Welcome to my academic homepage!

I am a first-year Computer Science graduate student at the University of Maryland, College Park. My research interests lie in the intersection of Computer Vision, Computer Graphics and Deep Learning with an application domain of Augmented and Virtual Reality.

Previously, I was a researcher at Innovation Labs, Tata Consultancy Services collaborating with Dr. Lovekesh Vig and Ms. Ramya Hebbalaguppe. I completed my undergrad in Computer Science and Engineering at Indraprastha Institute of Information Technology Delhi (IIITD). At IIITD, I was fortunate to work with Prof. Saket Anand and Prof. Ojaswa Sharma on interesting problems of scene reconstruction and procedural modelling.

  • Deep Neural Network Optimization
  • 3D Scene Understanding
  • Hand Gestural Interfaces for AR
  • Situated Visualization
  • M.S. in Computer Science, 2021-2023

    University of Maryland, College Park

  • B.Tech in Computer Science and Engineering, 2017

    Indraprastha Institute of Information Technology Delhi

Recent Updates

  • 18th Oct 2021: My co-authored work “Rethinking Common Assumptions to Mitigate Racial Bias in Face Recognition Datasets” won the best paper running up award at ICCV (HTCV ‘21)! Congrats to all the co-authors.

  • 1st Aug 2021: My co-authored work “Rethinking Common Assumptions to Mitigate Racial Bias in Face Recognition Datasets” accepted at ICCV (HTCV ‘21) as a oral paper. My first publication as a UMD student!

  • 25th May 2021: I have started my grad school at University of Maryland, College Park.

  • 13th Apr 2021: My co-authored work “Cross-Domain Multi-task Learning for Object Detection and Saliency Estimation” accepted at CVPR (CLVISION ‘21) as a poster.

  • 14th Feb 2020: Received TCS Citation Award for the second time for outstanding contributions to the organization through publications.

  • 20th Jul 2020: Invited as a reviewer for IEEE Transactions on Circuits and Systems for Video Technology (TCSVT, impact factor: 3.599). My first journal reviewing experience!

For older news visit here.


Researcher, IT Analyst
Aug 2017 – Aug 2021 New Delhi

Responsibilities include:

  • Research - Computer Vision, Deep Learning and Artificial Intelligence
  • Developing Augmented Reality prototypes
  • Prototyping and Deploying
Teaching Assistant
Jan 2017 – May 2017 New Delhi
Designing course curriculum, CUDA assignments and projects for the course of GPU Computing at Graduate and Post graduate level at IIIT-Delhi.
Software Development Intern
Jan 2017 – Mar 2017 New Delhi
  • Fine-tuned control of Fatigue Testing Machine(FTM) used for evaluating material strength and fatigue visualization.
  • Worked with .NET technology for developing data analysis tool for PID controller data of FTM.
Research Intern
May 2016 – Aug 2016 New Delhi
  • Worked on Augmented Reality with Google Cardboard for Android Platform.
  • Development of hand gesture interaction techniques for Google Cardboard for Augmented Reality.
  • UI development and text rendering for Google Cardboard application.


Deep Neural Network Compression

Compressing deep neural network models for memory constrained devices


A non-intrusive, relevant and temporally coherent overlay placement technique

Draw In Air

A hand gesture based in-air touch-less interaction technique for AR applications

Robust 3D Reconstruction of Indoor Scenes using Deep Learning

Developing an end to end pipeline for automatic generation of 3D models of indoor scenes.

Distributed Fault Tolerant Multi-Robot Area Coverage Under Limited Communication Ranges

Analysed Multi-Agent area coverage problem for surveillance purposes.

Modelling Vegetation with L-Systems Using an Image

Procedural modelling of vegetation using context-free grammar


A sketching interface for rapid designing of freeform 3D models from 2D sketches

Virtual Campus Project

Creating a virtual walk-through of IIIT-Delhi campus

Recent Publications

Quickly discover relevant content by filtering publications.
(2021). Cross-Domain Multi-task Learning for Object Detection and Saliency Estimation. In CLVISION, CVPR.


(2020). An Empirical Study of Iterative Knowledge Distillation for Neural Network Compression. In ESANN.


(2020). Variational Student: Learning Compact and Sparser Networks in Knowledge Distillation Framework. In ICASSP (Oral).

Preprint PDF