Viraj Prabhu

I am a third year CS Ph.D. student at Georgia Tech, advised by Prof. Judy Hoffman. My research interests are in developing data-efficient and reliable computer vision systems that can be deployed in the real world. Specifically, I am interested in sample-efficient learning (particularly few-shot and active learning), adaptation across visual tasks and domains, and reliable and calibrated uncertainty estimation from deep neural networks.

I earned my Master's in CS (awarded the MS Research award) in Spring '19, also at Georgia Tech, where I was advised by Prof. Devi Parikh (and worked closely with Prof. Dhruv Batra) on developing visual conversational agents.

I spent two wonderful summers doing research in machine learning for healthcare at Curai, where I worked on open-set learning for medical diagnosis, and on few-shot diagnosis of dermatological diseases (mentored by Dr. Anitha Kannan). Prior to joining Georgia Tech, I was a research assistant in the Machine Learning and Perception lab at Virginia Tech, advised by Prof. Dhruv Batra. Before that, I worked as a software developer at Adobe.

I received my Bachelor's degree in Computer Science from BITS Pilani. Over the course of my undergrad, I was fortunate to undertake research internships at Adobe, Tonbo Imaging, and CEERI Pilani, where I worked on problems ranging from video segmentation to camera calibration.

On the side, I have been an open-source contributor to CloudCV and served as mentor for Google Summer of Code (2016, 2017) and Google Code-In (2017) for the Fabrik project. I've also won a couple of hackathons (VTHacks '17, BITS Google Hackathon '14). Apart from work, I enjoy running, soccer, reading, playing the guitar, and (occasionally) writing.

Contact: I'm always happy to discuss research or grad school applications/life! Feel free to email me at

Fall 2011-Spring 2015
Fall 2017-current
Summer 2014, Fall 2015- Summer 2016
Fall 2016-Spring 2017
Summer 2018, 2019
Summer 2021


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AUGCO: Augmentation Consistency-guided Self-training for Source-free Domain Adaptive Semantic Segmentation

Viraj Prabhu*, Shivam Khare*, Deeksha Kartik, Judy Hoffman
(* = equal contribution)

UDIS: Unsupervised Discovery of Bias in Deep Visual Recognition Models

BMVC 2021

Arvind Krishnakumar, Viraj Prabhu, Sruthi Sudhakar, Judy Hoffman

Paper Code
Mitigating Bias in Visual Transformers via Targeted Alignment

BMVC 2021

Sruthi Sudhakar, Viraj Prabhu, Arvind Krishnakumar, Judy Hoffman

Selective Entropy Optimization via Committee Consistency for Unsupervised Domain Adaptation

ICCV 2021

Viraj Prabhu, Shivam Khare, Deeksha Kartik, Judy Hoffman

Paper Project Page Code Video Slides Poster
Active Domain Adaptation via Clustering Uncertainty-weighted Embeddings

ICCV 2021

Viraj Prabhu, Arjun Chandrasekaran, Kate Saenko, Judy Hoffman

Paper Project Page Code Video Slides Poster
Open Set Medical Diagnosis

ML4H workshop at NeurIPS 2019

Viraj Prabhu, Anitha Kannan, Geoffrey J. Tso, Namit Katariya, Manish Chablani, David Sontag, Xavier Amatriain

Few-shot Learning for Dermatological Disease Diagnosis

MLHC 2019 (spotlight), ML4H workshop at NeurIPS 2018

Viraj Prabhu, Anitha Kannan, Murali Ravuri, Manish Chablani, David Sontag, Xavier Amatriain

Do Explanations make VQA Models more Predictable to a Human?

EMNLP 2018, Chalearn Looking at People Workshop, CVPR 2017

Arjun Chandrasekaran*, Viraj Prabhu*, Deshraj Yadav*, Prithvijit Chattopadhyay*, Devi Parikh
(* = equal contribution)

The Promise of Premise: Harnessing Question Premises in Visual Question Answering

EMNLP 2017

Aroma Mahendru*, Viraj Prabhu*, Akrit Mohapatra*, Dhruv Batra, Stefan Lee
(* equal contribution)

Paper Code Dataset
Evaluating Visual Conversational Agents via Cooperative Human-AI Games

HCOMP 2017

Prithvijit Chattopadhyay*, Deshraj Yadav*, Viraj Prabhu, Arjun Chandrasekaran, Abhishek Das, Stefan Lee, Dhruv Batra, Devi Parikh

Paper Code


Fabrik: An Online Collaborative Neural Network Editor

Utsav Garg, Viraj Prabhu, Deshraj Yadav, Ram Ramrakhya, Harsh Agrawal, Dhruv Batra

Lead mentor on Fabrik, an open-source web platform to collaboratively build, visualize, and design neural networks in the browser.

Report Code
PyTorch implementation of Learning Cooperative Visual Dialog Agents with Deep Reinforcement Learning

Nirbhay Modhe, Viraj Prabhu, Michael Cogswell, Satwik Kottur, Abhishek Das, Stefan Lee, Devi Parikh, Dhruv Batra

Adobe Captivate Prime

During my time as a software developer at Adobe (Aug '15-'16), I was responsible for the Captivate Prime Android app through two release cycles. I developed features for offline content play-back, syncing, and UI.

Automated camera calibration and boresighting

Over a research internship at Tonbo Imaging (Spring '15), I designed an algorithm for automated camera calibration and implemented a boresighting algorithm for the company's video precision boresight tool.


Over an internship at Adobe, I co-developed KeyframeCut, a fast graphcut-based segmentation algorithm for real-time background substitution in video. Transferred into Magic Green Screen, the marquee feature of Adobe Presenter Video Express 11.

Demo Blog