- Comment: Please see the guideline on External Links. Shadow311 (talk) 19:17, 24 April 2024 (UTC)
- Comment: Unfortunately this article is written almost completely ignoring Wikipedia standards, and many prior declinations. It contains overlong descriptions of his work which read like a CV. There are far too many claims which are bragging, WP:PUFFERY. Looking deeper, with a Google Scholar h-factor of 51 and no major awards he does not pass the notability bar, WP:NPROF. Plus there are large parts of his career which are unsourced.If you want to try again treat this as a serious research problem. Read other pages. Remove the claims and masses of less useful information; I estimate 1/4 the current size. Add awards (if they exist). Ldm1954 (talk) 12:45, 4 March 2024 (UTC)
- Comment: The coverage of Ido Kanter is about the research and does not demonstrate significant notability about them. Needs references specifically about Kanter and not using the authors own papers for references to show notability. At the moment appears to be a bit of a CV. KeepItGoingForward (talk) 18:03, 1 November 2023 (UTC)
- Comment: Every single reference except the scienmag.com one is a primary source. -- NotCharizard đš 10:54, 21 September 2023 (UTC)
- Comment: "Follow your dreams"??? OLI 09:23, 2 September 2023 (UTC)
- Comment: "Follow your dreams"???? Theroadislong (talk) 12:51, 26 August 2023 (UTC)
Professor Ido Kanter | |
---|---|
Born | |
Nationality (legal) | Israeli |
Citizenship | Israel |
Alma mater | Bar-Ilan University |
Awards | Weizmann Postdoctoral Fellowship (1988-1989)
Humboldt Senior Research Prize (2001) |
Scientific career | |
Fields |
|
Institutions | Postdoc: Princeton University, with P. W. Anderson |
Doctoral advisor | Haim Sompolinsky |
Ido Kanter (born: 21 Nov. 1959) is an Israeli professor of physics and the head of the Lab for Reverberating Modes in Neural Networks at the Gonda Brain Research Center at Bar-Ilan University. He specializes in models of disorder magnetic systems, physical random number generators, theory of neural networks, deep learning and synchronization among neurons and lasers, documented in more than 200 publications.
Education
Kanter graduated from Bar-Ilan University with a bachelor's degree in physics and computer science in 1983. In 1987, he received his direct Ph.D. from Bar-Ilan University with his thesis, âTheory of Spin Glasses and its Applications to Complex Problems in Mathematics and Biology,â under the supervision of Professor Haim Sompolinsky.
After completing his Ph.D., Kanter joined Professor Phil W. Andersonâs group at Princeton University as a visiting research fellow (1988-1989). He was also a visiting research fellow at AT&T Bell Labs, collaborating with Yann le Cun (1989). In 1989, Kanter became a senior lecturer at Bar-Ilan University. He became an associate professor in 1991 and a full professor in 1996.
Personal Life
Ido Kanter was born and raised in Rehovot, Israel and served in the Israeli Defense Force from 1978 to 1981.
Research Interests
Ido Kanter specializes in models of disorder magnetic systems, ultrafast physical random number generators, theory of neural networks, neural cryptography, deep learning and synchronization among neurons and lasers and experimental and theoretical neuroscience, documented in more than 220 publications.[1]
Main Contributions
Using a combination of theoretical and experimental methods[2], Kanter has made several major contributions to a wide range of fields ranging from statistical physics and communication to neural cryptography and neuroscience[3]. These include pioneering a new field of statistical physics known as the inverse problem[4], bridging between Shannon theory and the second thermodynamic law[5], presenting a cryptographic key exchange protocol based on neural networks[6], and creating an ultrafast non-deterministic random bit generator (RBG)[7]. Currently focusing on the field of experimental and theoretical neuroscience, Kanter studies a variety of topics including the new neuron[8], dendritic learning[9], neural interfaces, and machine learning[10].
Selected Publications
- Reidler, I., Aviad, Y., Rosenbluh, M. & Kanter, I. Ultrahigh-speed random number generation based on a chaotic semiconductor laser. Physical review letters 103, 024102 (2009).
- Kanter, I., Aviad, Y., Reidler, I., Cohen, E. & Rosenbluh, M. An optical ultrafast random bit generator. Nature Photonics 4, 58-61 (2010).
- Kanter, I. & Gotesdyner, R. Do classical spin systems with the same metastable states have identical Hamiltonians? Physical review letters 72, 2678 (1994).
- Shental, O. & Kanter, I. Shannon meets Carnot: Generalized second thermodynamic law. Europhysics Letters 85, 10006 (2009).
- Nixon, M. et al. Synchronized cluster formation in coupled laser networks. Physical review letters 106, 223901 (2011).
- Kanter, I., Kopelowitz, E. & Kinzel, W. Public channel cryptography: chaos synchronization and Hilbertâs tenth problem. Phys Rev Lett 101, 084102 (2008).
- Sardi, S. et al. Dendritic learning as a paradigm shift in brain learning. ACS chemical neuroscience 9, 1230-1232 (2018).
References
- ^ Ido Kanter's Google Scholar profile
- ^ https://kanterlabsite.wixsite.com/idokanter/about-me
- ^ https://physics.biu.ac.il/en/node/578
- ^ Kanter, I. & Gotesdyner, R. Do classical spin systems with the same metastable states have identical Hamiltonians? Physical review letters 72, 2678 (1994).
- ^ Shental, O. & Kanter, I. Shannon meets Carnot: Generalized second thermodynamic law. Europhysics Letters 85, 10006 (2009).
- ^ Kanter, I., Kopelowitz, E. & Kinzel, W. Public channel cryptography: chaos synchronization and Hilbertâs tenth problem. Phys Rev Lett 101, 084102 (2008).
- ^ Kanter, I., Aviad, Y., Reidler, I., Cohen, E. & Rosenbluh, M. An optical ultrafast random bit generator. Nature Photonics 4, 58-61 (2010).
- ^ Sardi, S., Vardi, R., Sheinin, A., Goldental, A. & Kanter, I. New Types of Experiments Reveal that a Neuron Functions as Multiple Independent Threshold Units. Scientific reports 7, 18036 (2017)
- ^ Sardi, S. et al. Dendritic learning as a paradigm shift in brain learning. ACS chemical neuroscience 9, 1230-1232 (2018).
- ^ https://gondabrain.biu.ac.il/en/node/317