
Graduate Student
- CS Department
Rochester Institute of Technology
Email : iss8405@cs.rit.edu
Ph.No : 585-705-0589
WORK EXPERIENCE
Nov 2007 – May 2008 Co-op Software Engineer – Software
Configuration Management Department
Thomson-West,
·
OS : Windows
·
Languages Used
: Java, VC++ and .NET(for deployment)
·
IDEs Used : NetBeans(Java) and Visual Studio(.Net and C++)
Work
Description: Took part in the
Projects assigned to the Tools team within the Software Configuration
Management Department. The Projects basically were based on ‘.NET builds’ over
objects, which were built using VC++ and Java. Exposed to a lot of real-time
issues from running a build to setting-up an automated system. Learnt how to
handle these kinds of issues. The Software Configuration Management Automation
System (SCMAS) developed and used by Thomson-West is a System that holds the
actions of the Project. This SCMAS is a tool developed to automate the Projects
and its processes. A major part of the co-op work was in this project. There
were few other projects in which I assisted the lead engineers.
EDUCATION
ü
2006 – 2008 Master’s Degree in Computer Science
Rochester Institute
of Technology,
ü
2002 – 2006 Bachelor’s Degree in Computer Science &
Engineering
ü
2001 – 2002 High School with Major in Computer Science
Shrine Vailankanni Matriculation Higher Secondary School,
ü
1999 – 2000 Grade 10
Perks Matriculation Higher
Secondary School,
COURSES AND PROJECTS
|
Master’s
Project |
Project Proposal Presentation 1 : link The above presentation is about “E-bid
Framework”. Reference Papers: (will post them by tonight) Project Proposal Presentation 2 : link <- yet to be scheduled The above presentation is on “Privacy
Protection in Data Mining”. Reference Papers: -
This LINK
is very useful to find the range of papers published on Privacy Protecting
Data Mining. -
“Privacy Preserving Data Mining” by Agarwal
and Srikant : here -
“State-of-the-art in Privacy Preserving Data Mining” by Verykios, Bertino, Fovino, Provenza, Saygin, Theodoridis : here -
“Achieving Privacy Preservation When Sharing Data For Clustering” by S
R M Oliveira and O R Za¨ıane : here -
“Privacy Preserving Mining of Association Rules” by Srikant,
Agarwal, Evfimievski and Gehrke : here -
“Tools for Privacy Preserving Distributed Data Mining” by Kantarcioglu, Vaidya, Lin and
Zhu : here |
|
Secure
Database Systems Prof. Rajendra K Raj Winter 2007 |
Airline Auction System Find the presentation
of the project here. |
|
Introduction
to Data Mining Prof. Carol Romanowski Fall 2007 |
Mining of Letter-Recognition Dataset Find the presentation
of the project here. |
|
Database
Systems Prof. Walter Wolf Summer 2007 |
Home Contact List Description: Find the presentation of the project here. |
|
Active
Database Systems Prof. Rajendra K Raj Spring 2007 |
Distributed e-bid Framework Description: Find the presentation
of the project here. The demo for the
framework that we developed can be found here
as a presentation. |
|
Introduction
to Computer Vision Prof. Roger S Gaborski Winter 2006 |
Man-Made Object Detection Description: Find the presentation of the project here. The results for all the images can be found in
this Word
Document. |
|
Secure
Software Systems Prof. Rajendra K Raj Fall 2006 |
Sarbanes
Oxley Compliant Virtual Private Database Description: Find the Presentation of the project here. |
|
BE – CSE
Final Year Project Dr. Gurumurthy
K Ramanan |
Active Shape Model (ASM) in Implementation Image
Recognition Description: Model-based vision is a robust approach to recognize and locate known
rigid objects in presence of noise, clutter and occlusion. It is more
problematic to apply model-based methods to images of objects whose
appearances can vary though a number of approaches based on the use of
flexible templates have been proposed. The problem with existing methods is
that they sacrifice model specificity in order to accommodate variability
thereby compromising robustness during image interpretation. The Active Shape
Model (ASM) differs from other Model-based Approach by the way it deforms to
fit the data consistent with the Training set. In this, a model is trained
from a set of images marked with landmark points. By analyzing the variations
in shape over the training set a model is built. To interpret a new image,
first the parameters which best match the model instance to the image are
found. Thus the model is fit to the image and image search is made. Find the presentation
of the project here. |
AREAS OF
INTEREST : Programming,
Software Development, Pattern Recognition, Networks, Security
REWARDS
Ø
Merit Rank in
National IT Aptitude Test (NITAT) conducted by NIIT (2005)
Ø
Credit Award in
International Assessments for Schools in Mathematics conducted by
Ø
Achievement
Award in International Assessments for Schools in Mathematics conducted by
EXTRA-CURRICULAR ACTIVITIES
1.
Out-door Games
: Shuttle, Bowling, Cricket
2.
Games that I
love to watch : Soccer (My Favorite Team :
3.
Instrument
that I play : Veena
4.
Weekend Movies
: Anything except Scientific Fiction
5.
Like Trekking
(Did not have a chance yet in US)
Sites that I often browse
(yet to be updated)