Education

Ph.D. Computer Science

University of Virginia • 2020 — present

Advised by Dr. Tom Fletcher
Previously advised by Dr. Vicente Ordonez Roman

M.S. Data Science

University of Virginia • 2018 — 2019

B.Tech. Mechanical Engineering

Indian Institute of Technology, Roorkee • 2013 — 2017

Experience

Research Scientist Intern

Adobe Research, CA • June 2023 — Present

Advised by Dr. Kushal Kafle. Working on designing an AI assistant for visual reasoning via bootstrapping pretrained foundation models.

Research Scientist Intern

Salesforce Research, CA • May — Nov 2022

Advised by Dr. Stefano Ermon and Dr. Nikhil Naik. Worked on conditional generative diffusion models for image synthesis.

Research Scientist

University of Virginia • 2019 — 2020

Advised by Dr. Donald E. Brown and Dr. Sana Syed. Developed learning frameworks for the understanding and assisted diagnosis of gastrointestinal diseases.

Analyst

Citibank, India • 2017 — 2018

Built a streamlined visualization platform with data-driven insights for the Chief Country Officer. However, would not recommend.

Selected Publications

NASDM, Nuclei-Aware Semantic Histopathology Image Generation Using Diffusion Models

[paper]

Aman Shrivastava and P. Thomas Fletcher.

In International Conference on Medical Image Computing and Computer-Assisted Intervention. MICCAI, 2023.

CLIP-Lite, Information Efficient Visual Representation Learning from Textual Annotations

[paper] [code]

Aman Shrivastava, Ramprasaath R. Selvaraju, Nikhil Naik, and Vicente Ordonez.

In International Conference on Artificial Intelligence and Statistics. PMLR, 2023.

Identifying metabolic shifts in Crohn's disease using'omics-driven contextualized computational metabolic network models

[paper]

Philip Fernandes, Yash Sharma, Fatima Zulqarnain, Brooklyn McGrew, Aman Shrivastava, Lubaina Ehsan, Dawson Payne et al.

In Scientific Reports, 2023.

Estimating and Maximizing Mutual Information for Knowledge Distillation

[paper]

Aman Shrivastava, Yanjun Qi, and Vicente Ordonez.

In IEEE CVPR Workshop on Fair, Data Efficient and Trusted Computer Vision, 2023.

Self-attentive adversarial stain normalization

[paper] [code]

Aman Shrivastava, William Adorno, Yash Sharma, Lubaina Ehsan, S. Asad Ali, Sean R. Moore, Beatrice Amadi, Paul Kelly, Sana Syed, and Donald E. Brown.

In International Conference on Pattern Recognition, pp. 120-140. Springer, Cham, 2021.

Deep Learning for Visual Recognition of Environmental Enteropathy and Celiac Disease

[paper]

Aman Shrivastava, Karan Kant, Saurav Sengupta, Sung-Jun Kang, Marium Khan, S. Asad Ali, Sean R. Moore et al.

In 2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), pp. 1-4. IEEE, 2019.

Cluster-to-Conquer, A Framework for End-to-End Multi-Instance Learning for Whole Slide Image Classification

[paper] [code]

Sharma, Yash, Aman Shrivastava, Lubaina Ehsan, Christopher A. Moskaluk, Sana Syed, and Donald E. Brown.

In Medical Imaging with Deep Learning. PMLR, 2021.

Artificial Intelligence Applied to Gastrointestinal Diagnostics, A Review

[paper]

Vatsal Patel, Marium N. Khan, Aman Shrivastava, Kamran Sadiq, S. Asad Ali, Sean R. Moore,Donald E. Brown, Sana Syed.

In Journal of pediatric gastroenterology and nutrition 70, no. 1, 2020.

Projects

Deep Image Colorization

[code]

A self-attentive GAN to colorize b/w images. Uses perceptual loss that eancourages vibrant and natural image generation.

Infinite meme generator

[code]

Generates humerous captions using a joint visual-semantic embedding sapce that represents visual features composed with the tone of a meme template.

Connect 4

[demo] [code]

A lightweight connect-4 game with a self-written pure-javascript bot using Minimax algorithm and Monte Carlo simulations.

News Sentiment Tracker

[code]

Automatic scraping and analysis of trends in the sentiment of editorial articles on any selected topic of media discussion. Applied it to parameterize and co-relate social response with economic fluctuations during the demonetization drive by the Government of India in November 2016.

Soccer Squad Optimization

[code]

Strategic team selection by predicting the best football squad given budget, nationality (and/or club) and playing formation constraints based on self extracted FIFA dataset.