On the vision side, I am interested in problems in vision and language, learning common sense and visual reasoning. On the machine learning side, I am interested in developing tools for effective low-shot learning, generative models, bayesian deep learning and variational inference.
I also care about issues of how we evaluate our models, as we edge towards higher-level AI-complete tasks. In my first project in grad school, I worked on a (now popularly used) evaluation metric for image captioning called CIDEr.
- Recognized as one of the outstanding reviewers at CVPR, 2017
- Paper on learning word embeddings grounded in sounds accepted as a short paper at EMNLP, 2017!
- I will be interning at Facebook AI Research (FAIR) this summer, working with Devi Parikh, Dhruv Batra and Marcus Rohrbach!
- Two papers accepted to CVPR 2017 as Spotlight presentations!
- I interned at Google Research in Winter 2017, working with Kevin Murphy on generative models for images!
- Serving as reviewer for ECCV 2016, BMVC 2017, CVPR 2017, ICCV 2017
- I interned at Google Research in Summer 2016, with Gal Chechik and Samy Bengio!
- I interned at the Center for Visual Computing at INRIA in Summer, 2014 with Iasonas Kokkinos
- MSCOCO Caption Evaluation code
- Codes from MSCOCO Caption Evaluation for metrics (BLEU, ROUGE, CIDEr-D and METEOR), independent of the COCO annotations
- Code for our CVPR'16 paper on Learning Visually Grounded Word Embeddings
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