Meet Shah | મીત શાહ
Resident at Facebook AI Research

About Me

I'm a resident at Facebook AI Research working on problems in Computer Vision, NLP and their intersection with Prof. Devi Parikh.

I graduated with my Dual Degree (Bachelor's + Master's) in Electrical Engineering (EE) from IIT-Bombay. I worked at Vision, Graphics and Imaging Lab (ViGIL) with Prof. Suyash Awate on semi and weakly supervised deep learning methods for biomedical image analysis.

I've interned with research teams at Microsoft Research (Bangalore), Curious AI (Helsinki), (Mumbai), and Advanced Digital Sciences Center - UIUC (Singapore). I've also interned with software teams at Sony Corporation in their Tokyo HQ and have completed Google Summer of Code with Python Software Foundation.

I am interested in the application of Machine Learning and Computer Vision in real time systems. I'm not a big fan of redundancy and I like to automize things which consume my time on a highly frequent basis. I promote Open Source Software and keep making my little contributions as and when time permits.


  1. Mar 2018: Two papers accepted at CVPR 2019. "Cycle Consistency for Robust Question Answering" (oral) and "Towards VQA Models that can read"
  2. Dec 2018: My paper "Annotation-cost Minimization for Medical Image Segmentation using Suggestive Mixed Supervision Fully Convolutional Networks" at Medical Imaging meets NeurIPS workshop 2018
  3. Dec 2018: Our paper "Pythia: A platform for Vision and Language Multimodal Resarch" at Systems for ML and Open Source Software workshop, NeurIPS 2018
  4. Sep 2018: My paper "MS-Net: Mixed Supervision Fully-Convolutional Networks for Full-Resolution Segmentation" was Runners Up for Young Scientist Award at MICCAI 2018, Granada
  5. Sep 2018: Placed 1st at the VizWiz Challenge, ECCV 2018.
  6. Jun 2018: Started as an AI Resident at Facebook AI Research, Menlo Park, USA.
  7. Aug 2018: Awarded Undergraduate Research Award (URA03) for exceptional work in master's thesis.
  8. May 2018: Graduated from IIT-Bombay.
  9. Apr 2018: Presented my paper "Semi-supervised Abnormality Detection with Robust Quasi-Norm Autoencoding" (full oral) at ISBI 2018, Washington DC
  10. Sep 2017: Presented my paper "Leaf Classification using marginalized shape context and shape+texture Dual-Path Deep Convolutional Neural Networks" (full oral) at ICIP 2017, Beijing
  11. May 2017: Research Internship at The Curious AI Company in Helsinki, Finland.
  12. Dec 2016: Research Internship at Microsoft Research in Bangalore with Amit Deshpande and Pushmeet Kohli.
  13. Aug 2016: Google Summer of Code with Python Software Foundation successfully completed.
  14. May 2016: Software Engineering Internship at Sony Corporation HQ in Tokyo, Japan.
  15. Dec 2015: Deep Learning Intern at
  16. May 2015: Research Internship at Advance Digital Sciences Center, Singapore with Swathi Gurumani in the HLS team.
  17. Dec 2014: Research Internship at Indian Institute of Management, Ahmedabad with Prof. Sachin Jayaswal.
  18. July 2013: Started school at IIT-Bombay

Cycle-Consistency for Robust Visual Question Answering
Meet Shah ,Xinlei Chen, Marcus Rohrbach, Devi Parikh.
CVPR 2019 (oral)

Towards VQA Models That Can Read
Amanpreet Singh, Vivek Natarajan, Meet Shah ,Tina Yu Jiang, Xinlei Chen, Dhruv Batra, Devi Parikh, Marcus Rohrbach.
CVPR 2019

MS-Net: Mixed-Supervision Fully-Convolutional Networks for Full-Resolution Segmentation
Meet Shah ,Shabbir Merchant, Suyash Awate.
MICCAI 2018 (full oral)
Young Scientist Award Runners Up

[Paper] [Project]
Semi-supervised Abnormality Detection with Robust Quasi-norm Autoencoding
Meet Shah ,Shabbir Merchant, Suyash Awate.
ISBI 2018 (full oral)

[Paper] [Project]