I spent some time as a Visiting Scholar at the Redwood Center for Theoretical Neuroscience at UC Berkeley, which produced some publications (see Google Scholar).
My core research interest is in understanding how the brain works when viewed as an information processing system, with a particular focus on the neural circuits underlying visual perception. I am also interested in human organizations when viewed as systems, and the use of technology to implement intelligent learning behavior.
My most recent neuroscience work has focused on biologically-realistic spiking network models of visual pattern detection and sparse code formation. Sparse coding is a method for representing information that appears to be used by the brain. Its key characteristic is that very few representation variables (neurons) are active at any given moment.
One research project is E-I Net, a neural circuit model and simulation engine written in MATLAB that learns sparse code patterns using an approach inspired by the brain's visual cortex. This was written up in a paper published in The Journal of Neuroscience (abstract, PDF).
Lately I have been answering neuroscience questions on the Q&A website Quora and was selected as a "Top Writer" for 2017, 2016, 2014, and 2013. See representative answers.
Over 60 Quora answers have been picked up and published by sites such as Forbes (20+), Huffington Post (10+), Slate (8+), and Business Insider (7+). See selected articles.
Systems neuroscience interests:
- Discovery of objects and scene structure in the human visual system
- Perceptual organization, dynamic configuration, and information routing
- World model formation, representation, and neural encoding
- Dynamic interaction-driven models of perception, strategy, and action in the sensorimotor loop
- Integration of bottom-up and top-down information processing in perception
- System and circuit theories of information processing in the brain
- Functional role of cortical oscillations (gamma, theta, alpha, beta)
- Models of spike-based information processing in the cortical microcircuit
- Circuit models of learning and memory (LTP, LTD, STDP, working memory)
- Reinforcement learning, strategy planning, and policy execution in spiking networks
Computer science interests — machine learning:
- Statistical models of visual processing and object recognition
- Neural networks and neural information processing models
- Reinforcement learning and Bayesian statistical models
- Machine models of behavior planning and interactive adaptation
Computer science interests — software architecture:
- Object-oriented models of information and function representation
- Computer vision systems
- User interface design and interactive information mapping strategies
- Social networking and collaboration system data models
Attended research meetings:
- SfN 2005-2011 (Society for Neuroscience)
- Cosyne 2006, 2007, 2008, 2009, 2012 (Computational and Systems Neuroscience)
- CVPR 2006, 2007, 2009 (IEEE Computer Vision and Pattern Recognition)
- VSS 2006, 2007 (Vision Science Society)
- NIPS 2005, 2006 (Neural Information Processing Systems)
- CNS 2006, 2012 (Computational Neuroscience Society)
- FENS 2006 (Federation of European Neuroscience Societies)
- ASSC 2007, 2011 (Association for the Scientific Study of Consciousness)
- TSC 2000, 2006, 2008, 2010, 2012 (Towards a Science of Consciousness)