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.