Research Scientist
FAIR, Meta AI
abhshkdz at meta dot com

News

• [Feb 22] Runner-up for the 2020 AAAI/ACM SIGAI Doctoral Dissertation Award.
• [Mar 21] Awarded the Georgia Tech Sigma Xi Best PhD Thesis Award.
• [Mar 21] Awarded the Georgia Tech College of Computing Dissertation Award.
• [Nov 20] The Open Catalyst Project was covered by Fortune, Engadget, CNBC, VentureBeat.
• [Nov 20] Organizing the 4th Visually-Grounded Interaction & Language Workshop at NAACL.
• [July 20] Presenting Probing Emergent Semantics in Predictive Agents at ICML 2020 (Video).
• [Mar 20] I completed my PhD! My thesis, “Building agents that can see, talk, and act”, is here.
• [Nov 19] Organizing the Visual Question Answering and Dialog workshop at CVPR 2020.
• [Sep 19] Organizing the Visually-Grounded Interaction & Language Workshop at NeurIPS.
• [Jun 19] Presenting Targeted Multi-Agent Communication as an oral at ICML 2019 (Video).
• [Mar 19] Co-founded Caliper. Caliper helps recruiters evaluate practical AI skills.
• [Feb 19] My work was featured in this wonderful article by Georgia Tech.
• [Jan 19] Awarded the Facebook Graduate Fellowship.
• [Jan 19] Awarded the Microsoft Research PhD Fellowship (declined).
• [Jan 19] Awarded the NVIDIA Graduate Fellowship (declined).
• [Jan 19] Organizing the 2nd Visual Dialog Challenge.
• [Oct 18] Presenting Neural Modular Control for Embodied QA at CoRL 2018 (Video).
• [Sep 18] Presenting results and analysis of the 1st Visual Dialog Challenge at ECCV 2018.
• [Jul 18] Presenting a tutorial on Connecting Language and Vision to Actions at ACL 2018.
• [Jun 18] Organizing the 1st Visual Dialog Challenge.
• [Jun 18] Presenting Embodied Question Answering as an oral at CVPR 2018 (Video).
• [Jun 18] Organizing the VQA Challenge and Visual Dialog Workshop at CVPR 2018.
• [Mar 18] Speaking on Embodied Question Answering at NVIDIA GTC (Video).
• [Dec 17] Awarded the Adobe Research Fellowship. (Department’s news story)
• [Dec 17] Awarded the Snap Inc. Research Fellowship. (Department’s news story)
• [Oct 17] Presenting Cooperative Visual Dialog Agents as an oral at ICCV 2017 (Video).
• [Jul 17] Presenting Visual Dialog at the VQA Challenge Workshop, CVPR 2017 (Video).
• [Jul 17] Presenting our paper on Visual Dialog as a spotlight at CVPR 2017 (Video).

Bio

I am a Research Scientist at Fundamental AI Research (FAIR) at Meta AI working on deep neural networks and its applications in climate change. My current focus is on electrocatalyst discovery for renewable energy storage as part of the Open Catalyst Project. Renewable energy sources (like solar, wind) are great but intermittent – the sun shines only during the day. During the evening, we fall back on fossil fuels. To avoid this, we need to discover cheap, scalable ways of converting electricity from renewable sources to storable forms, so that we can transfer it from times of peak generation to peak demand. AI can help accelerate the chemical simulations needed to make these discoveries.

Before this, I was a Computer Science PhD student at Georgia Tech, advised by Dhruv Batra, and working closely with Devi Parikh, where I focused on developing artificial agents that can see (computer vision), talk (language modeling), and act (reinforcement learning).

IIT Roorkee
2011 - 2015

Queensland Brain Institute
Summer 2015

Virginia Tech
2015 - 2016

Georgia Tech
2017 - 2020

Facebook AI Research
S2017, W2018, S2018

DeepMind
Winter 2019

Tesla Autopilot
Summer 2019

Facebook AI Research
Present

During my PhD, I interned thrice at Facebook AI Research — Summer 2017 and Spring 2018 at Menlo Park, working with Georgia Gkioxari, Devi Parikh and Dhruv Batra on training embodied agents for navigation and question-answering in simulated environments (see embodiedqa.org), and Summer 2018 at Montréal, working with Mike Rabbat and Joelle Pineau on communication protocols in multi-agent reinforcement learning. In 2019, I interned at DeepMind in London working on grounded language learning with Felix Hill, Laura Rimell, and Stephen Clark, and at Tesla Autopilot in Palo Alto working on differentiable neural architecture search with Andrej Karpathy.

My PhD research was supported by fellowships from Facebook, Adobe, and Snap.

Prior to joining grad school, I worked on neural coding in zebrafish tectum as an intern under Prof. Geoffrey Goodhill and Lilach Avitan at the Goodhill Lab, Queensland Brain Institute.

I got my Bachelor’s at IIT Roorkee in 2015. During my undergrad, I took part in Google Summer of Code (2013 and 2014), won several competitions (Yahoo! HackU!, Microsoft Code.Fun.Do., Deloitte CCTC 2013 and 2014), and owe most of my programming/tinkering bent to SDSLabs.

On the side, I built aideadlin.es (countdowns to a bunch of CV/NLP/ML/AI conference deadlines) and aipaygrad.es (statistics of industry job offers in AI), neural-vqa and its extension neural-vqa-attention, HackFlowy, graf, Erdős, etc. I also occasionally dabble in generative art. I like this map tracking the places I’ve been to. Blog posts from a previous life.

Publications

AdsorbML: Accelerating Adsorption Energy Calculations with Machine Learning

Janice Lan, Aini Palizhati, Muhammed Shuaibi, Brandon M. Wood, Brook Wander, Abhishek Das, Matt Uyttendaele, C. Lawrence Zitnick, Zachary W. Ulissi
Paper Code

The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysis

Richard Tran*, Janice Lan*, Muhammed Shuaibi*, Siddharth Goyal*, Brandon M. Wood*, Abhishek Das, Javier Heras-Domingo, Adeesh Kolluru, Ammar Rizvi, Nima Shoghi, Anuroop Sriram, Zachary Ulissi, C. Lawrence Zitnick
Paper Code Dataset

"... new dataset for green hydrogen fuel" by Janice, Siddharth, Ammar, Larry

GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets

Johannes Gasteiger, Muhammed Shuaibi, Anuroop Sriram, Stephan Günnemann, Zachary Ulissi, C. Lawrence Zitnick, Abhishek Das
TMLR 2022 Paper Code

Spherical Channels for Modeling Atomic Interactions

C. Lawrence Zitnick, Abhishek Das, Adeesh Kolluru, Janice Lan, Muhammed Shuaibi, Anuroop Sriram, Zachary Ulissi, Brandon Wood
NeurIPS 2022 Paper Code

Open Challenges in Developing Generalizable Large Scale Machine Learning Models for Catalyst Discovery

Adeesh Kolluru*, Muhammed Shuaibi*, Aini Palizhati, Nima Shoghi, Abhishek Das, Brandon Wood, C. Lawrence Zitnick, John R. Kitchin, Zachary Ulissi
ACS Catalysis (Perspective) 2022 Paper

Transfer learning using attentions across atomic systems with graph neural networks (TAAG)

Adeesh Kolluru, Nima Shoghi, Muhammed Shuaibi, Siddharth Goyal, Abhishek Das, C. Lawrence Zitnick, Zachary Ulissi
The Journal of Chemical Physics 2022 Paper Code

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

Ram Ramrakhya, Eric Undersander, Dhruv Batra, Abhishek Das
CVPR 2022 Paper Code Website Presentation video

Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations

Anuroop Sriram, Abhishek Das, Brandon M. Wood, Siddharth Goyal, C. Lawrence Zitnick
ICLR 2022 Paper Code

Rotation Invariant Graph Neural Networks using Spin Convolutions

Muhammed Shuaibi, Adeesh Kolluru, Abhishek Das, Aditya Grover, Anuroop Sriram, Zachary Ulissi, C. Lawrence Zitnick
Paper Code

Automated Video Description for Blind and Low Vision Users

Aditya Bodi, Pooyan Fazli, Shasta Ihorn, Yue-Ting Siu, Andrew T Scott, Lothar Narins, Yash Kant, Abhishek Das, Ilmi Yoon
CHI EA 2021
Paper

Auxiliary Tasks and Exploration Enable ObjectNav

Joel Ye, Dhruv Batra, Abhishek Das, Erik Wijmans
ICCV 2021
Paper Code Website

ForceNet: A Graph Neural Network for Large-Scale Quantum Calculations

Weihua Hu, Muhammed Shuaibi, Abhishek Das, Siddharth Goyal, Anuroop Sriram, Jure Leskovec, Devi Parikh, C. Lawrence Zitnick
ICLR 2021 Deep Learning for Simulation Workshop
Paper opencatalystproject.org Presentation video

The Open Catalyst 2020 (OC20) Dataset and Community Challenges

Lowik Chanussot^*, Abhishek Das^*, Siddharth Goyal^*, Thibaut Lavril^*, Muhammed Shuaibi^*, Morgane Riviére, Kevin Tran, Javier Heras-Domingo, Caleb Ho, Weihua Hu, Aini Palizhati, Anuroop Sriram, Brandon Wood, Junwoong Yoon, Devi Parikh, C. Lawrence Zitnick, Zachary Ulissi
ACS Catalysis 2021
Paper Code Dataset opencatalystproject.org

An Introduction to Electrocatalyst Design using Machine Learning for Renewable Energy Storage

C. Lawrence Zitnick, Lowik Chanussot, Abhishek Das, Siddharth Goyal, Javier Heras-Domingo, Caleb Ho, Weihua Hu, Thibaut Lavril, Aini Palizhati, Morgane Riviére, Muhammed Shuaibi, Anuroop Sriram, Kevin Tran, Brandon Wood, Junwoong Yoon, Devi Parikh, Zachary Ulissi
Paper opencatalystproject.org

"Facebook and Carnegie Mellon launch .. to ... store renewable energy" by Larry Zitnick

"Facebook A.I. researchers push for a breakthrough in renewable energy storage" by Jeremy Kahn

"Facebook deploys its AI to find green energy storage solutions" by Andrew Tarantola

"Facebook to use artificial intelligence in bid to improve renewable energy storage" by Sam Shead

"Facebook and Carnegie Mellon launch project to ... store renewable energy" by Kyle Wiggers

"Facebook plans to use AI to help fight climate change" by Queenie Wong

"Facebook & CMU Open Catalyst Project Applies AI to Renewable Energy Storage" by Fangyu Cai

Auxiliary Tasks Speed Up Learning PointGoal Navigation

Joel Ye, Dhruv Batra, Erik Wijmans*, Abhishek Das*
CoRL 2020
Paper Code

Large-scale Pretraining for Visual Dialog: A Simple State-of-the-Art Baseline

Vishvak Murahari, Dhruv Batra, Devi Parikh, Abhishek Das
ECCV 2020
Paper Code

Building agents that can see, talk, and act

Abhishek Das
PhD Thesis AAAI/ACM SIGAI Doctoral Dissertation Award, Runner-up
Georgia Tech Sigma Xi Best PhD Thesis Award
Georgia Tech College of Computing Dissertation Award

Probing Emergent Semantics in Predictive Agents via Question Answering

Abhishek Das^*, Federico Carnevale^*, Hamza Merzic, Laura Rimell, Rosalia Schneider, Josh Abramson, Alden Hung, Arun Ahuja, Stephen Clark, Gregory Wayne, Felix Hill
ICML 2020
Paper Presentation video Slides

Feel The Music: Automatically Generating A Dance For An Input Song

Purva Tendulkar, Abhishek Das, Aniruddha Kembhavi, Devi Parikh
ICCC 2020
Paper Code Videos

IR-VIC: Unsupervised Discovery of Sub-goals for Transfer in RL

Nirbhay Modhe, Prithvijit Chattopadhyay, Mohit Sharma, Abhishek Das, Devi Parikh, Dhruv Batra, Ramakrishna Vedantam
IJCAI-PRICAI 2020, ICLR 2019 Task-Agnostic RL Workshop
Paper

Improving Generative Visual Dialog by Answering Diverse Questions

Vishvak Murahari, Prithvijit Chattopadhyay, Dhruv Batra, Devi Parikh, Abhishek Das
EMNLP 2019
Paper Code

TarMAC: Targeted Multi-Agent Communication

Abhishek Das, Théophile Gervet, Joshua Romoff, Dhruv Batra, Devi Parikh, Michael Rabbat, Joelle Pineau
ICML 2019
Paper Slides

Embodied Question Answering in Photorealistic Environments with Point Clouds

Erik Wijmans*, Samyak Datta*, Oleksandr Maksymets*, Abhishek Das, Georgia Gkioxari, Stefan Lee, Irfan Essa, Devi Parikh, Dhruv Batra
CVPR 2019 (Oral)
Paper

Audio-Visual Scene-Aware Dialog

Huda Alamri, Vincent Cartillier, Abhishek Das, Jue Wang, Stefan Lee, Peter Anderson, Irfan Essa, Devi Parikh, Dhruv Batra, Anoop Cherian, Tim K. Marks, Chiori Hori
CVPR 2019
Paper Code video-dialog.com

End-to-end Audio Visual Scene-Aware Dialog Using Multimodal Attention-based Video Features

Chiori Hori, Huda Alamri, Jue Wang, Gordon Wichern, Takaaki Hori, Anoop Cherian, Tim K. Marks, Vincent Cartillier, Raphael Lopes, Abhishek Das, Irfan Essa, Dhruv Batra, Devi Parikh
ICASSP 2019
Paper video-dialog.com

Neural Modular Control for Embodied Question Answering

Abhishek Das, Georgia Gkioxari, Stefan Lee, Devi Parikh, Dhruv Batra
CoRL 2018 (Spotlight)
Paper embodiedqa.org Presentation video Slides

Embodied Question Answering

Abhishek Das, Samyak Datta, Georgia Gkioxari, Stefan Lee, Devi Parikh, Dhruv Batra
CVPR 2018 (Oral)
Paper embodiedqa.org Code Presentation video Slides

"Embodied Question Answering" by Abhishek Das

"... a goal-driven approach to autonomous agents" by Dhruv Batra, Devi Parikh

"... an AI scavenger hunt that could lead to the first useful home robots" by Will Knight

Evaluating Visual Conversational Agents via Cooperative Human-AI Games

Prithvijit Chattopadhyay^*, Deshraj Yadav^*, Viraj Prabhu, Arjun Chandrasekaran, Abhishek Das, Stefan Lee, Dhruv Batra, Devi Parikh
HCOMP 2017
Paper Code

Learning Cooperative Visual Dialog Agents with Deep Reinforcement Learning

Abhishek Das^*, Satwik Kottur^*, Stefan Lee, José M.F. Moura, Dhruv Batra
ICCV 2017 (Oral)
Paper Code Presentation video Slides

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, Dhruv Batra
IJCV 2019, ICCV 2017, NIPS 2016 Interpretable ML for Complex Systems Workshop
Paper Code Demo

Visual Dialog

Abhishek Das, Satwik Kottur, Khushi Gupta, Avi Singh, Deshraj Yadav, José M.F. Moura, Devi Parikh, Dhruv Batra
PAMI 2018, CVPR 2017 (Spotlight)
Paper Code visualdialog.org AMT chat interface Demo Presentation video Slides

Human Attention in Visual Question Answering: Do Humans and Deep Networks Look at the Same Regions?

Abhishek Das^*, Harsh Agrawal^*, C. Lawrence Zitnick, Devi Parikh, Dhruv Batra
CVIU 2017, EMNLP 2016, ICML 2016 Workshop on Visualization for Deep Learning
Paper Project+Dataset neural-vqa-attention

"Is Artificial Intelligence Permanently Inscrutable?" by Aaron Bornstein

"Deep learning is creating computer systems we don't fully understand" by James Vincent

"Robot eyes and humans fix on different things to decode a scene" by Aviva Rutkin

"Robots and humans see the world differently – but we don't know why" by Duncan Geere

"AI Is Learning to See the World—But Not the Way Humans Do" by Jamie Condliffe

Talks

Side projects