Research Areas
Giving people the power to share and connect requires constant innovation
At Facebook, research permeates everything we do. We believe the most interesting research questions are derived from real world problems. Working on cutting edge research with a practical focus, we push product boundaries every day. At the same time, we publish papers, give talks, and collaborate broadly with the academic community.
We solve real-world problems that impact billions of people in areas such as:
Research Areas at Facebook
AR/VR
Creating the future of personal and shared reality
Artificial Intelligence
Advancing the field of machine intelligence
Computational Photography & Intelligent Cameras
Mobile visual processing to understand, augment, and enhance sharing and connections
Computer Vision
Understanding the visual world around us
Connectivity
Connecting the unconnected
Data Science
Gaining insights to deliver meaningful social interactions
Economics & Computation
Exploring the intersection of economics and computation
Human Computer Interaction & UX
Understanding and improving social experiences
Machine Learning
Applying machine learning science to Facebook products
Natural Language Processing & Speech
Breaking down language barriers
Security & Privacy
Keeping the Facebook community safe and secure
Systems & Networking
Building the systems to bring the world closer together
Our people
See all People
Jordan Eschler
UX Researcher
Human Computer Interaction & UX
Mark Harman
Research Scientist
Systems & Networking
Yann LeCun
Chief AI Scientist
Artificial Intelligence
Aude Hofleitner
Research Scientist Manager
Data Science
Nicolas Stier
Co-Director of Core Data Science
Connectivity, Data Science, Economics & Computation, Machine Learning, Systems & Networking
Lauren Scissors
Research Director
Human Computer Interaction & UX
Latest Publications
All PublicationsIR-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 - January 5, 2021
Asynchronous Gradient-Push
Mahmoud Assran, Michael Rabbat
IEEE Transactions on Automatic Control - January 1, 2021
Eliminating Bugs with Dependent Haskell (Experience Report)
Noam Zilberstein
Haskell Symposium - August 27, 2020
Adversarial Continual Learning
Sayna Ebrahimi, Franziska Meier, Roberto Calandra, Trevor Darrell, Marcus Rohrbach
ECCV - August 25, 2020
Learning to Generate Grounded Visual Captions without Localization Supervision
Chih-Yao Ma, Yannis Kalantidis, Ghassan AlRegib, Peter Vajda, Marcus Rohrbach, Zsolt Kira
ECCV - August 24, 2020
Expressive Telepresence via Modular Codec Avatars
Hang Chu, Shugao Ma, Fernando De la Torre, Sanja Fidler, Yaser Sheikh
ECCV - August 24, 2020
End-to-End Object Detection with Transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, Sergey Zagoruyko
ECCV - August 23, 2020
Large-scale Pretraining for Visual Dialog: A Simple State-of-the-Art Baseline
Vishvak Murahari, Dhruv Batra, Devi Parikh, Abhishek Das
ECCV - August 23, 2020
Latest News
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Videos
All Videos
Audio- and Gaze-driven Facial Animation of Codec Avatars
4:42 | August 11, 2020
FroDO: From Detections to 3D Objects
| June 10, 2020
Epipolar Transformers
| June 10, 2020
ARCH: Animatable Reconstruction of Clothed Humans
| June 10, 2020
PyTorch 
DensePose 
Torch