Graduate Research Assistant

Classification of plankton images taken from the ocean

I am currently working on the Bigelow project in the Computer Vision group at UMass. My advisor is Dr. Allen Hanson.

Planktons are the smallest living beings in the ocean and are critical for the ocean ecosystem for various reasons.

An automatic system to identify and count the number of different types of zoo and phyto plankton would be a great tool in the hands of marine scientists. At UMass, we are working on such a system and also developing new algorithms to achieve accurate results. Our data comes from underwater images, and from a Vision point of view, the task is extremely challenging.

Graduate Research Assistant

Efficient tracking of moving objects in surveillance video

• Masters thesis and research
• Advisor - Dr. Donna Haverkamp
• Worked on Intelligent algorithms and Image processing techniques for Automatic Video Surveillance
• Developed a new Bayesian algorithm for tracking.
• Used smart algorithms for background modeling and moving object segmentation.
• Developed a new concept called Vicinity Factor for improved tracking and segmentation

With no prior work in tracking done at the University, the KUVidAnalysis work was aimed at kickstarting a surveillance and tracking research group at Kansas.

My honors thesis "Automatic Tracking of Moving Objects in Video for Surveillance Applications" can be found here. Part of the work was accepted at the Object Tracking and Classification in and Beyond the Visual Spectrum (OTCBVS) workshop at CVPR 2007 Minneapolis. Here is the paper - A Bayesian algorithm for tracking multiple objects in surveillance video.

Presentations

• Thesis
• CVPR 2007 OTCBVS paper
  

Lead Avionics Engineer

Development of a new generation balloon system to support the Honeywell corporation funded Nanosatellite called KUBESAT.

• Design and development of avionics, software and structure for HABS that is responsible for deployment and recovery of KU's Balloon Satellite
• Developed the newer generation (HABS-3) system with improved power system, additional robustness to failure, better interfacing and improved software version
• The balloon satellite system is capable of deploying a satellite upto a height of 100000 feet above the earth and is required to recover the satellite after each launch
• The HABS-3 system was the best HABS system designed for KU till date

One of the most challenging and interesting projects I have worked on. Lab work was one thing, but the launch and recovery of the balloon satellites was something else. We would launch the balloons after detailed weather analysis and predictions and then chase the balloons in vans while locking on to the radio signal that was emitted by the balloon. The chases were "twister" style (The Jodie Foster movie) and one of our vans also had a road accident on one such chase.

I got first interested in AI and Machine Learning by working with Dr. Xue-wen Chen in the KU Knowledge Discovery in Bioinformatics group.

I worked on Protein Sequence Alignment (SAGA, CLUSTAL, HMMer) and Feature Reduction in Breast Cancer Data using Support Vector Machines (SVMs).

Classification of Trading Strategies in Adaptive Markets - Machine Learning course project [report] [presentation]

• Classified behavior patterns of trading agents in the CAT agents tournament enviroment by using Support Vector Machines and Hidden Markov Models

Detection of video shot transition boundaries using various algorithms

• Implementation of Motion Compensated DCT compression in video frames Implemented using C++ language and KU Image Processing Libraries

• Used Support Vector Machines (LIBSVM) to categorize a two-class text corpus

• Disambiguation of word pairs, implemented using C++

• Study of statistics involved in human language for further applications like Speech generation and Machine Translation

• Course project for Information Retrieval class

• A feasibility study in use of Support Vector Machine (SVM) based RFE feature elimination in breast cancer patient data

• Used a hierarchical Neural Network approach to classify rock data to identify oil bearing rocks
  

• Classified radar signature data obtained from airplanes using Neural Networks on MATLAB platform

• A detailed study and performance comparison of various Protein Alignment algorithms
• Quickly learned theory and implementation of diverse algorithms: Saga, Clustal and HMMer

• Designed and implemented various algorithms for robot competitions like Maze traversing, Robot Football, Robot Races, Robot Sumo