32 Vassar Street
Cambridge, MA 02139
- PhD in Electrical Engineering and Computer Science, MIT, 2001
- MS in Computer Scince, Technion, Israel, 1995
- BSc in Computer Science, Technion, Israel, 1993
Polina Golland is a Professor of Electrical Engineering and Computer Science at MIT. Her research interests span computer vision and machine learning. Her current work focuses on developing statistical analysis methods for characterization of biological processes using images (from MRI to microscopy) as a source of information. She received BSc and Masters in Computer Science from Technion, Israel in 1993 and 1995, and a PhD in Electrical Engineering and Computer Science from MIT in 2001. She joined the faculty in 2003.
Polina’s primary research interest is in developing novel techniques for biomedical image analysis and understanding. She particularly enjoys working on algorithms that either explore the geometry of the world and the imaging process in a new way or improve image-based inference through statistical modeling of the image data. She is interested in shape modeling and representation, predictive modeling, and visualization of statistical models.
Polina’s current research focuses on developing statistical analysis methods for characterization of biological processes using images as a source of information. In this domain, she is interested in modeling biological shape and function, how they relate to each other and vary across individuals.
- Ruth and Joel Spira Awards for Excellence in Teaching, School of Engineering, MIT, 2021
- AIMBE Fellow, 2021
Henry Ellis Warren (1894) Chair in Electrical Engineering and Computer Science, EECS, MIT, 2018
- MICCAI Society Fellow. 2016
- ECEDHA Diversity Award, 2014
- Jamieson Prize for Excellence in Teaching, MIT, 2013
- Smullin award for teaching excellence, EECS, MIT, 2011
A full list of Professor Golland’s publications can be found on her website.
- 6.3800 Introduction to Inference
- 6.7800 Inference and Information