Assistant Professor, MathCS and Neuroscience, Emory University
New Interfaces in Neural Computing
“Technology is the active human interface with the material world.” -UK LeGuin
Computer science is the art of reducing complex, messy real-world problems to tractable abstractions. The layers of abstraction developed by computer scientists over the last fifty years have formed a diverse ecosystem of high level paradigms to create, understand, and distribute information with speed, reliability, and efficiency.
Neuroscience today is done at what we could consider the “transistor level,’’ but the questions neuroscientists face are often identical to those asked by current frontiers of computing. These questions include “How should data be represented, and how do we decide what to keep?’’ or “How much power does it cost to build our network, and can we do better?’’ In this talk, we will explore the parallels between problems involving power efficiency, redundancy, and structure between distributed computing and biologically plausible neural-networks, and in this translation demonstrate the power of an interdisciplinary approach to neural computing.
Dr. Avani Wildani is an Assistant Professor in MathCS and Neuroscience at Emory University. Prior to that, she was a Pioneer Postdoctoral Fellow in computational neuroscience at the Salk Institute for Biological Sciences. She has worked as a systems administrator, video game tester, and lab animal wrangler as well as research internships at Google, IBM Almaden, and Sandia National Laboratories. She earned her B.S. in Computer Science and Mathematics at Harvey Mudd College and her Ph.D. in Computer Science at UC Santa Cruz under Dr. Ethan Miller. Her interests are centered around information storage and retrieval across different storage models, with application domains including access prediction, data deduplication, archival economics, power management, wireless mesh networks, auditory receptive field characterization, and pollution monitoring.
She is the co-PI of the SimBioSys lab at Emory, and her group focuses on information models in cloud and communication systems, particularly those with biological connections, with a long term goal of categorizing neural information. She was co-chair of the inaugural computer systems track at the 2016 Grace Hopper Celebration of Women in Computing, and is mad enough to do it again this year.