Michael G. Ross

mgross@mit.edu (617) 258-9675 46-4078B Postdoctoral associate Computational Visual Cognition Laboratory Brain and Cognitive Sciences Massachusetts Institute of Technology Curriculum vitae

Research

I am a computer scientist and my primary research interest is the application of statistical machine learning techniques to challenging problems in computer vision, human vision, and other real-world domains. I'm currently exploring the visual features humans use to classify images and judge their similarity and physical layouts. My current collaborators include Aude Oliva, Michelle Greene, and Emmanuelle Boloix. My Ph.D. advisor was Leslie Pack Kaelbling at the MIT Computer Science and Artificial Intelligence Laboratory. I was previously a postdoc with Andrew Cohen at the University of Massachusetts Amherst Psychology Department.

Manuscripts

• Michael G. Ross, Aude Oliva. Estimating perceptual spatial layout of scenes from gist features. (Under revision)
• Michael G. Ross, Michelle R. Greene, Aude Oliva. Human natural image classification strategies revealed by graphical models. (Under revision)
• Michael G. Ross, Emmanuelle Boloix, Aude Oliva. Psychological assessment of image feature spaces and their combinations. (In preparation)

Publications

• Andrew L. Cohen, Michael G. Ross. Exploring Mass Perception with Markov Chain Monte Carlo. Journal of Experimental Psychology: Human Perception and Performance. (In press) [pdf]
• Michael G. Ross, Andrew L. Cohen. Using graphical models to infer multiple visual classification features. Journal of Vision, 9(3). 2009. [link]
• Michael G. Ross, Leslie Pack Kaelbling. Segmentation According to Natural Examples: Learning Static Segmentation from Motion Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(4). April 2009. [pdf]
• Marwan A. Mattar, Michael G. Ross, Erik G. Learned-Miller. Nonparametric Curve Alignment. IEEE International Conference on Acoustics, Speech, and Signal Processing. 2009. [pdf]
• Kyle R. Cave, Andrew Cohen, Caren Rotello, Anthony McCaffrey, Michael G. Ross, Min Zeng, Xingshan Li, Matthew Zivot, Kris Chang. Using Eye Movements to Understand Complex Visual Comparisons, K. Rayner, D. Shen, X. Bai, and G. Yan (eds), Tianjin People’s Press/Psychology Press. 2008.
• Michael G. Ross, Andrew L. Cohen. GRIFT: A graphical model for inferring visual classification features from human data. Advances in Neural Information Processing Systems (NIPS) 20. 2008. [pdf]
• Michael Wick, Michael G. Ross, Erik Learned-Miller. Context-Sensitive Error Correction: Using Topic Models to Improve OCR. Ninth International Conference on Document Analysis and Recognition (ICDAR). September 2007. [pdf]
• Andrew L. Cohen, Richard M. Shiffrin, Jason M. Gold, David A. Ross, Michael G. Ross. Inducing features from visual noise. Journal of Vision, 7(8). 2007. [link]
• Michael G. Ross. Learning Static Object Segmentation from Motion Segmentation. Massachusetts Institute of Technology Ph.D. Thesis. August 2005. [pdf]
• Michael G. Ross, Leslie Pack Kaelbling. Learning Static Object Segmentation from Motion Segmentation. Twentieth National Conference on Artificial Intelligence. July 2005. [pdf]
• Michael G. Ross, Leslie Pack Kaelbling. A Systematic Approach to Learning Object Segmentation from Motion. NIPS 2003 Workshop on Open Challenges in Cognitive Vision. December 2003. [pdf]
• Michael G. Ross, Leslie Pack Kaelbling. Learning object segmentation from video data. MIT Artificial Intelligence Lab Memo, AIM-2003-022 (MIT-CSAIL-TR-2003-018). September 2003. [link]
• Michael G. Ross. Exploiting Texture-Motion Duality in Optical Flow and Image Segmentation. Massachusetts Institute of Technology Master's Thesis. August 2000. [pdf]
• Michael G. Ross. Multiscouting: Guiding distributed manipulation with multiple mobile sensors. Dartmouth College Technical Report PCS-TR98-332. June 1998. [pdf]

Code

• Master's Thesis Code Requires quicksort function to be implemented - see README files for details