Classes I took at UMD and some of my academic projects




Spring 2009

1) Advanced Machine Learning
    Instructor: Dr. Rich Maclin

Research Paper Implementation: SVMTool
The aim of this project is to understand the details of the method described in 
SVMTool: A general POS tagger generator based on Support Vector Machines and implement it to some extent in order to demonstrate the understanding.


Fall 2008

1) Advanced Computer Architecture
    Instructor: Dr. Ted Pedersen

Samudra-Manthan
The aim of this project is to dig out a list of top R terms of varying lengths M through N that are especially interesting using the TF*IDF measure, from a large corpus of text. The goal is to do this as fast as possible with the use of multiple processors, but still retaining the accuracy. We are using the Gigaword corpus (a large archive of newspaper stories) as an input to this system.



Spring 2008

1) Advanced Computational Logic
    Instructor: Dr. Hudson Turner

2) Abstract Algebra II
    Instructor: Dr. Robert McFarland



Fall 2007

1) Human Computer Interaction ( http://www.d.umn.edu/~willemsn/courses/cs8561_fa07/ )
     Instructor: Dr. Pete Willemsen    
     
    Haptic Sound Generator
    Platforms Supported: Ubuntu
    Though this application is not tested on other unix platforms, it is likely to work on most of the unix platforms.

    This is a Haptic Piano Player, in which frequency of the sound is changed according to the key pressed by the haptic device pointer.
    Moreover, amplitude of the sound is changed according to the force applied by the user on the key.

2) Abstract Algebra I
    Instructor: Dr. Joseph Gallian

3) Natural Language Processing ( http://www.d.umn.edu/~tpederse/teaching.html )
     Instructor: Dr. Ted Pedersen


          
Projects done during Master in Computer Science at Fergusson College ( affiliated to TheUniversity of Pune )

1) Pattern Recognizer (2005)
Platforms Supported: Windows
Download: Pattern-Recognizer.rar
This is a basic image processing tool which gives the functionalities such as Image Filtering, Edge Detection, Color Processing and mainly Pattern Matching using Correlation. This is developed using Component Object Model (COM) technology. This is a Client-Server architecture. The server provides image processing functionality to the client through interfaces. The client provides GUI and uses services provided by the server. The client is completely encapsulated from the internal logic of the server.