Sharon's research interest is in the neurological basis of social behavior, emotion, learning, and decision-making, and its changes in psychiatric disorders. She received her Bachelor of Science in Computer Science, in the Intelligent Systems track, at Columbia University. She has a background in machine learning and artificial intelligence, robotics, and natural language processing. Her past research experience includes developing neural network models of learning at the Parallel Distributed Processing Laboratory at Stanford University with Jay McClelland.
Brenden's research interests are in neuroeconomics, behavioral economics, decision theory, economics of information, and experimental economics. He is particularly interested in models of perception and choice under limited attention and cognition. He received a Bacholer in Economics (with a minor in Mathematics) from New York University, completed a Masters in Economics at Columbia University, and has been working as an applied micro research assistant at Columbia Business School for the past two years.
Sabera seeks to understand how the brain relies on various electrical and chemical feedback signals to influence learning and memory. She was most recently at the Chan Zuckerberg Biohub where she established the neuroengineering research initiatives and conceived the Biohub's first Neuroengineering Symposium. Sabera graduated from Stanford with two Bachelors of Science with Honors in electrical engineering and biochemistry. While at Stanford, she explored how fruit flies learn visual memories with Professor Tom Clandinin, published her electrostatic precipitator work with Professor Juan Rivas at IEEE COMPEL, and implemented a neuropmorphic model on Neurogrid with Professor Kwabena Boahen. Outside of research, Sabera also enjoys making systems to help people in third world countries. For example, she created, built and deployed water purification systems in daycares for street children in Dhaka, Bangladesh.
Yameng received a Bachelor of Science in Neuroscience from Columbia University. She has spent the past year as a research assistant in two different labs at Columbia. The Zucker lab research is focused on elucidating mechanisms used for signal transduction and information processing in sensory systems. Research in the Laboratory for Intelligent Imaging and Neural Computing, under Paul Sajda, uses principles of reverse engineering to characterize the cortical networks underlying perceptual and cognitive processes, such as rapid decision making, in the human brain.
Computational and Neural Systems
George received a Bachelor of Science in Neuroscience and Cognitive Science, Mathematics, and Computer Science from the University of Arizona. He was an undergraduate research associate in the lab of Dr. Shaowen Bao where the research goal is to understand sensory processing.
Kejun received a Bachelor of Science in Math and Computer Science and Neuroscience and Behavioral Biology from Emory University. For the past two years she has been an undergraduate researcher in the Systems Neural Engineering Lab where research centers on understanding how large populations of neurons in the brain perform computations and represent intention. These insights are used to develop high-performance, robust, and practical assistive devices for people with disabilities and neurological disorders.
Yue received a Bachelor of Science in Computer Science with an additional major in Physics and a minor in Neural Computation from Carnegie Mellon University. Yue has spent the last year as a research assistant at the Center for the Neural Basis of Cognition, Carnegie Mellon University. She investigated the connections between scene statistics and neuronal codes at the individual level and at the population level.