Aishwarya Agrawal

me

Aishwarya Agrawal
Graduate Student

Advisor: Dhruv Batra
School of Interactive Computing
Georgia Tech

Email: aishwarya -at- gatech.edu
Lab: 272B College of Computing

Highlights and News


Spring 2019:
Upcoming visits to:
  • Simon Fraser University (School of Computing Science)
  • University of Michigan (ECE)

Fall 2018:
Giving talks on Visual Question Answering and Beyond at:
  • Vector Institute for Artificial Intelligence
  • Montreal Institute of Learning Algorithms
  • Facebook AI Research Lab, Montreal
  • Google Brain, Montreal
  • Emory University (CS Seminar)
  • Stanford University (NLP Seminar)
  • University of Massachusetts, Amherst (Vision and Graphics Group)
  • Massachusetts Institute of Technology (Computer Vision Group)
  • Boston University (Computer Vision and Learning Group)
  • University of California, Berkeley (Trevor Darrell's Group)
  • Cornell Tech (Pixel Cafe)
  • New York University (Machine Learning for Language Group)
  • Princeton University (PIXL Lunch)
July 2018:
I am a finalist of the Foley Scholars Award.
June 2018:
I got selected for the Rising Stars in EECS workshop.
Feb 2018:
I won the NVIDIA Graduate Fellowship.

About Me


I am on the job market for faculty and industry research positions.

I am a 5th year PhD student in the School of Interactive Computing at Georgia Tech. I am advised by Dhruv Batra and also collaborate closely with Devi Parikh.

My research interests lie at the intersection of Computer Vision, Deep Learning and Natural Language Processing, with a focus on developing Artificial Intelligence (AI) systems that that can 'see' (i.e. understand the contents of an image: who, what, where, doing what?) and 'talk' (i.e. communicate the understanding to humans in free-form natural language).

I co-organize the annual VQA challenge and workshop .

I received my bachelors degree in Electrical Engineering with a minor in Computer Science and Engineering from Indian Institute of Technology Gandhinagar in May 2014.

As a research intern I have spent time at:

  • Google DeepMind (London) in Summer 2018,
    (collaborators: Tejas Kulkarni, Mateusz Malinowski, Felix Hill, Ali Eslami, Oriol Vinyals),
  • Microsoft Research (Redmond) in Summer 2017,
    (collaborators: Jianfeng Gao, Xiaodong He),
  • Allen Institute for Artificial Intelligence in Spring 2017,
    (collaborator: Aniruddha Kembhavi),
  • Microsoft Research (Redmond) in Summer 2015,
    (collaborators: Larry Zitnick, Margaret Mitchell, Xiaodong He),
  • Human Photonics Laboratory in University of Washington Seattle in summer 2013,
    (collaborators: Ronnie Das, Eric Seibel).
  • Short Bio.

    Publications

    Generating Diverse Programs with Instruction Conditioned Reinforced Adversarial Learning
    Aishwarya Agrawal, Mateusz Malinowski, Felix Hill, Ali Eslami, Oriol Vinyals, Tejas Kulkarni
    Visually-Grounded Interaction and Language workshop (spotlight), NIPS 2018
    Learning by Instruction workshop, NIPS 2018
    [ArXiv]
    Overcoming Language Priors in Visual Question Answering with Adversarial Regularization
    Sainandan Ramakrishnan, Aishwarya Agrawal, Stefan Lee
    Neural Information Processing Systems (NIPS), 2018
    [ArXiv]
    Don't Just Assume; Look and Answer: Overcoming Priors for Visual Question Answering
    Aishwarya Agrawal, Dhruv Batra, Devi Parikh, Aniruddha Kembhavi
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018
    [ArXiv | Project Page]
    Resolving Language and Vision Ambiguities Together: Joint Segmentation & Prepositional Attachment Resolution in Captioned Scenes
    Gordon Christie*, Ankit Laddha*, Aishwarya Agrawal, Stanislaw Antol, Yash Goyal, Kevin Kochersberger, Dhruv Batra

    *equal contribution

    Computer Vision and Image Understanding (CVIU), 2017
    [Arxiv | Project Page]
    C-VQA: A Compositional Split of the Visual Question Answering (VQA) v1.0 Dataset
    Aishwarya Agrawal, Aniruddha Kembhavi, Dhruv Batra, Devi Parikh
    CoRR, abs/1704.08243, 2017
    [ArXiv]
    VQA: Visual Question Answering
    Aishwarya Agrawal*, Jiasen Lu*, Stanislaw Antol*, Margaret Mitchell, Larry Zitnick, Devi Parikh, Dhruv Batra

    *equal contribution

    Special Issue on Combined Image and Language Understanding, International Journal of Computer Vision (IJCV), 2017
    [ ArXiv | visualqa.org (data, code, challenge) | slides | talk at GPU Technology Conference (GTC) 2016]
    Analyzing the Behavior of Visual Question Answering Models
    Aishwarya Agrawal, Dhruv Batra, Devi Parikh
    Conference on Empirical Methods in Natural Language Processing (EMNLP), 2016
    [Arxiv | slides | talk at Deep Learning Summer School, Montreal, 2016]
    Resolving Language and Vision Ambiguities Together: Joint Segmentation & Prepositional Attachment Resolution in Captioned Scenes
    Gordon Christie*, Ankit Laddha*, Aishwarya Agrawal, Stanislaw Antol, Yash Goyal, Kevin Kochersberger, Dhruv Batra

    *equal contribution

    Conference on Empirical Methods in Natural Language Processing (EMNLP), 2016
    [Arxiv | Project Page]
    Measuring Machine Intelligence Through Visual Question Answering
    Larry Zitnick, Aishwarya Agrawal, Stanislaw Antol, Margaret Mitchell, Dhruv Batra, Devi Parikh
    AI Magazine, 2016
    [Paper | ArXiv]
    Visual Storytelling
    Ting-Hao Huang, Francis Ferraro, Nasrin Mostafazadeh, Ishan Misra, Aishwarya Agrawal, Jacob Devlin, Ross Girshick, Xiaodong He, Pushmeet Kohli, Dhruv Batra, Larry Zitnick, Devi Parikh, Lucy Vanderwende, Michel Galley, Margaret Mitchell
    Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT), 2016
    [Arxiv, Project Page]
    VQA: Visual Question Answering
    Stanislaw Antol*, Aishwarya Agrawal*, Jiasen Lu, Margaret Mitchell, Dhruv Batra, Larry Zitnick, Devi Parikh

    *equal contribution

    International Conference on Computer Vision (ICCV), 2015
    [ ICCV Camera Ready Paper | ArXiv | ICCV Spotlight | visualqa.org (data, code, challenge) | slides | talk at GPU Technology Conference (GTC) 2016]
    A Novel LBP Based Operator for Tone Mapping HDR Images
    Aishwarya Agrawal, Shanmuganathan Raman
    International Conference on Signal Processing and Communications (SPCOM-2014)
    [Paper |Poster]
    Optically clearing tissue as an initial step for 3D imaging of core biopsies to diagnose pancreatic cancer
    Ronnie Das, Aishwarya Agrawal, Melissa P. Upton, Eric J. Seibel
    SPIE BiOS, International Society for Optics and Photonics, 2014
    [Paper]

    Videos and Talks

    Projects

    Shape recovery using Photometric Stereo
    Class project for 3D Computer Vision course by Dr. Shanmuganathan Raman
    PDF here
    Magic Wand Tool for Region Selection
    Class project for Digital Image Processing course by Dr. Krishna Prasad
    PDF here