Eli Shlizerman is an Assistant Professor in the Department of Applied Mathematics at the University of Washington. He received his MSc and PhD degrees in computer science and applied mathematics from the Weizmann Institute of Science in 2005 and 2009 respectively. His training is in dynamical systems, model reduction and complex dynamics. Since September 2009, Eli joined the department of Applied Mathematics at UW for his postdoctoral research as an Acting Assistant Professor and then
promoted to Assistant Professor in October 2012.
Eli's research focuses on classification and modeling of dynamics of complex systems. For this purpose he develops methods
that combine data analysis and dynamical systems theory. Complex systems that are being studied are neuronal networks (high dimensional)
and partial differential equations (infinite dimensional). Among the methods are tools for derivation of reduced models, inference of connectivity in networks, classification and recognition of dynamics.
The approaches are applied to modeling of functional connectomics, neurobiological networks that underly insects' sensory systems and to neural dynamics of organisms such as C. elegans.
I am particularly excited about working with real data (vs. only simulations) and thereby collaborating with UW Biology, U-Mass Neurobiology and Allen Institute for Brain Science. For example see our latest Science paper with Riffell's lab.
Seminars
I organize the Netcomp (Network Computation) workgroup: joint meetings of Fairhall, Kutz, Shea-Brown and Shlizerman groups on network related research. You are welcome to join us on Wednesdays bi-weekly at 11am in Lewis Hall, room 208.
I am the representative of UW and MBI institutional partnership. Check the workshops on MBI website and contact me for further details.
AMath Distinguished Boeing Colloquia has an outstanding line-up of speakers.
Join the Computational Neuroscience Journal Club organized by Eric Shea-Brown and Yu Hu on Tuesdays 9:30-10:30 alternating between Lewis Hall and Allen Institute for Brain Science.
Conferences
Conferences that are focused on Applied/Computational Mathematics, Data Analysis, Computational Neuroscience are relevant to our research. Typically you can find our research presented at the following conferences:
SIAM Dynamical systems
SIAM Life Sciences
SIAM Nonlinear Waves
CNS
Cosyne
Society for Neuroscience
IMAA
AIMS
BMES
NIPS
Check the map below for recent conferences and talks:
