537 publications or more.
The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Assaf Zeevi sits on this spectrum.
This scientist: 41 D-Index — 49th percentile
49% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 86 D-Index or more.
Assaf Zeevi is affiliated with Columbia University in the United States. Their primary fields of study include Decision Sciences and Computer Science, with a focus on several specialized subfields such as Management Science and Operations Research, Artificial Intelligence, Computer Networks and Communications, Management Information Systems, and Marketing.
The main topics covered in their research encompass Advanced Bandit Algorithms Research, Auction Theory and Applications, Optimization and Search Problems, Machine Learning and Algorithms, Reinforcement Learning in Robotics, Supply Chain and Inventory Management, and Consumer Market Behavior and Pricing.
Zeevi has contributed to a range of scholarly publications, with recent papers including:
Their frequent co-authors include:
Zeevi's work has appeared in a variety of publication venues, the most frequent being:
In recognition of their work, Assaf Zeevi was named a Fellow of the Institute for Operations Research and the Management Sciences (INFORMS) in 2020.
Omar Besbes;Assaf Zeevi
Omar Besbes;Yonatan Gur;Assaf J. Zeevi
N. Bora Keskin;Assaf Zeevi
Edo Waks;Assaf Zeevi;Yoshihisa Yamamoto
Omar Besbes;Yonatan Gur;Assaf Zeevi
Assaf Zeevi;Roy Mashal
J. Michael Harrison;N. Bora Keskin;Assaf Zeevi
Omar Besbes;Assaf Zeevi
Denis Sauré;Assaf Zeevi
J. Michael Harrison;Assaf Zeevi
David Gamarnik;Assaf Zeevi
Omar Besbes;Assaf Zeevi
Achal Bassamboo;J. Michael Harrison;Assaf Zeevi
J. Michael Harrison;Assaf Zeevi
N. Bora Keskin;Assaf Zeevi
Shipra Agrawal;Vashist Avadhanula;Vineet Goyal;Assaf Zeevi
Achal Bassamboo;Sandeep Juneja;Assaf Zeevi
Constantinos Maglaras;Assaf Zeevi
Constantinos Maglaras;Assaf Zeevi
Achal Bassamboo;Ramandeep S. Randhawa;Assaf Zeevi
If you think any of the details on this page are incorrect, let us know.
Pursuing a Mathematics degree in the USA opens doors to diverse career pathways, especially when combined with online education. For those interested in broadening their skill set, exploring online mba transfer credits programs can facilitate a smooth transition into business leadership roles, leveraging analytical skills gained from mathematics.
Data-driven fields are booming, and specialized data analysis programs perfectly complement a math background by focusing on real-world applications of statistics and computational tools. These programs often enhance career prospects in tech, finance, and healthcare sectors.
For those looking for a quicker entry into management without compromising on education quality, researching the easiest mba programs can be a practical step. These programs offer accessible options to gain essential business knowledge.
Many students also seek the easiest mba programs available online to balance studies with professional or personal commitments. Choosing the right online pathway ensures flexibility while still advancing your career goals after a Mathematics degree.
Tsinghua University
Binghamton University
Philipp University of Marburg
University of Gothenburg
University of Kentucky
University of California, San Diego
Paul Scherrer Institute
Commonwealth Scientific and Industrial Research Organisation
University of Queensland
Meiji University
Graz University of Technology
University of Technology Sydney
University of Amsterdam
Korea Advanced Institute of Science and Technology
Cornell University
BI Norwegian Business School
