You can edit almost every page by Creating an account and confirming your email.

Fathi M. Salem

From EverybodyWiki Bios & Wiki

Template:Prod llm/dated

Fathi M. Salem is an American electrical engineer and academic who is a professor of electrical and computer engineering at Michigan State University, where he leads the Circuits, Systems and Artificial Neural Networks research group.[1] He is also affiliated with the MSU Neuroscience Program.[2] In 1996, he became an IEEE Life Member and Fellow "for contributions to the development of tools for the analysis and design of nonlinear and chaotic circuits and systems".[3]

Education

Salem received a PhD in electrical engineering and computer sciences from the University of California, Berkeley in 1983. He earned a Master of Science degree in electrical engineering from the University of California, Davis in 1979.[4]

Research

Salem's research focuses on neural networks and learning systems, blind signal deconvolution and extraction, dynamical systems and chaos, and integrated CMOS sensing and processing.[2] His work on blind source recovery established a state-space framework for the problem using Kullback–Leibler divergence as a performance functional.[5][6]

His more recent work has focused on recurrent neural networks, including developing simplified variants of long short-term memory (LSTM) architectures with reduced parameters.[7][8]

References

  1. "Research". Michigan State University College of Engineering. Retrieved January 25, 2026.
  2. 2.0 2.1 "Fathi Salem". Michigan State University College of Natural Science. Retrieved January 25, 2026.
  3. "IEEE Fellow Directory: Fathi Salem". IEEE Fellows Directory. Retrieved 25 January 2026.
  4. "Fathi Salem". ResearchGate. Retrieved January 25, 2026.
  5. Waheed, Khurram; Salem, Fathi M. (2003). "Blind Source Recovery: A Framework in the State Space". Journal of Machine Learning Research. 4: 1411–1446. doi:10.1162/jmlr.2003.4.7-8.1411.
  6. Salem, F.M.; Waheed, K.; Erten, G. (2005). "Blind Source Recovery in a State-Space Framework: Algorithms for Static and Dynamic Environments". Neural Processing Letters. Springer. 21 (3): 153–173. doi:10.1007/s11063-004-5484-9.
  7. Heck, Joel C.; Salem, Fathi M. (2017). Simplified minimal gated unit variations for recurrent neural networks. 2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS). pp. 1593–1596. doi:10.1109/MWSCAS.2017.8053225.
  8. Dey, Rahul; Salem, Fathi M. (2017). Gate-variants of Gated Recurrent Unit (GRU) neural networks. 2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS). pp. 1597–1600. doi:10.1109/MWSCAS.2017.8053226.


This article "Fathi Salem" is from Wikipedia. The list of its authors can be seen in its historical and/or the page Edithistory:Fathi Salem. Articles copied from Draft Namespace on Wikipedia could be seen on the Draft Namespace of Wikipedia and not main one.