Shih-Chii Liu

Shih-Chii Liu is a professor at the University of Zürich and is the co-leader of the Sensors Group at the Institute of Neuroinformatics[1], University of Zürich / ETH Zürich. Her research interests include developing algorithms and networks using knowledge obtained from neuroscience.

Education and career

Liu pursued a Bachelor's degree in electrical engineering at Massachusetts Institute of Technology[2] and received her PhD in 1997 from California Institute of Technology from the department of Computation and Neural Systems [3]. A year later she joined the Sensors Group at the Institute of Neuroinformatics, a group which is also affiliated with the Neuroscience Center Zurich [4].

Recognition

Liu is a past chair of the IEEE CAS Neural Systems and Applications, and IEEE Sensory Systems Technical Committees [5]. She is currently a chair of the IEEE CAS/ED Swiss Chapter[5], and is an associate editor for the Neural Networks Journal, and the IEEE Transactions on Biomedical Circuits and Systems, among others[3].

Publications

Liu is the lead author of two textbooks on Neuromorphic engineering: Analog VLSI: Circuits and Principles (MIT Press, 2002)[6] and Event‐Based Neuromorphic Systems (John Wiley & Sons, Ltd, 2015)[7].

gollark: What's meant to be *positive* bias?
gollark: That also has a ton of connotations.
gollark: ***Ë***
gollark: We should all aim to be more correct™.
gollark: "Winning" is silly.

References
  1. "Institute Page". Retrieved 2020-03-05.
  2. https://news.ece.ufl.edu/2018/12/05/seminar-dr-shih-chii-liu/, retrieved 2020-05-03
  3. http://sensors.ini.uzh.ch/biography.html, retrieved 2020-0503
  4. [https://www.neuroscience.uzh.ch/en/research/sensory_systems.html#liu, retrieved 2020-05-03
  5. "Seminar: Dr. Shih-Chii Liu". ECE Florida News. 2018-12-05. Retrieved 2020-03-05.
  6. "Analog VLSI: Circuits and Principles". Retrieved 2020-03-05.
  7. "Event‐Based Neuromorphic Systems". Retrieved 2020-03-05.
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.