I am a PhD candidate in the Department of Computer Science at The Johns Hopkins University. I am part of the Computational Interaction and Robotics Lab, I am advised by Dr Bruno Jedynak and Dr Gregory D Hager.


Visual Object Counting: In this work, doubly stochastic Poisson processes and convolutional neural net classifiers are used to estimate the number of instances of an object in an image. We tackle the inherent computational and storage complexity associated with the Cox formulation by employing the Kronecker algebra, taking advantage of the separability of covariance kernels.

Efficient Search: We consider the problem of quickly localizing multiple instances of an object in an image by asking questions of the form ``How many instances are there in this sub-region?", while obtaining noisy answers. We propose a policy for called the dyadic policy for creating image sub-regions and derive analytical expressions for the posterior distribution for this policy, and in turn use this to localize objects.



Teaching assistant for the following courses:

  • Algorithms for Sensor Based Robotics in Spring'18.

  • Introduction to Computer Vision in Fall'16.

  • Introduction to Machine Learning in Spring'14.

  • Past Projects

    Asteroid detection: The objective of the project was to develop asteroid detection algorithms that can be hosted on-board a small spacecraft (with limited computational and storage facilities) to serve as a fully autonomous early warning system for asteroids approaching the earth.

    Computational Stereo: Stereo matching and correspondence on the da Vinci surgical system.

    Barrett's Esophagus: Detection and classification of lesions in the human esophagus using endoscopic images.

    Capsule Endoscopy: Capsule Enscopy is used in the diagnosis of Crohn's diesease, intestinal tumors and ulcers. We developed an ordinal regression framework to rank the lesions in the gastro-intestinal tract using sparse pair-wise preference relationships annotated by the physician.


    first name at cs dot jhu dot edu
    Hackerman 136, 3400 N Charles Street, Baltimore, MD-21218