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Information Security Software Engineer

Location:
San Jose, CA
Posted:
March 16, 2020

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Resume:

Rakesh Nagaraju

669-***-**** San Jose, CA ***** adcbnm@r.postjobfree.com

www.linkedin.com/in/rakesh-nagaraju https://github.com/Raki2205 EDUCATION

M.S in Computer Science- San Jose State University, San Jose, CA Expected: May 2021 Coursework: Machine Learning, Artificial Intelligence, Distributed Computing, Cryptography and Information Security, Database System principles.

B.E in Computer Science- Nitte Meenakshi Institute of Technology, Bangalore, India May 2016 Coursework:Design and Analysis of Algorithms, Python programming, JAVA/J2EE, Data Structures, Advanced Database Management.

TECHNICAL SKILLS

Languages:Python, Java/J2EE, C/C++, MySQL, DB2, Mainframe JCL & COBOL, HTML5, CSS, PHP, JavaScript. Operating system:LINUX/UNIX(Fedora, Ubuntu), IOS, Windows, Android. Libraries:Keras, Scikit-learn, TensorFlow, Pandas, Numpy, Kazoo, Pickle, matplotlib, Scipy. Tools and Databases:Apache Spark, Tomcat, Eclipse IDE, MongoDB, Maven, JUnit, MySQL Workbench, Sqoop, Hadoop, Hive, Android Studio, Jenkins, MS Office, Netbeans, Zeke Scheduler, Visual Studio Code. ACADEMIC PROJECTS

Twitter Data Analysis using Hadoop Spr 2020

● In this project, we analyze unstructured data that is obtained from Twitter using Hadoop and then perform Trend, and Sentiment analysis using Hive on MapReduce and Apache Spark.

● We then compare Hive and Spark approaches to determine better performance. Cryptography and Information security Projects Spr 2020

● Successfully wrote code to implement various algorithms such as A5/1, ORYX, PKZIP, AES, DES, FEAL, RC4, RC6, TEA, Diffie-Hillman, RSA, message digest(MD4, MD5), SHA, HMAC, Digital signature, Rabin cipher. Most Accurate ML Model for Breast Cancer Classification Fall 2019

● Machine Learning model that classifies breast cell test report data as either Malignant or Benign.

● Trained seven different algorithms on a “Wisconsin Breast Cancer '' dataset using Python and its libraries.

● Generated ROC and PR curves to compare and determine the most accurate model. Real-time Pedestrian Detection - Artificial Intelligence Fall 2019

● A model with an accuracy of 79.8mAP that detects Pedestrians in real-time.

● Designed in a team of 4, by integrating the “Repulsion Loss”, a loss function, with “Faster RCNN” model with the help of PyTorch and CUDA.

Distributed Computing Projects Fall 2019

● Implemented ABD, Chain Replication and RAFT protocols to handle Client-Server communication, by utilizing Google gRPC, Python, Java, Zookeeper and Kazoo. WORK EXPERIENCE

Capgemini India Pvt Ltd, Bangalore - India

Associate Consultant Apr 2019 - Aug 2019

● Led a team for building applications in an Agile methodology of the Project cycle and also provided UAT support for the same.

● Created Functional Designs by analyzing the Business Requirements provided by the client.

● Experienced with Sprint and User story creation/estimation through Rally, QA Assistance. Senior Software Engineer Apr 2018 - Mar 2019

● Indulged in the designing and development of agile software development practices.

● Reduced Project Costs by 35% by automating tools to handle repetitive Change Requests.

● Handled banking applications related Production environment by solving P2 and P3 tickets in HPSM. Software Engineer Nov 2016 - Mar 2018

● Built software applications with the Waterfall model, generated monthly and yearly XML Reports.

● Designed applications related to JAVA, Mainframe, and query processing in DB2. ACTIVITIES AND CERTIFICATION

● Certified in “IBM certified DB2–9 Fundamentals”.



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