I am a Computer Scientist at the Center for Vision Technologies at SRI (formerly, Stanford Research Institute) International, where I primarily work with Ajay Divakaran, Yi Yao, and Giedrius Burachas on applying Deep Learning to Computer Vision and Natural Language Processing tasks. I finished graduate school (Master's) majoring in Computer Engineering from Virginia Tech (VT). While at VT, I had the honor of working in the Computer Vision Lab advised by Prof. Devi Parikh and in close collaboration with Prof. Dhruv Batra.
In my research, I am excited about how to make human-AI and AI-AI teams solve tasks effectively. Consequently, I am interested in and work on models that can interact with humans using natural language, models that can rationalize and explain their decisions, and models that leverage social media to do societal good.
Dr. Erik Brynjolfsson, the Director of the MIT Center for Digital Business, tweeted:
Drones will soon be able to spot you when you walk around outside: UAV With Facial Recognition Takes Flight http://t.co/qpb2owdzGd— Erik Brynjolfsson (@erikbryn) September 21, 2014
Arijit Ray, Michael Cogswell, Xiao Lin, Kamran Alipour, Ajay Divakaran, Yi Yao, Giedrius Burachas, Knowing What VQA Does Not: Pointing to Error-Inducing Regions to Improve Explanation Helpfulness [arXiv] [Project Page]
Arijit Ray, Karan Sikka, Ajay Divakaran, Stefan Lee, Giedrius Burachas, Sunny and Dark Outside?! Improving Answer Consistency in VQA through Entailed Question Generation , 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP 2019), also at CVPR-W 2019 VQA and Visual Dialog Workshop, [arXiv], [bibTex] [Data]
Arijit Ray, Yi Yao, Rakesh Kumar, Ajay Divakaran, Giedrius Burachas, Can You Explain That: Lucid Explanations Help Human-AI Collaboratve Image Retrieval , 2019 AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2019), [arXiv], [bibTex]
Arijit Ray, Giedrius T. Burachas, Karan Sikka, Anirban Roy, Avi Ziskind, Yi Yao, Ajay Divakaran, Make Up Your Mind: Towards Consistent Answer Predictions in VQA Models [pdf], [bibTex], Workshop on Shortcomings in Vision and Language , European Conference on Computer Vision, 2018 (ECCV-W 2018)
Arijit Ray, Gordon Christie, Mohit Bansal, Dhruv Batra, and Devi Parikh, "Question Relevance in VQA: Identifying Non-Visual And False-Premise Questions.", 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP 2016). [pdf] [code] [Video]
Prashant Chandrasekar, Xuan Zhang, Saurabh Chakravarty, Arijit Ray, John Krulick, and Alla Rozovskaya, "The Virginia Tech System at CoNLL-2016 Shared Task on Shallow Discourse Parsing", CoNLL Shared Task (2016).
The Art of Deep Connection - Towards Natural and Pragmatic Conversational Agent Interactions. [Master's Thesis], Virginia Tech E-Library, 2017
Object Prediction using Image Context: Predict next object in an image reasoned on present image context in a sequential manner, Computer Vision Class Project Fall 2015
Online Demo for Predicting Plausibility of Common Sense Assertions: Enter a three-phrase tuple to assess the plausibility score based on a joint language-vision common-sense reasoning, Class Project, Fall 2015
Learning to Listen: Matching Cover songs with Original Productions: Match Original Songs to Cover Songs using an Ensemble of Supervised and Unsupervised Approaches, Machine Learning Class Project, Fall 2015.
Ray, Arijit, Kishan Prudhvi Guddanti, and N. Chellammal. "An Approach to Intelligent Traction Control Using Regression Networks and Anomaly Detection.", Junior (3rd Year) Semester Project, Fall 2013, published in Applied Artificial Intelligence 29.6 (2015): 597-616.
Best way to reach me would be to drop an email to ray93 at vt dot edu. Please don't spam me!