Celebrating the Mathematical Work of

Celebrating the Mathematical Work of

Professor Maryam Mirzakhani

Professor Maryam Mirzakhani

Saturday, November 4, 2017, 2:00 to 4:30 PM, Mathematics Building, Room 4000A, UCLA

Professor Lotfi Zadeh, Father of Mathematical "Fuzzy Logic",

Professor Lotfi Zadeh, Father of Mathematical "Fuzzy Logic",

passed away at the age of 96

2017 Awards Ceremony

2017 Awards  Ceremony

Professor Madjid Samii

Named World Top Neurosurgeon

Professor Behrokh Khoshnevis

Wins NASA’s Top Award

Maryam Shanechi recognized as one of 35 Innovators Under 35 by MIT Technology Review

Each year the MIT Technology Review reveals its annual list of Innovators Under 35.  This is a list of 35 technologists under the age of 35, across universities, corporations and research labs, worldwide, whose work has the potential to transform the world.  This year, Assistant Professor Maryam Shanechi of the Electrical Engineering Department at USC is honored on the list. 

Prior to joining USC, Maryam was an assistant professor at the School of Electrical and Computer Engineering at Cornell University.  She received the B.A.Sc. degree with honors in Engineering Science from the University of Toronto in 2004 and the S.M. and Ph.D. degrees in Electrical Engineering and Computer Science (EECS) from the Massachusetts Institute of Technology (MIT) in 2006 and 2011, respectively.  She has held postdoctoral fellowships at Harvard Medical School and in the EECS department at the University of California, Berkeley.  She has received various awards for academic achievement including the Professional Engineers of Ontario gold medal, the W.S. Wilson medal, and the Natural Sciences and Engineering Research Council of Canada doctoral fellowship.

                                                                         Maryam Shanechi

Dr. Shanechi's research focuses on applying the principles of information and control theories and statistical signal processing to develop effective solutions for basic and clinical neuroscience problems that involve the collection and manipulation of neural signals and information.  One problem of particular interest to her is brain-machine interface design for motor function, for closed-loop control of anesthesia, and for control of neuropsychological disorders.  Her work combines methodology development with in vivo implementation and testing.

Source: MIT Technology Review