I am a Machine Learning PhD student at Georgia Tech advised by Zsolt Kira and Dhruv Batra. I am interested in embodied AI and reinforcement learning. From Summer 2022 to Winter of 2022, I interned at Meta AI working with Akshara Rai and Ruta Desai. From Summer to Winter of 2021 I interned at Meta AI working with Franziska Meier on inverse reinforcement learning. I completed my undergrad in Computer Science at the University of Southern California with a minor in Mathematics, where I worked with Joseph Lim. My email is "andrewszot 1 @ gmail com" (no spaces).
Research

Adaptive Coordination in Social Embodied Rearrangement
Andrew Szot, Unnat Jain, Dhruv Batra, Zsolt Kira, Ruta Desai, Akshara Rai
Andrew Szot, Unnat Jain, Dhruv Batra, Zsolt Kira, Ruta Desai, Akshara Rai
ICML 2023
[PDF Coming Soon]

Galactic: Scaling End-to-End Reinforcement Learning for Rearrangement at 100k Steps-Per-Second
Vincent-Pierre Berges*, Andrew Szot*, Devendra Singh Chaplot, Aaron Gokaslan, Roozbeh Mottaghi, Dhruv Batra, Eric Undersander (* - equal contribution)
Vincent-Pierre Berges*, Andrew Szot*, Devendra Singh Chaplot, Aaron Gokaslan, Roozbeh Mottaghi, Dhruv Batra, Eric Undersander (* - equal contribution)
CVPR 2023
[PDF Coming Soon]

BC-IRL: Learning Generalizable Reward Functions from Demonstrations
Andrew Szot, Amy Zhang, Dhruv Batra, Zsolt Kira, Franziska Meier
Andrew Szot, Amy Zhang, Dhruv Batra, Zsolt Kira, Franziska Meier
ICLR 2023 (Spotlight, top 8% of 4900 submissions)
[PDF]

Retrospectives on the Embodied AI Workshop
Matt Deitke, Dhruv Batra, Yonatan Bisk, Tommaso Campari, Angel X. Chang, Devendra Singh Chaplot, Changan Chen, Claudia Pérez D'Arpino, Kiana Ehsani, Ali Farhadi, Li Fei-Fei, Anthony Francis, Chuang Gan, Kristen Grauman, David Hall, Winson Han, Unnat Jain, Aniruddha Kembhavi, Jacob Krantz, Stefan Lee, Chengshu Li, Sagnik Majumder, Oleksandr Maksymets, Roberto Martín-Martín, Roozbeh Mottaghi, Sonia Raychaudhuri, Mike Roberts, Silvio Savarese, Manolis Savva, Mohit Shridhar, Niko Sünderhauf, Andrew Szot, Ben Talbot, Joshua B. Tenenbaum, Jesse Thomason, Alexander Toshev, Joanne Truong, Luca Weihs, Jiajun Wu
Matt Deitke, Dhruv Batra, Yonatan Bisk, Tommaso Campari, Angel X. Chang, Devendra Singh Chaplot, Changan Chen, Claudia Pérez D'Arpino, Kiana Ehsani, Ali Farhadi, Li Fei-Fei, Anthony Francis, Chuang Gan, Kristen Grauman, David Hall, Winson Han, Unnat Jain, Aniruddha Kembhavi, Jacob Krantz, Stefan Lee, Chengshu Li, Sagnik Majumder, Oleksandr Maksymets, Roberto Martín-Martín, Roozbeh Mottaghi, Sonia Raychaudhuri, Mike Roberts, Silvio Savarese, Manolis Savva, Mohit Shridhar, Niko Sünderhauf, Andrew Szot, Ben Talbot, Joshua B. Tenenbaum, Jesse Thomason, Alexander Toshev, Joanne Truong, Luca Weihs, Jiajun Wu
Preprint 2022
[PDF]

Housekeep: Tidying Virtual Households using Commonsense Reasoning
Yash Kant, Arun Ramachandran, Sriram Yenamandra, Igor Gilitschenski, Dhruv Batra, Andrew Szot*, Harsh Agrawal* (* - equal advising)
Yash Kant, Arun Ramachandran, Sriram Yenamandra, Igor Gilitschenski, Dhruv Batra, Andrew Szot*, Harsh Agrawal* (* - equal advising)

Habitat 2.0: Training Home Assistants to Rearrange their Habitat
Andrew Szot, Alex Clegg, Eric Undersander, Erik Wijmans, Yili Zhao, John Turner, Noah Maestre, Mustafa Mukadam, Devendra Chaplot, Oleksandr Maksymets, Aaron Gokaslan, Vladimir Vondrus, Sameer Dharur, Franziska Meier, Wojciech Galuba, Angel Chang, Zsolt Kira, Vladlen Koltun, Jitendra Malik, Manolis Savva, Dhruv Batra
Andrew Szot, Alex Clegg, Eric Undersander, Erik Wijmans, Yili Zhao, John Turner, Noah Maestre, Mustafa Mukadam, Devendra Chaplot, Oleksandr Maksymets, Aaron Gokaslan, Vladimir Vondrus, Sameer Dharur, Franziska Meier, Wojciech Galuba, Angel Chang, Zsolt Kira, Vladlen Koltun, Jitendra Malik, Manolis Savva, Dhruv Batra

Goal-Driven Imitation Learning from Observation by Inferring
Goal Proximity
Youngwoon Lee*, Andrew Szot*, Shao-hua Sun and Joseph J. Lim (* - equal contribution)
Youngwoon Lee*, Andrew Szot*, Shao-hua Sun and Joseph J. Lim (* - equal contribution)
NeurIPS 2021
[PDF]
Experience
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Meta AI:
With Akshara Rai and Ruta Desai.
Working on multi-agent reinforcement learning (work in progress).
Summer 2022 - Present
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Facebook AI Research:
With Franziska Meier.
Developed a new inverse reinforcement learning method for learning generalizable reward functions (work under submission).
Summer 2021 - Winter 2021
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USC CLVR Lab:
With Professor Joseph Lim.
Researched imitation from observation (published at NeurIPS 2021), generalization to new actions in reinforcement learning (published at ICML 2020), and benchmarks for tool usage and physical reasoning in RL.
Fall 2018 - Summer 2020 (Summer 2019 included)
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USC MCL:
With Professor C.-C. Jay Kuo.
Researched weakly supervised CNNs using clustering approaches to pre-train.
Fall 2016 - Winter 2017
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Airbnb:
Deployed a model to production that predicted and took automated action against account takeover fraud using Scikit-learn, XGBoost, Hive and Presto, resulting in a 50% reduction in account takeover fraud.
Summer 2018
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eBay:
Delivered a data analytics platform using Scala, Spark, Hadoop and Druid to process petabytes of eBay metrics.
Summer 2017
Awards
- Georgia Tech Institute-Wide Outstanding Online Teaching Assistant of the Year (2021)
- NSF GRFP Honorable Mention. (2021)
- USC Viterbi Fellowship: Research funding given to the top 20 engineering students per class. (2016-2020)
- USC Trustee Scholarship: Full tuition scholarship. (2016-2020)
- USC Provost Fellowship: Merit based fellowship for summer research funding. (2019)
Service and Teaching
- Lead organizer of Habitat Rearrangement Challenge at NeurIPS 2022.
- Organizer of Embodied AI Workshop at CVPR 2022.
- Graduate Deep Learning Class Teaching Assistant (CS 7643, won outstanding TA award). See the homework assignment I created for the class. (Fall 2021)
- Reviewer: ICCV 2021, IROS 2021, ICLR 2022, CVPR 2022.
Press Coverage
Habitat 2.0
- CNET: How Facebook’s AI is training home robots to tackle the chores you hate
- TechCrunch: Facebook and Matterport collaborate on realistic virtual training environments for AI
- VentureBeat: Facebook updates Habitat environment to train ’embodied AI’”
- Culture Geek (broadcast, France): Facebook wants to put butler robots in our homes
- WIRED (Middle East): Facebook wants to train robot butlers to tidy your house
- Siècle Digital (France): Facebook unveils Habitat 2.0: a virtual environment to train AI to navigate a house
- Ynet (Israel): Shopping Assistants and Home Robots: The Future of Artificial Intelligence According to Facebook