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Ramprasaath R. Selvaraju

Senior Researcher

Apple
Sunnyvale, CA

About Me:

Hello! I am a Senior Research Scientist at Apple, specializing in Computer Vision. I did my PhD at Georgia Tech advised by Prof. Devi Parikh and Prof. Dhruv Batra. My research focuses on advancing AI systems through —

  • creating tailored solutions for enterprise applications while addressing model biases,
  • understanding and interpreting model decisions while diagnosing failures,
  • building trust and enabling knowledge transfer between humans and AI,
  • encouraging human-like reasoning and grounded representations.

Check out my papers below and reach out to me if you would like to chat!

Education

  • Ph.D in Computer Science, 2020

    Georgia Institute of Technology, Atlanta

    Thesis: Explaining model decisions and fixing them via human feedback

  • Master of Science in Physics, 2015

    Birla Institute of Technology and Science (BITS-Pilani), Hyderabad, India

  • Bachelor of Engineering in Electrical & Electronics Engineering, 2015

    Birla Institute of Technology and Science (BITS-Pilani), Hyderabad, India

Awards & Recognition

  • 2022

    Recognized among the Top-100 scholars in the AMinor 2022 AI 2000 Most influential scholars in Computer Vision between 2012-2021.

Selected Publications

(view list)

Development and validation of an AI‑derived digital pathology‑based biomarker

Development and validation of an AI‑derived digital pathology‑based biomarker to predict benefit of long‑term androgen deprivation therapy with radiotherapy in men with prostate cancer

AJ Armstrong, VYT Liu, Ramprasaath R. Selvaraju, E Chen, J Simko, S DeVries
Journal of Clinical Oncology 41 (16_suppl), 5001‑5001, 2023
AI Biomarker
Icon Information efficient visual representation learning with language supervision

CLIP‑Lite: Information Efficient Visual Representation Learning with Language Supervision

A Shrivastava, Ramprasaath R. Selvaraju, N Naik, V Ordonez
AISTATS, 2023
CLIP‑Lite
Icon Can domain adaptation make object recognition work for everyone?

Can Domain Adaptation Make Object Recognition Work for Everyone?

V Prabhu, Ramprasaath R. Selvaraju, J Hoffman, N Naik
CVPR, 2022
Domain Adaptation
Icon Vision‑Language Representation Learning with Momentum Distillation

Align before Fuse: Vision and Language Representation Learning with Momentum Distillation

Junnan Li, Ramprasaath R. Selvaraju, Akihiro Sugimoto, Asim Kadav, Hassan Akbari, Larry Zitnick
NeurIPS 2021
PDF Code
ALBEF
Icon Learning to Localize Improves Self‑Supervised Representations

Casting Your Model: Learning to Localize Improves Self‑Supervised Representations

Ramprasaath R. Selvaraju, K Desai, J Johnson, N Naik
CVPR, 2021
CAST
Icon Interrogating VQA Models with Sub‑Questions

Squinting at VQA Models: Introspecting VQA Models with Sub‑Questions

Ramprasaath R. Selvaraju, P Tendulkar, D Parikh, E Horvitz, MT Ribeiro, B Nushi
CVPR, 2020
SQUINT
Icon Visual Explanations from Deep Networks

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Class Activation Mapping

Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, Dhruv Batra
ICCV 2019
PDF Code
Visual Explanations
Icon Making Vision and Language Models More Grounded

Taking a HINT: Leveraging Explanations to Make Vision and Language Models More Grounded

Ramprasaath R. Selvaraju, S Lee, Y Shen, H Jin, S Ghosh, L Heck, D Batra, D Parikh
ICCV 2019
HINT

Research Experience

 
 
 
 
 

Senior Researcher

Apple

May 2023 – Present Cupertino
 
 
 
 
 

Founding Member

Artera AI

Feb 2022 – Mar 2023 Los Altos
Led research and development of AI solutions for precision medicine.
 
 
 
 
 

Senior Research Scientist

Salesforce Research

June 2020 – Feb 2022 Palo Alto
Working at the intersection of large-scale multimodal representation learning and explainability
 
 
 
 
 

Research Intern

Adaptive Systems and Interaction Group, Microsoft Research

Summer 2019 Redmond
Towards evaluating and encouraging human-like reasoning abilities in deep models.
 
 
 
 
 

Research Intern

Tesla Autopilot

Spring 2019 Palo Alto
Preventing failures of autonomous systems in case of rarely occurring scenarios.
 
 
 
 
 

Research Intern

Samsung Research America

Summer 2018 Mountain View
Leveraging explanations to make AI models more grounded.
 
 
 
 
 

Research Intern

Applied Machine Learning, Facebook

Spring 2017 Menlo Park
Developing framework for interpreting and visualizing Facebook's deep models.
 
 
 
 
 

PhD Research Assistant

Visual Intelligence Lab, Georgia Tech

2015 – 2020 Atlanta
Towards building AI systems that are Interpretable, Transparent, and Unbiased.
 
 
 
 
 

Research Intern

Visual Intelligence Lab, Virginia Tech

Spring 2015 Atlanta
Building curious systems that ask Natural Language open-ended questions about an image.
 
 
 
 
 

Research Intern

Oxford University

Fall 2014 Oxford
Developing interactive augmented reality systems for visually impaired.
 
 
 
 
 

Research Intern

Brown University

Summer 2013 Providence
Designing a vision-based navigation system to help the visually impaired navigate indoor environments.