About Me

Christopher Kanan I’m an Assistant Professor in the Carlson Center for Imaging Science at the Rochester Institute of Technology. I direct the Machine and Neuromorphic Perception Laboratory (a.k.a., kLab) at RIT.

I use machine learning to solve problems in computer vision. My recent work has focused on object recognition, object detection, active vision, and visual question answering. Beyond computer vision, I also have a strong background in machine learning, eye tracking, primate vision, and theoretical neuroscience.

Check out our new site that uses our algorithms for Visual Question Answering: http://www.askimage.org/

Recent News

2017/02: I am an area chair for ICIP-2017.
2017/01: Teaching IMGS 682 – Image Processing for Computer Vision.
2016/12: Our paper on self-taught deep learning models for semantic segmentation of hyperspectral images was accepted to IEEE TGRS.
2016/08: Teaching IMGS 789 – Deep Learning for Vision.
2016/06: Our paper on Answer-Type Prediction for Visual Question Answering appeared at CVPR-2016.
2016/05: I won the RIT College of Science Rising Star Award.
2016/04: Our web-app for Visual Question Answering has launched: http://www.askimage.org/
2016/03: Our paper on using gnostic fields and saliency for tracking appeared at WACV-2016.
2016/01: Started teaching IMGS 682 – Image Processing for Computer Vision.
2015/08: Started as an assistant professor at RIT. My lab: http://klab.cis.rit.edu/
2015/07: The VAIS dataset for ship classification is now available for download.
2015/07: Our paper on combining hierarchical ICA with Gnostic Fields appeared at COGSCI-2015.
2015/06: Our paper on the VAIS dataset for ship classification appeared at the CVPR-2015 Perception Beyond the Visible Spectrum workshop.
2015/01: Our paper on the Multi-Fixation Pattern Analysis, a new method for analyzing eye movement data, appeared in Vision Research.

Outreach & Service

Christopher Kanan

I was General Chair for the 5th Annual inter-Science of Learning Center Conference (iSLC), which was held April 21-23, 2012. The meeting was sponsored by the National Science Foundation (NSF) and more than 100 scientists attended.

I was actively involved in the Temporal Dynamics of Learning Center and I served as Chair of the graduate student and postdoc committee from 2009-2012.

I’ve endeavored to promote diversity in graduate education. I’ve given talks at the California Forum for Diversity and at several California State Universities to help undergraduates obtain a better idea of how to get into a Ph.D. program and what is expected of them once they are accepted. I’m currently a faculty mentor for the RIT McNair and LSAMP Scholars programs, which are aimed at preparing first-generation college students and members of underrepresented minority groups for graduate school.


I grew up in a tiny town in rural Oklahoma, where I first began to explore artificial intelligence in 1996 by creating “bots” to play online multiplayer computer games in high school. As an undergraduate at Oklahoma State University, I double majored in philosophy and computer science.

Subsequently, I earned a M.S. in computer science from the University of Southern California (USC) , with an emphasis in artificial intelligence and neuroscience while working with Michael Arbib, an early pioneer in computational neuroscience and neural networks. I then went on to earn a Ph.D. in computer science at the University of California, San Diego (UCSD), where I was a member of Gary Cottrell’s research group. Afterwards, I became a Caltech Postdoctoral Scholar, where I worked at NASA’s Jet Propulsion Laboratory (JPL) as part of the Maritime and Aerial Perception group in the Robotics and Mobility Section. After eight months, JPL hired me as a Research Technologist, where I helped develop artificial vision systems for autonomous robots. In August 2015, I joined the Chester F. Carlson Center for Imaging Science at RIT as an Assistant Professor.