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RAKESH NAGARAJU



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RAKESH NAGARAJU


Hi, Welcome...!   
I am a Software developer, currently pursuing Master's in Computer Science.
Residing in San Jose, I am open to work and am currently looking for a Full-time position in Software development.

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HELLO,
I'm RAKESH
I'm available for work.

I would describe myself as a passionate programmer and a professionally committed person. I am actively seeking a full-time or an internship opportunity to utilize my expertise, in achieving the company's goal.

Available for:
● Associate Consultant
● Software Developer
● Machine Learning/Security Engineer.

Experience: 2 Years 8 months
● Former Associate Consultant
● Former Senior Software/ Software Engineer
at Capgemini.

Contact:
rakesh.nagaraju@sjsu.edu
rakenju@gmail.com

Phone:
+1 669(288)-4508

Website:
https://rakesh-nagaraju.github.io

About Me:

1 / 4
My Undergrad College @NMIT
2 / 4
My Graduation
3 / 4
My Office in Bangalore @Capgemini
4 / 4

Complete details of programming skills:

Languages/ Frameworks: Python, Java, C, C++, JCL, COBOL, SQL, OpenMP, Shell Scripting, JUnit.
Front-End: JavaScript, HTML, CSS, CICS, Swift.
Wireless Networking: 2G, 3G, 4G, 5G, wireless sensors, IoT.
Big-Data: Apache Hadoop, Apache Spark and Apache Hive, Flume, HBase.
DBMS: Microsoft SqlServer, DB2, Oracle, MySql, Postgresql.
Cloud: OpenStack and AWS EC2, RDS, S3.
ML/Security: GAN’s, CNN, ML/ Cipher algorithms, Scipy, TensorFlow, Keras, Pytorch, OpenCV, OpenCL.
Tools: Grpc, Zookeeper, CUDA, Android Studio, Git, MS Office, macOS, Windows, Linux/Ubuntu, Jenkins, Maven, Visual Studio Code, Eclipse IDE, MySQL Workbench, Android Studio, MS Office, Zeke Scheduler.
Others: DB2, Sqoop, Hadoop, Hive, Apache Spark, Zookeeper, sklearn, CUDA, Tensorflow, Keras, Jenkins.

Kindly do check out the other tabs for more info.

Currently pursuing Master's degree in Computer Science at San Jose State University with a GPA of 3.57.

Specialization :
Machine Learning, Artificial Intelligence, Cryptography and Information Security.
Relevant Coursework:
Machine Learning, Artificial Intelligence, Distributed Computing, Cryptography and Information Security, Database System principles, Design and Analysis of Algorithms.

Additionally, I did my Bachelor's in Computer Science at NMIT in India.
My hands-on experience and knowledge include: Data structures and Algorithms, Database/ Advanced-Database Management, Data Structures, Object-Oriented concepts, Python, JAVA/J2EE.
For more information, academic performances, kindly check the table below.

● I have a total work experiece of about 2 Years 8 months
● Experienced in developing Front-end UI and Back-end applications
● Experience in Agile methodology of development

Technology :
JAVA, Python, COBOL, CICS, JCL, DB2
Expertise :
Software development in Agile methodology
Roles :
Associate Consultant, Senior Software Engineer, Software Engineer

Career Summary:

Ex capgemini employee, professionally committed developer, with expertise in Front-end UI, Back-end software developement through Agile methodoly, Unit Testing, Requirement Analysis, Production support.

For more info on my Roles and experience check below.

Experience letter: File type : pdf

● Apart from Profession, I am very keen in learning new technologies and working on new, creative projects.
● Feel free to scroll to Projects tab and have a look at various projects I have worked on.

Kindly do check out the other tabs for more info.

● Hi, I have worked on variety of creative and unique Projects.
● I have had the opportunity to work with many brilliant Professors and their inputs have certainly helped me evolve as an efficient developer.
● Kindly check out my work below!

Language/ Concepts learned:
Python, JAVA, C, HTML, CSS, Javascript, ReactJS, Swift, Unity 3D, Android Studio

Technology Used:

Machine Learning, Artificial Intelligence,
Hadoop, Spark, Encryption/Decryption,
Distributed Computing,
Algorithms,
Parallel Processing,
Wireless Mobile Networking.
CUDA, Big Data(Hadoop/Spark), Security, GRPC, Zookeeper, Cloud, Malware detection.

Relevent Skills:

• Python • Machine Learning • Software Development (Agile/ Waterfall) • Cryptography and Information Security
• Artificial Intelligence • Web Development- Full stack • JAVA and J2EE • Data Analytics (Hadoop, Spark)
• Distributed Computing • Algorithms

My Projects:

Machine Learning Projects

→ 1. Malware Classification Using GANS - Master's Final Year Project

Completion: Expected, Spring 2021.

The main idea of this project is use Malware samples as Images and apply GAN's for classification. The reason for converting malware to images is because the cost of extracting and analyzing malware samples such as: opcodes is very costly. And since GAN's are the next big thing in Machine Learning and also good with images, I plan to use GAN's.

The project has been started in Fall 2020 under the guidance of Professor Mark Stamp, SJSU and is expected to finish by Spring 2021.

→ 2. Analysis of various algorithms for Breast Cancer cell classification

Completed: Fall 2019

In this project, we implement seven different Machine Learning algorithms for Breast cancer classificaation using Python.
● Algorithms include Support Vector Machine(SVM), Logistic Regression, K-nn, Random Forest, Decision Tree, Naive Bayes and also a Neural Network.
● Dataset: Breast cancer dataset from Kaggle.
● Accuracy, Area under the curve(AUC) for PR curves and ROC curves are plotted to analyze performance.

Github Link: https://github.com/Rakesh-Nagaraju/Analysis-of-ML-algorithms-for-accurate-Breast-Cancer-Classification.git

Cryptography and Information Security

→ 1. Various Ciphertext algorithms.

Completed: Spring 2020

As a part of Cryptography course succesfully understood the concepts and implemented following :

● Simple substitution cipher, Double Transposition cipher, A5/1 cipher, Tea cipher, Cmea cipher,
Knapsack cipher, Pkzip cipher, RSA cipher, Rabin cipher.

Github Link: https://github.com/Rakesh-Nagaraju/Cryptography_projects.git

Artificial Intelligence

→ 1. Pedestrian Detection using Faster RCNN with Repulsion Loss :

Completed: Fall 2019

● In Real-world scenarios, detecting Pedestrians can be a challenging task especially in a crowd, as many Individual pedestrians can gather around and occlude each other.
● In this Project, we design a model which detects Pedestrians by utilizing Repulsion Loss, based on faster RCNN with the intention improving efficiency.
● We also compare the Mean Average Precision, PR curves for both Repulsion Loss implemented on SSD (Single Shot Detector) and Repulsion Loss on Faster RCNN.

Github Link: https://github.com/Rakesh-Nagaraju/Pedestrian-Detection-using-Faster-RCNN-with-Repulsion-Loss

Database Projects

→ 1. Twitter Data Analysis on COVID19 using Hadoop Flume Hive and Spark :

Completed: Spring 2020

● In this project we use the Hadoop framework to analyze unstructured Twitter data and perform sentiment and trend analysis using Hive on MapReduce and Spark on keyword “COVID19”.
● We then compare the Hive and Spark approaches to determine the best performance.
● First, we Sign up a Twitter developer account and retrieve COVID-19 related Twitter data using Flume and store it in Hadoop HDFS.
● Perform Sentiment Analysis by creating Hive tables and quering the database.
● Perform Trend Analysis using spark by creating sparkcontext and filter out Trends based on re-tweets and likes.
● Compare both the Hive and Spark approach by performing Volume Testing and Sentiment Analysis on the data available.

Github https://github.com/Rakesh-Nagaraju/Twitter-Data-Analysis-on-COVID19-using-Hadoop-Flume-Hive-and-Spark..git

Design and Analysis of Algorithms

→ 1. Analysis of K-person Asymmetric TSP Problem using hybrid Ant Colony approach :

Completed: Summer 2020

● In this project, we consider a variant of the well know Travelling Salesman problem (TSP). In particular we consider the k-person Asymmetric TSP known as the ‘k-ATSPP’ problem. Suppose we have an Asymmetric graph G = (V, A) with two distinguished nodes s, t ∈ V.
● Our goal is to find the k paths such that it starts from s and ends at t where union of all k paths cover all the nodes only once.
● Main result is a modified Ant-Colony Optimization (ACO) that includes 3-OPT for optimization and Genetic algorithm (GA) to create new improved paths.
● We test this algorithm against a TSPLIB dataset against various test cases.
● The results are compared, and time complexity is analyzed.
● The algorithm performs well with large data while maintaining optimal to sub-optimal quality of the results.
● Finally, we also analyze the reasons for achieving such results.

Github Link: https://github.com/Rakesh-Nagaraju/Analysis-of-K-ATSPP-problem-using-hybrid-Ant-Colony-approach.git

Distributed Computing

→ 1. Chain Replication Using Python Kazoo. :

Completed: Fall 2019

● In this project we implement chain replication. Specifically, we will be implementing a replica that will form part of a chain replication chain. We will deal with links (replicas) going away and new links arriving as the server connected in a network may be the head or the tail or just a replica in the chain.
● For our implementations, we will use grcp with the proto file chain.proto(in the repository) to interoperate.

Github Link: https://github.com/Rakesh-Nagaraju/Chain-Replication-Using-Python-Kazoo..git

→ 2. ABD Protocol :

Completed: Fall 2019

● In this project we implement ADB protocol for succesfull client-server distributed computing.

Github Link: https://github.com/Rakesh-Nagaraju/ADB_protocol_using_python_and_google_grpc.git

→ 3. RAFT :

Completed: Fall 2019

● In this project we implement RAFT protocol for successfull distributed Computing. Specifically, we will be implementing a replica that will form part of a chain replication chain.
● Raft is a consensus algorithm that is designed to be easy to understand.
● It's equivalent to Paxos in fault-tolerance and performance.

Github Link: https://github.com/Rakesh-Nagaraju/RAFT_python_implementation_using_google_grpc.git
Kindly do check out the other tabs for more info.

Cerfication and code Competitions:


  1. I am officially certified in “IBM certified DB2–9 Fundamentals”.
  2. My passion has driven me to participate in various coding competitions such as: Google Hash Code 2020, Google Kick Start, Hackerank, Kaggle competition.
  3. I have also had the opportunity to volunteer for the "Food Pantry" at my University.

Letter of Appreciation:


My Pofessor's and my Manager have said a couple of things about me, please click below to know more:
  1. Adarsh Sadashiva (Team Leader/TSA/Manager, Capgemini)

    File type:pdf
    File size: 449 Kb
  2. Prof Sujatha Joshi (Phd, NMIT)

    File type:pdf
    File size: 571 Kb
  3. Prof Mohan BA (Phd, NMIT)

    File type:pdf
    File size: 501 Kb

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Wanna checkout my Resume, Please click below to download.



File type:pdf
File size: 75 Kb
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