- Professor of Electrical Engineering and Computer Science, Massachusetts Institute of Technology
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.
- PhD in Electrical Engineering and Computer Science, MIT, 2001
- MS in Computer Scince, Technion, Israel, 1995
- BSc in Computer Science, Technion, Israel, 1993
- Faculty Research Innovation Fellowship, EECS MIT, 2015
- Electrical and Computer Engineering Department Heads Association: Diversity Award, 2014
- MIT: Jamieson Prize for Excellence in Teaching, 2013
- MIT: Smullin Prize for Teaching, 2011
- Medical Image Computing and Computer Assisted Intervention Society: Young Investigator Award, 2011
- Medical Image Computing and Computer Assisted Intervention Society: Young Investigator Award, 2010
- National Science Foundation: Career Award, 2007
- Medical Image Computing and Computer Assisted Intervention Society: Young Investigator Award, 2007
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.
- C. Wachinger, P. Golland, W. Kremen, B. Fischl, and M. Reuter. “BrainPrint: A discriminative characterization of brain morphology.” NeuroImage, 109 (2015): 232-48.
- G. Langs, A. Sweet, D. Lashkari, Y. Tie, L. Rigolo, A.J. Golby, and P. Golland. “Decoupling function and anatomy in atlases of functional connectivity patterns: Language mapping in tumor patients.” NeuroImage 103 (2014): 462-75.
- A. Woolgar, P. Golland, and S. Bode. “Coping with Confounds in Multivoxel Pattern Analysis: What Should We Do About Reaction Time Differences? A Comment on Todd, Nystrom & Cohen 2013.” NeuroImage 98 (2014): 506-12.
- C. Wachinger and P. Golland. “Atlas-Based Under-Segmentation.” LNCS 8673 (2014): 315-22.
- C. Wachinger, P. Golland, and M. Reuter. “BrainPrint: Identifying Subjects by Their Brain.” LNCS 8673 (2014): 41-48.
A full list of Professor Golland’s publications can be found on her website.