PeopleofSuperintelligence

Researcher

Aishwarya Agrawal

Aishwarya Agrawal is a computer vision and language researcher whose early work helped define visual question answering as an AI research task and challenge series. She earned an electrical-engineering degree in 2014, completed a Georgia Tech PhD in 2019 and worked full time at DeepMind through 2020. Her later research tested VQA models’ ability to generalize beyond benchmark data, and she shared the 2025 PAMI Mark Everingham Prize for the challenge series. As of October 2026, she is an assistant professor at Université de Montréal and a core academic member of Mila. She holds a Canada CIFAR AI Chair and is a research scientist at Google DeepMind.

Works
63
Citations
7,738
h-index
15
Badges

Publication numbers from OpenAlex, as of 18 October 2026.

Timeline

  1. 2014

    An engineering degree

    She earns a bachelor’s degree in electrical engineering with a minor in computer science and engineering at IIT Gandhinagar in 2014.

  2. 2015–2016

    VQA and the challenge

    She co-authors a 2015 paper that proposes open-ended visual question answering and a large dataset of image questions and answers. She helps organize the VQA Challenge and presents the challenge overview and results at its 2016 CVPR workshop.

  3. August 2019–December 2020

    DeepMind and a doctorate

    She completes a Georgia Tech PhD in August 2019 and works full time as a DeepMind research scientist from August 2019 to December 2020.

  4. 2020

    A Canada-CIFAR AI Chair

    Her Canada-CIFAR AI Chair appointment at Université de Montréal starts in 2020.

  5. 2023

    Testing VQA generalization

    She co-authors a 2023 EACL paper that evaluates vision-and-language models on out-of-distribution VQA. The study finds poor generalization in that setting.

  6. 2025

    A PAMI Mark Everingham Prize

    She receives the 2025 PAMI Mark Everingham Prize as a contributor to The VQA Series of Challenges. The prize recognizes the series for stimulating a new strand of vision and language research.

  7. July 2026

    A Flow-Transformer agent

    She co-authors “One Flow-Transformer for Imagination and Control,” a 2026 paper that introduces DRIFT, an online agent with a single Flow-Transformer as both world model and policy backbone.

  8. As of October 2026

    Assistant professor and research scientist

    As of October 2026, she is an assistant professor at Université de Montréal and a core academic member of Mila. She holds a Canada CIFAR AI Chair and is a research scientist at Google DeepMind in Montréal.

A language model matched the links in this timeline to people, organizations and papers (provisional, model-judged).

Career

  1. Since 2023MilaCore Academic Member
  2. Since 2020Université de MontréalCanada CIFAR AI Chair
  3. Since 2019Google DeepMindResearch Scientist
  4. 2022–2026CIFAR
  5. 2015–2018Virginia Tech

Education

  1. 2019Georgia Institute of TechnologyPhD
  2. 2014Indian Institute of Technology GandhinagarBachelor’s degree in electrical engineering

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

Most-cited works

  1. VQA: Visual Question Answering2015 · IEEE International Conference on Computer Vision (ICCV) · 4,480 citationsWith C. Lawrence Zitnick, Devi Parikh, Dhruv Batra and Margaret Mitchell
  2. Don't Just Assume; Look and Answer: Overcoming Priors for Visual Question Answering2018 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition · 586 citationsWith Aniruddha Kembhavi, Devi Parikh and Dhruv Batra
  3. Analyzing the Behavior of Visual Question Answering Models2016 · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 292 citationsWith Devi Parikh and Dhruv Batra
  4. Visual Storytelling2016 · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · 254 citationsWith C. Lawrence Zitnick, Devi Parikh, Dhruv Batra, Lucy Vanderwende, Margaret Mitchell and Pushmeet Kohli
  5. Overcoming Language Priors in Visual Question Answering with Adversarial Regularization2018 · 141 citations

From OpenAlex, as of 18 October 2026.

  1. The median h-index is 55 at universities and 20 at frontier AI labsIncludes Aishwarya Agrawal. The median h-index is 55 at universities and 20 at frontier AI labs. We compare publishing careers, citations and moves to estimate how universities and frontier labs contribute to AI research.
  2. Google has the highest combined h-index among AI organizationsIncludes Google. Our estimates of combined and median h-index at AI organizations, using current affiliations and OpenAlex records.
  3. Google alumni founded or led 77 other organizations, the most among the labs we compareIncludes Google. We trace 177 organizations founded or led by AI lab alumni, and 186 career moves between the labs.
  4. Google had the most people shaping AI every year from 2014 to 2025Includes Google. Our estimates of which organizations employed the most people shaping AI from 1962 to 2025, with a year-by-year chart.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

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  1. MIT Rising Stars risingstars-eecs.mit.edu. Checked 18 October 2026.
  2. VQA: Visual Question Answering arxiv.org. Checked 18 October 2026.
  3. VQA: Visual Question Answering visualqa.org. Checked 18 October 2026.
  4. VQA Challenge Workshop at CVPR 2016 visualqa.org. Checked 18 October 2026.
  5. Aishwarya Agrawal | Mila mila.quebec. Checked 18 October 2026.
  6. Canada’s top international AI talent grows to 80 newswire.ca. Checked 18 October 2026.
  7. Reassessing Evaluation Practices in Visual Question Answering: A Case Study on Out-of-Distribution Generalization aclanthology.org. Checked 18 October 2026.
  8. Aishwarya Agrawal awarded Everingham Prize 2025 | Mila mila.quebec. Checked 18 October 2026.
  9. Un corps professoral qui rayonne fas.umontreal.ca. Checked 18 October 2026.