Sivaramarajalu Ramadurai Venkataraajalu is pursuing a Master of Science in Computer Science from SUNY Buffalo with expected graduation in December 2016. He has a Bachelor of Technology in Information Technology from Anna University, Chennai. His technical skills include Java, C, Python, R, Apache Solr, HP Loadrunner, Dynatrace, Tableau, Hadoop, PING Identity, Oracle Access Manager, Spring, and Angular JS. He has worked as a software development intern at Likeminds Consulting and as a performance engineer at Cognizant. His academic projects include a faceted search system using Apache Solr, a 3-tier online retail application using Spring Framework,

1. Sivaramarajalu Ramadurai Venkataraajalu
Email - sivaramarajalurv@gmail.com https://www.linkedin.com/in/sivaramarajalu
Phone - 716.335.2504 https://github.com/sivaramarajalu
ACADEMIC BACKGROUND
Master of Science - Computer Science Expected Dec 2016
State University of New York at Buffalo, United States
Bachelor of Technology - Information Technology May 2013
Anna University, Chennai, India
COURSEWORK
Modern Networking Systems, Algorithms, Information Retrieval, Distributed Systems, Machine Learning, Data Intensive Computing
TECHNICAL SKILLS
Language Proficiency : Java (Proficient), C, Python, R
Tools : Apache Solr, HP Load runner, Dynatrace
Data Analytics : Tableau, Hadoop
Access Management : PING Identity, Oracle Access Manager
Web Frameworks : Spring and Angular JS (Beginner)
Java Performance Analysis Tools : Eclipse Memory Analyzer, GC Log Viewer, Access Log Analyzers
PROFESSIONAL EXPERIENCE
Summer Intern, Likeminds Consulting Inc. May 2016 –August 2016
Client: IEEE, USA Role: Software Development Intern
 Developed and maintained RESTful web services that support JSON to provide Single Sign-on experience for vendor
applications using Spring MVC, Spring Web Services, JSON, Log4J, RESTful and Maven
 Developed cookie filters to support co-existence of Ping Identity and Oracle Access Manager thereby providing necessary
development time for legacy applications to adopt PING over subsequent production cycles
 Wrote various ONGL and Groovy scripts to customize authorization rules in Ping Access that reduced development time in
applications present inside the security realm by 10-15%
Programmer Analyst, Cognizant August 2013 –July 2015
Client: Travelers, USA Role: Performance Engineer
 Identified various performance bottlenecks in the application by analyzing the Heap dumps, Thread dumps, Memory Leaks,
Connection Leaks and GC Pattern. Conducted various performance tests to generate necessary load on the system
 Designed and developed performance test scripts and performed live monitoring and profiling using Dynatrace
 Analyzed Automatic Workload Repository(AWR) reports and reduced runtime of SQL queries by up to 20%
 Automated the process of inserting transaction names in performance scripts thereby increasing productivity by up to 40%
ACADEMIC PROJECTS
 Web based multi-lingual faceted search system.
Designed a web based search system to retrieve incident specific search system from social media by grouping the
influencers, topics and places. Features include content tagging, faceted search and graphical analysis of collected data.
Technology used: Java, Ruby on Rails, Apache Solr, Bootstrap JS, jQuery.
 3-tier application implementing on-line retail store.
Data Access Object [DAO] pattern were used for database calls. Concurrency Utilities were further deployed to handle
asynchronous calls and thereby optimizing performance
Technology used: Java (Spring Framework), Oracle10g.
 Simplified Distance Vector Routing Protocol in C.
Implemented Bellman-Ford equation to solve for the shortest route from a source to destination. The routers sent
distance vectors over UDP sockets and consequently they all converge to form a complete network
 Hybrid peer-to-peer file sharing application using TCP/IP Socket Programming
Designed and implemented a server assisted chat and file sharing system similar to Napster. Implemented push and
pull technologies for file transfers. (Similar to FTP)
 Classroom Scheduling Problem with Apache Hadoop
Chained Map Reduce jobs were written to solve the Big Data problem of course and classroom scheduling at
University at Buffalo. Map Reduce results along with time utilization and other insights were visualized using Tableau
RESEARCH EXPERIENCE [Current Semester]
Performance Evaluation of 802.11ad Wi-Fi in Indoor WLANs using the first commercial 802.11ad router [Talon AD7200] and laptops
equipped with 802.11ad cards. Project also involves experiment automation using bots and manipulation of Linux device drivers to
effectively study the internals of 802.11ad’s beam forming mechanism.