Carl Vondrick - Professor of Computer Science at Columbia University

Carl Vondrick

YM Associate Professor of Computer Science
Columbia University

618 Schapiro CEPSR
530 West 120th St, New York, NY 10027

Google Scholar·CV·Ceramics


Brief Bio

I am a professor of computer science at Columbia, where I am a member of the Columbia Core AI Lab (CAIL). I am also a researcher at Apple.

I was previously a research scientist at Google and a visiting researcher at Cruise. I completed my PhD at MIT in 2017 advised by Antonio Torralba and my BS at UC Irvine in 2011, where I got my start working with Deva Ramanan.

I received the 2024 PAMI Young Researcher Award and the 2021 NSF CAREER Award. I served as Senior Program Chair for ICLR in 2025 and General Chair in 2026, and currently sit on the board.

Research

By training machines to observe and interact with their surroundings, our research aims to create robust and versatile models for perception. Our lab often investigates visual models that capitalize on large amounts of unlabeled data and transfer across tasks and modalities. Other interests include robotics, interpretable models, and other modalities such as sound, language, and beyond.

The lab recruits one or two PhD students each year. Prospective PhD students should apply to the PhD program. Due to the volume of email we receive, we unfortunately cannot respond to emails about applications.


PhD Students and Postdocs

Photo of Arjun Mani, PhD student at Columbia University Arjun Mani Photo of Junbang Liang, PhD student at Columbia University Junbang Liang Photo of Lennart Schulze, PhD student at Columbia University Lennart Schulze Photo of Sreehari Rammohan, PhD student at Columbia University Sreehari Rammohan Photo of Sruthi Sudhakar, PhD student at Columbia University Sruthi Sudhakar

Graduated PhD Students and Former Postdocs


Papers

Our research creates perception systems with diverse skills, including spatial, physical, logical, and reasoning abilities, for flexibly analyzing visual data. Our multimodal approach provides versatile representations for tasks like 3D reconstruction, visual question answering, and robot manipulation, while offering inherent explainability and excellent zero-shot generalization. The below papers highlight key examples of these capabilities.

Recent

Teaser for LookThere! Sparse Vision by Reinforced Selection

LookThere! Sparse Vision by Reinforced Selection
Sreehari Rammohan, Yousef Yassin, Anthony Fuller, Junfeng Wen, Carl Vondrick, Evan Shelhamer
arXiv 2026

@article{rammohan2026lookthere,
  title={LookThere! Sparse Vision by Reinforced Selection},
  author={Sreehari Rammohan and Yousef Yassin and Anthony Fuller and Junfeng Wen and Carl Vondrick and Evan Shelhamer},
  journal={arXiv 2026},
  year={2026},
  url={https://arxiv.org/abs/2609.04698}
}
Teaser for Robot Critics that Sweat the Small Stuff

Robot Critics that Sweat the Small Stuff
Sruthi Sudhakar, Junbang Liang, Sreehari Rammohan, Pavel Tokmakov, Richard Zemel, Carl Vondrick
arXiv 2026

@article{sudhakar2026robot,
  title={Robot Critics that Sweat the Small Stuff},
  author={Sruthi Sudhakar and Junbang Liang and Sreehari Rammohan and Pavel Tokmakov and Richard Zemel and Carl Vondrick},
  journal={arXiv 2026},
  year={2026},
  url={https://robocritic.cs.columbia.edu}
}
Teaser for A²: Smaller Self-Supervised ViTs Localize Better than Larger Ones

A²: Smaller Self-Supervised ViTs Localize Better than Larger Ones
Sreehari Rammohan, Huy Ha, Carl Vondrick
arXiv 2026

@article{rammohan2026a,
  title={A²: Smaller Self-Supervised ViTs Localize Better than Larger Ones},
  author={Sreehari Rammohan and Huy Ha and Carl Vondrick},
  journal={arXiv 2026},
  year={2026},
  url={https://arxiv.org/abs/2606.03148}
}
Teaser for Do multimodal models imagine electric sheep?

Do multimodal models imagine electric sheep?
Santhosh Kumar Ramakrishnan, Carl Vondrick, Raja Giryes, Philipp Krähenbühl, Vladlen Koltun
arXiv 2026

@article{ramakrishnan2026do,
  title={Do multimodal models imagine electric sheep?},
  author={Santhosh Kumar Ramakrishnan and Carl Vondrick and Raja Giryes and Philipp Krähenbühl and Vladlen Koltun},
  journal={arXiv 2026},
  year={2026},
  url={https://arxiv.org/abs/2605.09693}
}
Teaser for Few-Shot Design Optimization by Exploiting Auxiliary Information

Few-Shot Design Optimization by Exploiting Auxiliary Information
Arjun Mani, Carl Vondrick, Richard Zemel
ICML 2026

@inproceedings{mani2026fewshot,
  title={Few-Shot Design Optimization by Exploiting Auxiliary Information},
  author={Arjun Mani and Carl Vondrick and Richard Zemel},
  booktitle={ICML 2026},
  year={2026},
  url={https://designopt.cs.columbia.edu}
}
Teaser for New York Smells: A Large Multimodal Dataset for Olfaction

New York Smells: A Large Multimodal Dataset for Olfaction
Ege Ozguroglu, Junbang Liang, Ruoshi Liu, Mia Chiquier, Michael DeTienne, Wesley Wei Qian, Alexandra Horowitz, Andrew Owens, Carl Vondrick
arXiv 2025

@article{ozguroglu2025new,
  title={New York Smells: A Large Multimodal Dataset for Olfaction},
  author={Ege Ozguroglu and Junbang Liang and Ruoshi Liu and Mia Chiquier and Michael DeTienne and Wesley Wei Qian and Alexandra Horowitz and Andrew Owens and Carl Vondrick},
  journal={arXiv 2025},
  year={2025},
  url={https://smell.cs.columbia.edu}
}

Robotics

Multi-modal learning for robotic perception and action.

Teaser for Video Generators are Robot Policies

Video Generators are Robot Policies
Junbang Liang, Pavel Tokmakov, Ruoshi Liu, Sruthi Sudhakar, Paarth Shah, Rares Ambrus, Carl Vondrick
arXiv 2025

@article{liang2025video,
  title={Video Generators are Robot Policies},
  author={Junbang Liang and Pavel Tokmakov and Ruoshi Liu and Sruthi Sudhakar and Paarth Shah and Rares Ambrus and Carl Vondrick},
  journal={arXiv 2025},
  year={2025},
  url={https://arxiv.org/abs/2508.00795}
}
Teaser for Self-Improving Autonomous Underwater Manipulation

Self-Improving Autonomous Underwater Manipulation
Ruoshi Liu, Huy Ha, Mengxue Hou, Shuran Song, Carl Vondrick
ICRA 2025

@article{liu2025selfimproving,
  title={Self-Improving Autonomous Underwater Manipulation},
  author={Ruoshi Liu and Huy Ha and Mengxue Hou and Shuran Song and Carl Vondrick},
  journal={ICRA 2025},
  year={2025},
  url={https://aquabot.cs.columbia.edu}
}
Teaser for Dreamitate: Real-World Visuomotor Policy Learning via Video Generation

Dreamitate: Real-World Visuomotor Policy Learning via Video Generation
Junbang Liang*, Ruoshi Liu*, Ege Ozguroglu, Sruthi Sudhakar, Achal Dave, Pavel Tokmakov, Shuran Song, Carl Vondrick
CoRL 2024

@inproceedings{liang2024dreamitate,
  title={Dreamitate: Real-World Visuomotor Policy Learning via Video Generation},
  author={Junbang Liang and Ruoshi Liu and Ege Ozguroglu and Sruthi Sudhakar and Achal Dave and Pavel Tokmakov and Shuran Song and Carl Vondrick},
  booktitle={CoRL 2024},
  year={2024},
  url={https://dreamitate.cs.columbia.edu}
}
Teaser for PaperBot: Learning to Design Real-World Tools Using Paper

PaperBot: Learning to Design Real-World Tools Using Paper
Ruoshi Liu, Junbang Liang, Sruthi Sudhakar, Huy Ha, Cheng Chi, Shuran Song, Carl Vondrick
arXiv 2024

@article{liu2024paperbot,
  title={PaperBot: Learning to Design Real-World Tools Using Paper},
  author={Ruoshi Liu and Junbang Liang and Sruthi Sudhakar and Huy Ha and Cheng Chi and Shuran Song and Carl Vondrick},
  journal={arXiv 2024},
  year={2024},
  url={https://paperbot.cs.columbia.edu}
}

Interpretability

Explainable-by-construction methods that let people audit and reprogram perception.

Teaser for SelfIE: Self-Interpretation of Large Language Model Embeddings

SelfIE: Self-Interpretation of Large Language Model Embeddings
Haozhe Chen, Carl Vondrick, Chengzhi Mao
ICML 2024

@inproceedings{chen2024selfie,
  title={SelfIE: Self-Interpretation of Large Language Model Embeddings},
  author={Haozhe Chen and Carl Vondrick and Chengzhi Mao},
  booktitle={ICML 2024},
  year={2024},
  url={https://selfie.cs.columbia.edu}
}
Teaser for ViperGPT: Visual Inference via Python Execution for Reasoning

ViperGPT: Visual Inference via Python Execution for Reasoning
Dídac Surís*, Sachit Menon*, Carl Vondrick
ICCV 2023 (Oral)

@inproceedings{surís2023vipergpt,
  title={ViperGPT: Visual Inference via Python Execution for Reasoning},
  author={Dídac Surís and Sachit Menon and Carl Vondrick},
  booktitle={ICCV 2023 (Oral)},
  year={2023},
  url={https://viper.cs.columbia.edu}
}
Teaser for Visual Classification via Description from Large Language Models

Visual Classification via Description from Large Language Models
Sachit Menon, Carl Vondrick
ICLR 2023 (Oral)

@inproceedings{menon2023visual,
  title={Visual Classification via Description from Large Language Models},
  author={Sachit Menon and Carl Vondrick},
  booktitle={ICLR 2023 (Oral)},
  year={2023},
  url={https://arxiv.org/abs/2210.07183}
}
Teaser for HOGgles: Visualizing Object Detection Features

HOGgles: Visualizing Object Detection Features
Carl Vondrick, Aditya Khosla, Tomasz Malisiewicz, Antonio Torralba
ICCV 2013 (Oral)

@inproceedings{vondrick2013hoggles,
  title={HOGgles: Visualizing Object Detection Features},
  author={Carl Vondrick and Aditya Khosla and Tomasz Malisiewicz and Antonio Torralba},
  booktitle={ICCV 2013 (Oral)},
  year={2013},
  url={https://www.cs.columbia.edu/~vondrick/ihog}
}

AI4Science

Visual methods to accelerate scientific discovery.

Teaser for Teaching Humans Subtle Differences with DIFF-usion

Teaching Humans Subtle Differences with DIFF-usion
Mia Chiquier*, Orr Avrech*, Yossi Gandelsman, Berthy Feng, Katherine Bouman, Carl Vondrick
arXiv 2025

@article{chiquier2025teaching,
  title={Teaching Humans Subtle Differences with DIFF-usion},
  author={Mia Chiquier and Orr Avrech and Yossi Gandelsman and Berthy Feng and Katherine Bouman and Carl Vondrick},
  journal={arXiv 2025},
  year={2025},
  url={https://diff-usion.cs.columbia.edu}
}
Teaser for DiSciPLE: Learning Interpretable Programs for Scientific Visual Discovery

DiSciPLE: Learning Interpretable Programs for Scientific Visual Discovery
Utkarsh Mall, Cheng Perng Phoo, Mia Chiquier, Bharath Hariharan, Kavita Bala, Carl Vondrick
CVPR 2025

@inproceedings{mall2025disciple,
  title={DiSciPLE: Learning Interpretable Programs for Scientific Visual Discovery},
  author={Utkarsh Mall and Cheng Perng Phoo and Mia Chiquier and Bharath Hariharan and Kavita Bala and Carl Vondrick},
  booktitle={CVPR 2025},
  year={2025},
  url={https://disciple.cs.columbia.edu}
}

Learning from Video

Learning perceptual skills from unlabeled video without manual supervision.

Teaser for Tracking through Containers and Occluders in the Wild

Tracking through Containers and Occluders in the Wild
Basile Van Hoorick, Pavel Tokmakov, Simon Stent, Jie Li, Carl Vondrick
CVPR 2023

@inproceedings{hoorick2023tracking,
  title={Tracking through Containers and Occluders in the Wild},
  author={Basile Van Hoorick and Pavel Tokmakov and Simon Stent and Jie Li and Carl Vondrick},
  booktitle={CVPR 2023},
  year={2023},
  url={https://tcow.cs.columbia.edu}
}
Teaser for Representing Spatial Trajectories as Distributions

Representing Spatial Trajectories as Distributions
Dídac Surís, Carl Vondrick
NeurIPS 2022

@inproceedings{surís2022representing,
  title={Representing Spatial Trajectories as Distributions},
  author={Dídac Surís and Carl Vondrick},
  booktitle={NeurIPS 2022},
  year={2022},
  url={https://trajectories.cs.columbia.edu}
}
Teaser for VideoBERT: A Joint Model for Video and Language Representation Learning

VideoBERT: A Joint Model for Video and Language Representation Learning
Chen Sun, Austin Myers, Carl Vondrick, Kevin Murphy, Cordelia Schmid
ICCV 2019

@inproceedings{sun2019videobert,
  title={VideoBERT: A Joint Model for Video and Language Representation Learning},
  author={Chen Sun and Austin Myers and Carl Vondrick and Kevin Murphy and Cordelia Schmid},
  booktitle={ICCV 2019},
  year={2019},
  url={https://arxiv.org/abs/1904.01766}
}
Teaser for Tracking Emerges by Colorizing Videos

Tracking Emerges by Colorizing Videos
Carl Vondrick, Abhinav Shrivastava, Alireza Fathi, Sergio Guadarrama, Kevin Murphy
ECCV 2018

@inproceedings{vondrick2018tracking,
  title={Tracking Emerges by Colorizing Videos},
  author={Carl Vondrick and Abhinav Shrivastava and Alireza Fathi and Sergio Guadarrama and Kevin Murphy},
  booktitle={ECCV 2018},
  year={2018},
  url={https://arxiv.org/pdf/1806.09594.pdf}
}
Teaser for Assessing the Quality of Actions

Assessing the Quality of Actions
Hamed Pirsiavash, Carl Vondrick, Antonio Torralba
ECCV 2014

@inproceedings{pirsiavash2014assessing,
  title={Assessing the Quality of Actions},
  author={Hamed Pirsiavash and Carl Vondrick and Antonio Torralba},
  booktitle={ECCV 2014},
  year={2014},
  url={https://www.cs.columbia.edu/~vondrick/quality.pdf}
}

Anticipation and Prediction

Models that forecast future events and actions before they happen.

Teaser for Learning the Predictability of the Future

Learning the Predictability of the Future
Dídac Surís*, Ruoshi Liu*, Carl Vondrick
CVPR 2021

@inproceedings{surís2021learning,
  title={Learning the Predictability of the Future},
  author={Dídac Surís and Ruoshi Liu and Carl Vondrick},
  booktitle={CVPR 2021},
  year={2021},
  url={https://arxiv.org/pdf/2101.01600.pdf}
}
Teaser for Oops! Predicting Unintentional Action in Video

Oops! Predicting Unintentional Action in Video
Dave Epstein, Boyuan Chen, Carl Vondrick
CVPR 2020

@inproceedings{epstein2020oops,
  title={Oops! Predicting Unintentional Action in Video},
  author={Dave Epstein and Boyuan Chen and Carl Vondrick},
  booktitle={CVPR 2020},
  year={2020},
  url={https://arxiv.org/pdf/1911.11206.pdf}
}
Teaser for Generating Videos with Scene Dynamics

Generating Videos with Scene Dynamics
Carl Vondrick, Hamed Pirsiavash, Antonio Torralba
NeurIPS 2016

@inproceedings{vondrick2016generating,
  title={Generating Videos with Scene Dynamics},
  author={Carl Vondrick and Hamed Pirsiavash and Antonio Torralba},
  booktitle={NeurIPS 2016},
  year={2016},
  url={https://www.cs.columbia.edu/~vondrick/tinyvideo/}
}
Teaser for Anticipating Visual Representations from Unlabeled Video

Anticipating Visual Representations from Unlabeled Video
Carl Vondrick, Hamed Pirsiavash, Antonio Torralba
CVPR 2016 (Spotlight)

@inproceedings{vondrick2016anticipating,
  title={Anticipating Visual Representations from Unlabeled Video},
  author={Carl Vondrick and Hamed Pirsiavash and Antonio Torralba},
  booktitle={CVPR 2016 (Spotlight)},
  year={2016},
  url={https://www.cs.columbia.edu/~vondrick/prediction}
}

Multimodal

Cross-modal representations linking vision, sound, and language.

Teaser for Globetrotter: Connecting Languages by Connecting Images

Globetrotter: Connecting Languages by Connecting Images
Dídac Surís, Dave Epstein, Carl Vondrick
CVPR 2022 (Oral)

@inproceedings{surís2022globetrotter,
  title={Globetrotter: Connecting Languages by Connecting Images},
  author={Dídac Surís and Dave Epstein and Carl Vondrick},
  booktitle={CVPR 2022 (Oral)},
  year={2022},
  url={https://arxiv.org/pdf/2012.04631.pdf}
}
Teaser for Real-Time Neural Voice Camouflage

Real-Time Neural Voice Camouflage
Mia Chiquier, Chengzhi Mao, Carl Vondrick
ICLR 2022 (Oral)

@inproceedings{chiquier2022realtime,
  title={Real-Time Neural Voice Camouflage},
  author={Mia Chiquier and Chengzhi Mao and Carl Vondrick},
  booktitle={ICLR 2022 (Oral)},
  year={2022},
  url={https://voicecamo.cs.columbia.edu}
}
Teaser for The Boombox: Visual Reconstruction from Acoustic Vibrations

The Boombox: Visual Reconstruction from Acoustic Vibrations
Boyuan Chen, Mia Chiquier, Hod Lipson, Carl Vondrick
CoRL 2021

@inproceedings{chen2021the,
  title={The Boombox: Visual Reconstruction from Acoustic Vibrations},
  author={Boyuan Chen and Mia Chiquier and Hod Lipson and Carl Vondrick},
  booktitle={CoRL 2021},
  year={2021},
  url={https://arxiv.org/abs/2105.08052}
}
Teaser for The Sound of Pixels

The Sound of Pixels
Hang Zhao, Chuang Gan, Andrew Rouditchenko, Carl Vondrick, Josh McDermott, Antonio Torralba
ECCV 2018

@inproceedings{zhao2018the,
  title={The Sound of Pixels},
  author={Hang Zhao and Chuang Gan and Andrew Rouditchenko and Carl Vondrick and Josh McDermott and Antonio Torralba},
  booktitle={ECCV 2018},
  year={2018},
  url={https://arxiv.org/abs/1804.03160}
}
Teaser for SoundNet: Learning Sound Representations from Unlabeled Video

SoundNet: Learning Sound Representations from Unlabeled Video
Yusuf Aytar*, Carl Vondrick*, Antonio Torralba
NeurIPS 2016

@inproceedings{aytar2016soundnet,
  title={SoundNet: Learning Sound Representations from Unlabeled Video},
  author={Yusuf Aytar and Carl Vondrick and Antonio Torralba},
  booktitle={NeurIPS 2016},
  year={2016},
  url={http://projects.csail.mit.edu/soundnet/}
}

3D

Spatial awareness for 3D reconstruction and physical reasoning.

Teaser for Generative Camera Dolly: Extreme Monocular Dynamic Novel View Synthesis

Generative Camera Dolly: Extreme Monocular Dynamic Novel View Synthesis
Basile Van Hoorick, Rundi Wu, Ege Ozguroglu, Kyle Sargent, Ruoshi Liu, Pavel Tokmakov, Achal Dave, Changxi Zheng, Carl Vondrick
ECCV 2024 (Oral)

@inproceedings{hoorick2024generative,
  title={Generative Camera Dolly: Extreme Monocular Dynamic Novel View Synthesis},
  author={Basile Van Hoorick and Rundi Wu and Ege Ozguroglu and Kyle Sargent and Ruoshi Liu and Pavel Tokmakov and Achal Dave and Changxi Zheng and Carl Vondrick},
  booktitle={ECCV 2024 (Oral)},
  year={2024},
  url={https://gcd.cs.columbia.edu}
}
Teaser for pix2gestalt: Amodal Segmentation by Synthesizing Wholes

pix2gestalt: Amodal Segmentation by Synthesizing Wholes
Ege Ozguroglu, Ruoshi Liu, Dídac Surís, Dian Chen, Achal Dave, Pavel Tokmakov, Carl Vondrick
CVPR 2024

@inproceedings{ozguroglu2024pixgestalt,
  title={pix2gestalt: Amodal Segmentation by Synthesizing Wholes},
  author={Ege Ozguroglu and Ruoshi Liu and Dídac Surís and Dian Chen and Achal Dave and Pavel Tokmakov and Carl Vondrick},
  booktitle={CVPR 2024},
  year={2024},
  url={https://gestalt.cs.columbia.edu}
}
Teaser for Objaverse-XL: A Universe of 10M+ 3D Objects

Objaverse-XL: A Universe of 10M+ 3D Objects
Matt Deitke et al.
NeurIPS 2023

@inproceedings{deitke2023objaversexl,
  title={Objaverse-XL: A Universe of 10M+ 3D Objects},
  author={Matt Deitke and others},
  booktitle={NeurIPS 2023},
  year={2023},
  url={https://objaverse.allenai.org/objaverse-xl-paper.pdf}
}
Teaser for Zero-1-to-3: Zero-shot One Image to 3D Object

Zero-1-to-3: Zero-shot One Image to 3D Object
Ruoshi Liu, Rundi Wu, Basile Van Hoorick, Pavel Tokmakov, Sergey Zakharov, Carl Vondrick
ICCV 2023 (Oral)

@inproceedings{liu2023zeroto,
  title={Zero-1-to-3: Zero-shot One Image to 3D Object},
  author={Ruoshi Liu and Rundi Wu and Basile Van Hoorick and Pavel Tokmakov and Sergey Zakharov and Carl Vondrick},
  booktitle={ICCV 2023 (Oral)},
  year={2023},
  url={https://zero123.cs.columbia.edu}
}
Teaser for SurfsUp: Learning Fluid Simulation for Novel Surfaces

SurfsUp: Learning Fluid Simulation for Novel Surfaces
Arjun Mani*, Ishaan Preetam Chandratreya*, Elliot Creager, Carl Vondrick, Richard Zemel
ICCV 2023

@inproceedings{mani2023surfsup,
  title={SurfsUp: Learning Fluid Simulation for Novel Surfaces},
  author={Arjun Mani and Ishaan Preetam Chandratreya and Elliot Creager and Carl Vondrick and Richard Zemel},
  booktitle={ICCV 2023},
  year={2023},
  url={https://surfsup.cs.columbia.edu}
}
Teaser for Humans as Light Bulbs: 3D Human Reconstruction from Thermal Reflection

Humans as Light Bulbs: 3D Human Reconstruction from Thermal Reflection
Ruoshi Liu, Carl Vondrick
CVPR 2023

@inproceedings{liu2023humans,
  title={Humans as Light Bulbs: 3D Human Reconstruction from Thermal Reflection},
  author={Ruoshi Liu and Carl Vondrick},
  booktitle={CVPR 2023},
  year={2023},
  url={https://thermal.cs.columbia.edu}
}

Robustness

Trustworthy models with strong generalization under distribution shift.

Teaser for Raidar: geneRative AI Detection viA Rewriting

Raidar: geneRative AI Detection viA Rewriting
Chengzhi Mao, Carl Vondrick, Hao Wang, Junfeng Yang
ICLR 2024

@inproceedings{mao2024raidar,
  title={Raidar: geneRative AI Detection viA Rewriting},
  author={Chengzhi Mao and Carl Vondrick and Hao Wang and Junfeng Yang},
  booktitle={ICLR 2024},
  year={2024},
  url={https://arxiv.org/pdf/2401.12970.pdf}
}
Teaser for Adversarial Attacks are Reversible with Natural Supervision

Adversarial Attacks are Reversible with Natural Supervision
Chengzhi Mao, Mia Chiquier, Hao Wang, Junfeng Yang, Carl Vondrick
ICCV 2021

@inproceedings{mao2021adversarial,
  title={Adversarial Attacks are Reversible with Natural Supervision},
  author={Chengzhi Mao and Mia Chiquier and Hao Wang and Junfeng Yang and Carl Vondrick},
  booktitle={ICCV 2021},
  year={2021},
  url={https://arxiv.org/abs/2103.14222}
}
Teaser for Dissecting Image Crops

Dissecting Image Crops
Basile Van Hoorick, Carl Vondrick
ICCV 2021

@inproceedings{hoorick2021dissecting,
  title={Dissecting Image Crops},
  author={Basile Van Hoorick and Carl Vondrick},
  booktitle={ICCV 2021},
  year={2021},
  url={https://arxiv.org/pdf/2011.11831.pdf}
}
Teaser for Metric Learning for Adversarial Robustness

Metric Learning for Adversarial Robustness
Chengzhi Mao, Ziyuan Zhong, Junfeng Yang, Carl Vondrick, Baishakhi Ray
NeurIPS 2019

@inproceedings{mao2019metric,
  title={Metric Learning for Adversarial Robustness},
  author={Chengzhi Mao and Ziyuan Zhong and Junfeng Yang and Carl Vondrick and Baishakhi Ray},
  booktitle={NeurIPS 2019},
  year={2019},
  url={https://arxiv.org/abs/1909.00900}
}

All Papers


Teaching

  • Computer Vision II (Summer 2021, Spring 2022-2025)
  • Computer Vision I (Fall 2018-2019)
  • Advanced Computer Vision (Spring 2019)
  • Machine Learning Frontiers (Fall 2024-2025)
  • Representation Learning (Fall 2020-2022)

Funding

  • National Science Foundation
  • Defense Advanced Research Projects Agency
  • Toyota Research Institute
  • Amazon Research
  • Google

Press