I am a postdoctoral scholar at Stanford University. I received my Ph.D. in computer science from Princeton University under the supervision of Prof. Fei-Fei Li and Prof. Kai Li. My bachelor's degree in Computer Science is from Tsinghua University, China.

My primary interests are computer vision and machine learning, with a focus on large-scale visual recognition through big data. In particular, I am interested in the following topics.

• Large-Scale Visual Recognition. How do we represent visual signals for recognition at the human scale—that is, recognizing tens of thousands of visual categories? I am interested in the understanding and modeling of the relations between the pixel space and the semantic space through massive amounts of data.
• Large-Scale Datasets. How do we acquire, annotate, and manage massive amounts of visual data? I am interested in the use of crowd-sourcing for constructing large-scale datasets. I also develop algorithms and systems for indexing and retrieval.
• Large-Scale Machine Learning. How do we scale up machine learning for big data? I exploit the structures of data to develop learning algorithms that are computationally efficient and easily parallelizable.

	Crowdsourcing Annotations for Visual Object Detection Hao Su, Jia Deng, Li Fei-Fei. AAAI Human Computation Workshop (HCOMP) 2012 [ paper ]
	Large Scale Visual Recognition Jia Deng. Princeton University. Ph.D. Thesis. 2012 [ thesis ]
	Hedging Your Bets: Optimizing Accuracy-Specificity Trade-offs in Large Scale Visual Recognition Jia Deng, Jonathan Krause, Alex Berg, Li Fei-Fei IEEE Conference on Computer Vision and Pattern Recognition(CVPR), 2012. [ paper ] [ supplementary materials ]
	Fast and Balanced: Efficient Label Tree Learning for Large Scale Object Recognition Jia Deng, Sanjeev Satheesh, Alex Berg, Li Fei-Fei Neural Information Processing Systems(NIPS), 2011. [ paper] [ supplementary materials ]
	Hierarchical Semantic Indexing for Large Scale Image Retrieval. Jia Deng, Alex Berg, Li Fei-Fei IEEE Conference on Computer Vision and Pattern Recognition(CVPR), 2011. [ paper ] [ supplementary materials ]
	What does classifying more than 10,000 image categories tell us? Jia Deng, Alex Berg, Kai Li, Li Fei-Fei European Conference on Computer Vision(ECCV), 2010. [ paper ] [ data ] [ code ]
	ImageNet: A Large-Scale Hierarchical Image Database. Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, Li Fei-Fei IEEE Conference on Computer Vision and Pattern Recognition(CVPR), 2009. [ paper ] [ project site ]
	Towards scalable dataset construction: An active learning approach Brandon Collins, Jia Deng, Kai Li, Li Fei-Fei. European Conference on Computer Vision(ECCV), 2008. [ paper ]
	Digital Bas-Relief From 3D Scenes Tim Weyrich, Jia Deng, Connelly Barnes, Szymon Rusinkiewicz, Adam Finkelstein. ACM Transactions on Graphics (Proc. SIGGRAPH), 26(3), August 2007. [ paper ] [ project site ]

Co-organizer. Imagenet Large Scale Visual Recognition Challenge 2011 (ILSVRC2011).
Co-organizer. Imagenet Large Scale Visual Recognition Challenge 2010 (ILSVRC2010).