My main interest is the development of models and algorithms capable of making accurate inferences in the face of high levels of uncertainty. In particular, I study techniques in probabilistic graphical models, machine learning, and data mining; especially as they relate to computer vision.
I am also interested in sparse regression techniques and deep learning for visual feature building.
I am advised by David Crandall
Sven Bambach, Stefan Lee, David Crandall, Chen Yu, Lending A Hand: Detecting Hands and Recognizing Activities in Complex Egocentric Interactions, IEEE International Conference on Computer Vision (ICCV), 2015. [PDF
] [Dataset WWW
] [Paper WWW
Stefan Lee, Nicolas Maisonneuve, David Crandall, Josef Sivic, Alexei A. Efros. Linking Past to Present: Discovering Style in Two Centuries of Architecture, IEEE International Conference on Computational Photography (ICCP), 2015. [PDF
Stefan Lee, Haipeng Zhang, David Crandall. Predicting Geo-informative Attributes in Large-scale Image Collections using Convolutional Neural Networks, IEEE Workshop on Applications of Computer Vision (WACV), 2015. [PDF
Stefan Lee, Sven Bambach, David Crandall, John Franchak, Chen Yu. This Hand Is My Hand: A Probabilistic Approach to Hand Disambiguation in Egocentric Video, 3rd Workshop on Egocentric Vision, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014. (Best Paper Award Winner)
Stefan Lee, Jerome Mitchell, David Crandall, and Geoffery Fox. Estimating Bedrock and Surface Layer Boundaries And Confidence Intervals In Ice Sheet Radar Imagery Using MCMC, International Conference on Image Processing, 2014. [PDF
Technical reports and short papers:
Sven Bambach, Stefan Lee, David Crandall, Chen Yu, Detecting and Classifying Hands in Social and Driving Contexts, Vision for Intelligent Vehicles and Applications (VIVA) Challenge and Workshop, IEEE Intelligent Vehicles Symposium, 2015.
Sven Bambach, Stefan Lee, David Crandall, John Franchak, Chen Yu, Tracking Hands of Interacting People in Egocentric Video, Workshop on Observing and Understanding Hands in Action, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
Stefan Lee and David Crandall. Learning to Identify Local Flora with Human Feedback, Workshop on Computer Vision and Human Computation, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014. [PDF
Contributed a chapter on landmark recognition for Visual Analysis and Geo-Localization of Large Scale Imagery published by Springer [Upcoming]
Unpublished work possibly of interest to someone somewhere:
A Survey of Sparse Coding for Object Recognition [PDF
B659 - Image Processing and Recognition (Fall 2014)
I was responsible for developing and teaching weekly lab content in this mixed graduate/undergraduate introductory course on image processing and computer vision. I also aided in the design and grading of other course material including assignments and tests.
I399 - Research Methods for Informatics and Computing (Fall 2013)
In this course, I advised a group of four undergraduate students through a semester long research project. The resulting project was awarded "Best Project" in the course following a public presentation and voting session.
C211 - Introduction to Computer Science (Fall 2011 - Summer 2012)
I was responsible for weekly lab content as well as grading homeworks and tests. This course regularly had a few hundred students and one semester I led the group of 15+ assistant instructors.
PhD in Computer Science (Expected Summer 2016)
MS in Computer Science (2013)
BS in Computer Science (2011)
I adore board games and follow an embarassing number of web comics. I also really enjoy good food and like to cook.
In an effort to balance out the amount of time work keeps me in a chair, I've picked up running and weight lifting. I've played racquetball casually for a number of years but have yet to show any real skill at the game.
One of my favorite perks of academia is the chance to travel and I love visiting new places. I put together a digital push-pin map to keep track of the places I've gone.