PhD Student
Georgia Institute of Technology
ram.ramrakhya at gatech dot edu

News


Bio

I am a first year PhD student in the department of Computer Science at Georgia Tech advised by Prof. Dhruv Batra and Prof. Zsolt Kira. Prior to this, I completed my Masters in CS at Georgia Tech advised by Prof. Dhruv Batra and Abhishek Das. I also closely collaborate with Erik Wijmans and Eric Undersander during my time as a MS student.

Broadly, I am interested at the intersection of Computer Vision, Robotics and Reinforcement Learning. My long-term research goal is to develop general scalable algorithms and efficient systems to train embodied agents that exhibit emergent intelligent behavior to accomplish goals in diverse real-world environments.

Meta AI Research
Summer 2024
Allen Insitute of AI (AI2)
Summer 2023
Mitsubishi Electric Research Laborateries
Summer 2022
Georgia Tech
2021 - Current
Glance
2018 - 2021
Pune Institute of Computer Technology
2015 - 2018

During my MS, I was fortunate to intern at Allen Institute of AI (AI2) in Summer 2023 with Luca Weihs and Kuo-Hao Zheng on common-sense and context-based reasoning for embodied agents. At Mitsubishi Electric Research Laborateries (MERL) in Summer 2022 with Anoop Cherian on building embodied agents for navigation and interaction in simulated environments that leverage 3D scene graphs for effective scene understanding.

Previously, I spent a year working as a Research Intern in Computer Vision and Machine Learning Perception Lab at Georgia Tech advised by Prof. Dhruv Batra and Prof. Devi Parikh. I also lead an open source organization, CloudCV, where we are building several open-source softwares for reproducible AI research.

If you have any questions / want to collaborate / discuss research, feel free to send me an email at ram.ramrakhya@gatech.edu.


Publications

Seeing the Unseen: Visual Common Sense for Semantic Placement

Ram Ramrakhya, Aniruddha Kembhavi, Dhruv Batra, Zsolt Kira, Kuo-Hao Zeng^, Luca Weihs^
CVPR 2024, VLMNM workshop at ICRA'24 Paper Code Website


GOAT-Bench: A Benchmark for Multi-Modal Lifelong Navigation

Mukul Khanna*, Ram Ramrakhya*, Gunjan Chhablani, Sriram Yenamandra, Theophile Gervet, Matthew Chang, Zsolt Kira, Devendra Singh Chaplot, Dhruv Batra, Roozbeh Mottaghi
CVPR 2024 Paper Code Website


PIRLNav: Pretraining with Imitation and RL Finetuning for ObjectNav

Ram Ramrakhya, Dhruv Batra, Erik Wijmans, Abhishek Das
CVPR 2023, RRL workshop at ICLR 2023 Paper Code Website


Habitat-Matterport 3D Semantics Dataset

Karmesh Yadav*, Ram Ramrakhya*, Santhosh Kumar Ramakrishnan*, Theo Gervet, John Turner, Aaron Gokaslan, Noah Maestre, Angel Xuan Chang, Dhruv Batra, Manolis Savva, Alexander William Clegg^, Devendra Singh Chaplot^
CVPR 2023 (Highlight, top 2.5% of submissions) Paper Website


OVRL-V2: A simple state-of-art baseline for ImageNav and ObjectNav

Karmesh Yadav*, Arjun Majumdar*, Ram Ramrakhya, Naoki Yokoyama, Aleksei Baevski, Zsolt Kira, Oleksandr Makysmets, Dhruv Batra
arxiv Paper


Habitat-Web: Learning Embodied Object-Search Strategies from Human Demonstrations at Scale

Ram Ramrakhya, Eric Undersander, Dhruv Batra, Abhishek Das
CVPR 2022, EmbodiedAI workshop at CVPR 2022, Overlooked Aspects of IL workshop at RSS 2022 (Spotlight) Paper Code Website Presentation video


Offline Visual Representation Learning for Embodied Navigation

Karmesh Yadav, Ram Ramrakhya, Arjun Majumdar, Vincent-Pierre Berges, Sachit Kuhar, Dhruv Batra, Aleksei Baevski, Oleksandr Makysmet
RRL workshop at ICLR 2023 Paper


Fabrik: An Online Collaborative Neural Network Editor

Utsav Garg, Viraj Prabhu, Deshraj Yadav, Ram Ramrakhya, Harsh Agarwal, Dhruv Batra
Workshop on AI Systems, SOSP'2019 Paper Code


Projects

EvalAI

Leading open source platform for evaluating and benchmarking AI models. We have hosted 200+ AI challenges with 18,000+ users, who have created 180,000+ submissions. More than 30 organizations from industry and academia use it for hosting their AI challenges. The project is open source with 130+ contributors, and 2M+ yearly pageviews. Some of the organizations using it are Google Research, Facebook AI Research, DeepMind, Amazon, eBay Research, Mapillary Research, etc. and research labs from MIT, Stanford, Carnegie Mellon University, Georgia Tech, Virginia Tech, UMBC, University of Pittsburg, Draper, University of Adelaide, IIT-Madras, Nankai University, etc. also use it to host large AI challenges like AlexaPrize on it. It's forked versions are used by large organizations such as World Health Organization, Forschungszentrum J├╝lich (one of the largest interdisciplinary research centres in Europe), etc. for hosting their challenges instead of reinventing the wheel.

Fabrik

Fabrik is an online collaborative platform to build, visualize and train deep learning models via a simple drag-and-drop interface. It allows researchers to collectively develop and debug models using a web GUI that supports importing, editing and exporting networks to popular frameworks like Caffe, Keras, and TensorFlow.


(Courtesy: Abhishek Das)