I’m a PhD student in Computer Science at the Department of Electrical Engineering & Computer Sciences (EECS) at University of California, Berkeley advised by Prof. Jitendra Malik. Earlier, I have spent some wonderful time at Stanford as a Master’s student advised by Prof. Juan Carlos Niebles at the Stanford Vision Lab. Earlier yet, I graduated summa cum laude from the Indian Institute of Technology, Kanpur majoring in Electrical Engineering and with a minor in Machine Learning.
In my research journey, I’ve had the good fortune of working with amazing mentors in computer vision labs across the world such as, Prof. Yoshua Bengio & Prof. Alain Tapp (MILA, Research Intern), Prof. Pascal Fua & Dr. Mathieu Salzmann (EPFL, Semester Exchange Student), Prof. Yoichi Sato (University of Tokyo, Research Intern), Dr. Adrien Gaidon & Dr. Kuan-Hui Lee (Toyota Research Institute, Research Intern) Prof. Tanaya Guha (University of Warwick, Undergraduate Thesis) and Prof. K S Venkatesh (IITK, Research Intern).
In addition to my academic endeavours, I like playing board games, reading philosophy and absolutely love an interesting chat/discussion on different viewpoints of rationality & ethics especially in the light of recent developments in AI and its impact on work, society and human condition.
You can find my CV here. Feel free to drop me a mail at email@example.com.
PhD in Computer Science
University of California, Berkeley [Ongoing]
Master's in Computer Science (AI track)
Stanford University, USA [Dropout]
Master's Semester Exchange, 2018
Btech. in Electrical Engineering (ML Minor), 2018
IIT Kanpur, India
* indicates submitted and pending review
For a complete list, kindly see my CV
Developed a novel deep architecture for predicting future locations of people observed in first-person videos. Released a new dataset on human locomotion seen in FPV. Paper under review at CVPR’18.
Web-app for course recommendation using recommendation engine and text analysis. Won OVERALL BEST PROJECT in Google DevFest 2016. See project page for details.
Designed a novel algorithm to extend application of cellular automaton based image processing methods to grayscale images. Paper published at 28th Irish Signal and Systems Conference 2017
Designed a knowledge distillation procedure aimed for compressing Fully Convolutional Network (FCN) with skip connections such as U-net and Stacked Hourglass Network. Achieved ~100x model compression.
Implemented various classfiers for human emotion detection in the Emotion Recognition in the Wild Challenge 2016 dataset to compare against results from CNN based approaches. Details on project page.
Deisgned and developed early prototypes of an onboard image processing pipeline capable of underwater object recognition and autonomous manoeuvre. The current updated code is available here.
We aimed to develop a measure for synchrony measurement between speakers in one on one conversations. It was ndergraduate Research project for junior year under Prof. Tanaya Guha IIT Kanpur
Implemented a recommendation engine pipeline for e-commerce products. For pre-processing, designed a PGM based procedure for feature selection based on IAMB algorithm and for recommendations, trained a Collaborative filtering based Restricted Boltzmann Machine on Amazon datasets. The corresponding code is confidential being a product of my work as Research intern at Busigence in winters 2016.
I have worked as a Academic mentor in Counselling Service, IITK for