Sourav Pal

I am a first year PhD student of Computer Sciences at UW-Madison.

Prior to that I was part of Adobe Acrobat Reader team. Even before I was a Research Intern at the BigData Experience Lab of Adobe Research where I worked with an amazing mentor, Dr. Ritwik Sinha.

I spent four beautiful years, perhaps the most amazing period of my life at the Indian Institute of Technology (IIT) Kharagpur from where I graduated with a B.Tech (Hons.) in Computer Science and Engineering. I was fortunate enough to be advised by Prof. Pabitra Mitra during my undergraduate studies.

Email  /  CV  /  GitHub  /  LinkedIn

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Research

I am interested in solving challenging problems realted to Machine Learning and Computer Vision. I have had the opportunity to work on applications of Deep Learning in Computer Vision and Natural Language Processing.

Publications
D-FJ: Deep Neural Network Based Factuality Judgment
Ankan Mullick, Sourav Pal, Projjal Chanda, Arijit Panigrahy, Anurag Bharadwaj, Siddhant Singh, Tanmoy Dam
TrueFact, SIGKDD, 2019

Deep neural networks to detect facts and opinions from online news media. We have also shown how factuality, opinionatedness and sentiment fraction of different news articles changes over certain events in different time frames.

Visual Attention for Behavioral Cloning in Autonomous Driving
Sourav Pal*, Tharun Mohandoss*, Pabitra Mitra
ICMV, 2018

We present two methods of predicting visual attention maps. The first method is a supervised learning approach in which we collect eye-gaze data for the task of driving and use this to train a model for predicting the attention map. The second method is a novel unsupervised approach where we train a model to learn to predict attention as it learns to drive a car.

Saliency Prediction for Mobile User Interfaces
Prakhar Gupta, Shubh Gupta* , Ajaykrishnan Jayagopal*, Sourav Pal*, Ritwik Sinha
WACV, 2018

We introduce deep learning models for saliency prediction for mobile user interfaces at the element level to improve their usability.

Patents
Saliency Prediction for a Mobile User Interface

Saliency Prediction for Informational Documents

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