Martin I. Reiman
Martin I. Reiman | |
|---|---|
| Alma mater | Cornell University Stanford University |
| Awards | John von Neumann Theory Prize (2016) |
| Scientific career | |
| Fields | Operations Research |
| Institutions | Columbia University |
Martin I. Reiman is an American engineer and Professor in the Industrial Engineering and Operations Research Department at Columbia University.[1]
Biography
[edit]Reiman received his A.B. from Cornell University and his M.S. and Ph.D. from Stanford University.[2] He began his career at Bell Labs in 1977 after graduating from Stanford. He was a Distinguished Member of Technical Staff at Bell Labs from 1998 until 2015. His research has focused on teletraffic theory and stochastic networks.
Reiman joined the faculty of the Fu Foundation School of Engineering and Applied Science at Columbia University in 2017.[2]
Recognition
[edit]Reiman received the John von Neumann Theory Prize from INFORMS in 2016.[3][4]
He was elected to the National Academy of Engineering in 2022 for his "contributions to network theory and applications in large-scale stochastic systems."[1] He is also a Fellow of the Institute for Operations Research and the Management Sciences (INFORMS).[2][5]
References
[edit]- ^ a b "Dr. Martin I. Reiman". NAE Website. Retrieved 2023-04-04.
- ^ a b c "Martin Reiman and Three Columbia Engineering Alums Elected to National Academy of Engineering". Columbia Engineering. 2022-02-10. Retrieved 2023-04-04.
- ^ "UC San Diego Professor Wins Major Prize in Mathematics". today.ucsd.edu. Retrieved 2023-04-04.
- ^ INFORMS. "Martin I. Reiman". INFORMS. Retrieved 2023-04-04.
- ^ "Institute of Mathematical Statistics | Ruth Williams and Martin Reiman receive von Neumann Theory Prize". Retrieved 2023-04-04.
- Living people
- American engineers
- Columbia School of Engineering and Applied Science faculty
- Cornell University alumni
- Stanford University alumni
- Scientists at Bell Labs
- Members of the United States National Academy of Engineering
- Fellows of the Institute of Mathematical Statistics
- Fellows of the Institute for Operations Research and the Management Sciences