Face


email:
balakg@mit.edu

github:
github.com/balakg

address:
32 Vassar St.
Cambridge, MA
02139

Guha Balakrishnan

I am a postdoc in Bill Freeman’s group at MIT, with research interests in computer vision, graphics and machine learning. I completed my Master’s (2013) and PhD (2018) degrees in the EECS department at MIT, advised by Professors John Guttag and Frédo Durand. My PhD thesis was titled Analyzing and Synthesizing Deformations in Image Datasets. I explored how modeling deformations is useful for applications such as image warping/synthesis, image registration, and action alignment in videos.

I also have an interest in applications of computer vision to healthcare. My Master's work focused on vitals signs measurement from video recordings.

Prior to MIT, I completed my bachelor of science degrees in Computer Science and Computer Engineering at the University of Michigan, Ann Arbor. There, I worked on medical machine learning research with Professor Zeeshan Syed.

Selected Work

An Unsupervised Learning Model for Deformable Medical Image Registration.
G. Balakrishnan, A. Zhao, M. R. Sabuncu, J. Guttag, A. V. Dalca.
CVPR 2018
paper, code

Synthesizing Images of Humans in Unseen Poses.
G. Balakrishnan, A. Zhao, A. V. Dalca, F. Durand, J. Guttag.
CVPR 2018
paper, code

Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration.
A. V. Dalca, G. Balakrishnan, J. Guttag, and M. R. Sabuncu.
MICCAI 2018.
paper

A Video-Based Method for Objectively Rating Ataxia.
R. Jaroensri, A. Zhao, G. Balakrishnan, D. Lo, J. Schmahmann, J. Guttag, F. Durand
MLHC 2017.
paper

Video diff: highlighting differences between similar actions in videos.
G. Balakrishnan,  F. Durand, J. Guttag.
Siggraph Asia 2015.
project page

Detecting Pulse from Head Motions in Video.
G. Balakrishnan,  F. Durand, J. Guttag.
CVPR 2013.
project page

Scalable personalization of long-term physiological monitoring: Active learning methodologies for epileptic seizure onset detection.
G. Balakrishnan, Z. Syed.
AISTATS 2012.
paper