Joint Symposium on Neural Computation
This annual meeting brings together scientists from universities in southern California to discuss topics broadly related to computational neuroscience. This year's meeting will be held at UCSD on Saturday May 20, 2017. The symposium is hosted by the Institute for Neural Computation at the San Diego Supercomputer Center, and organized by Terry Sejnowski (email@example.com) of Salk and UC San Diego, and UCSD professor Gert Cauwenberghs (firstname.lastname@example.org).
Abstracts due: Monday, May 5, 2017
Other confirmed speakers will include:
Saket Navlaka - Salk Institute
There will also be a poster session for grad students and postdocs. More information at this website.
Keynote speaker David Anderson is Caltech's Seymour Benzer Professor of Biology and an investigator of the Howard Hughes Medical Institute. He received his AB from Harvard University (biochemical sciences, summa cum laude) and his PhD in cell biology from the Rockefeller University, where he trained with Nobel Laureate Günter Blobel, and did his postdoctoral training at Columbia University with Nobel Laureate Richard Axel. Anderson's research focuses on the study of neural circuits that control emotional behaviors in animal models. He has been at the forefront of developing and applying new technologies for neural-circuit manipulation, such as optogenetics and pharmacogenetics, to the study of emotional behaviors such as fear, anxiety, and aggression in both mice and the fruit fly Drosophila melanogaster. His work in mice is currently focused on limbic circuits, including the amygdala and hypothalamus, and their role in aggression.
Keynote speaker Hava Siegelmann joined DARPA in July 2016 with the goal of developing programs that advance intelligence in computerized devices, focusing on life-long learning, context-aware adaptivity, and user-centered applications. Prior to joining DARPA, Dr. Siegelmann directed the Biologically Inspired Neural and Dynamical Systems (BINDS) Laboratory at the University of Massachusetts Amherst. While at the University, she also served as a Core Member of the Neuroscience and Behavior Program. Siegelmann is the author of Neural Networks and Analog Computation: Beyond the Turing Limit (Birkhauser, 1998). She also has given nearly 200 invited lectures and served on various editorial boards, including those for Frontiers in Computational Neuroscience, Neural Networks, Chaos, and Scholarpedia. All of Dr. Siegelmann’s degrees are in Computer Science: a Ph.D. from Rutgers University in New Jersey, a M.S. from The Hebrew University in Israel, and a B.A. from Technion in Israel. Her academic distinctions include fellowships from the Center for Complexity Systems, the Alon Fellowship of Excellence of the Israeli National Committee for Higher Education, and the Rutgers Doctoral Fellowship of Excellence. She is the 2016 recipient of the Hebb Award of the International Neural Network Society.
Registration is required to ensure sufficient food during coffee breaks and lunch and to ensure sufficient poster boards:
*Registration is Required