Sriram Yenamandra

Sriram Yenamandra

I am a first year Computer Science PhD student at Stanford University advised by Prof. Dorsa Sadigh. I completed my Master's degree in Computer Science (Machine Learning specialization) from Georgia Tech. During my Master's degree, I worked in Prof. Dhruv Batra's lab on solving embodied mobile manipulation tasks. At Georgia Tech, I also had the privilege of being advised by Prof. Judy Hoffman on the problems of visual domain adaptation and bias identification.

Before coming to Georgia Tech, I earned my bachelor's degree in Computer Science and Engineering with a minor in Applied Statistics from IIT Bombay, where I worked on the problem of image inpainting under the supervision of Prof. Suyash Awate.

Email / CV / Google Scholar / Twitter / Github

News

[May 2025] Recognized as an Outstanding Reviewer for Computer Vision and Pattern Recognition (CVPR) 2025!

Publications	(*=equal contribution)
	GOAT: GO to Any Thing Matthew Chang, Theophile Gervet, Mukul Khanna, Sriram Yenamandra*, Dhruv Shah, So Yeon Min, Kavit Shah, Chris Paxton, Saurabh Gupta, Dhruv Batra, Roozbeh Mottaghi, Jitendra Malik, Devendra Singh Chaplot* RSS 2024 arXiv / code
	LANCE: Stress-testing Visual Models by Generating Language-guided Counterfactual Images Viraj Prabhu, Sriram Yenamandra, Prithvijit Chattopadhyay, Judy Hoffman NeurIPS 2023 arXiv / code
	HomeRobot: Open Vocabulary Mobile Manipulation Sriram Yenamandra, Arun Ramachandran, Karmesh Yadav, Austin Wang, Mukul Khanna, Theophile Gervet, Tsung-Yen Yang, Vidhi Jain, Alexander William Clegg, John Turner, Zsolt Kira, Manolis Savva, Angel Chang, Devendra Singh Chaplot, Dhruv Batra, Roozbeh Mottaghi, Yonatan Bisk, Chris Paxton CoRL 2023* arXiv / code
	FACTS: First Amplify Correlations and Then Slice to Discover Bias Sriram Yenamandra, Pratik Ramesh, Viraj Prabhu, Judy Hoffman ICCV 2023 arXiv / code
	Adapting Self-Supervised Vision Transformers by Probing Attention-Conditioned Masking Consistency Viraj Prabhu, Sriram Yenamandra, Aaditya Singh, Judy Hoffman NeurIPS, 2022 arXiv / code
	Housekeep: Tidying Virtual Households using Commonsense Reasoning Yash Kant, Arun Ramachandran, Sriram Yenamandra, Igor Gilitschenski, Dhruv Batra, Andrew Szot, and Harsh Agrawal ECCV, 2022 project page / arXiv / code / colab
	Semi-Supervised Deep Expectation-Maximization for Low-Dose PET-CT Vatsala Sharma, Ansh Khurana, Sriram Yenamandra, Suyash P. Awate ISBI, 2022 (Best paper award) paper
	Learning Image Inpainting from Incomplete Images using Self-Supervision Sriram Yenamandra, Ansh Khurana, Rohit Jena, Suyash P. Awate ICPR, 2020 paper

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