Rithin Pullela Portfolio

About

Howdy 👋! I am Rithin Pullela, a Masters Stundet in Computer Science at Texas A&M University graduating in May 2024 and I am actively looking for fulltime job Software Engineering Job Opportunities! Here is a list of few of my Interests and Skills:

Backend Application Development:

Proficient in diverse programming languages (Go, Java, C#, Python) and frameworks (Springboot, Flask, Django, Ruby on Rails) for building efficient and scalable backend solutions.

Utilizing multithreading (Java) and go routines (Go) for concurrent execution, ensuring API responsiveness and efficient resource utilization.

A strong understanding of low-level and high-level design principles, along with expertise in object-oriented programming and design patterns, further reinforced by strong problem-solving skills demonstrated through 600+ LeetCode problems solved.

Experienced in test framework utilization (pytest, pyfixtures) for API testing, database management (SQL, Oracle DBs, MySQL) and NoSQL solutions, along with a comprehensive grasp of REST and gRPC for data communication.

Cloud Native Application Development:

Extensive hands-on experience with Docker for containerization and Kubernetes for orchestration. Proficient in setting up CI/CD pipelines using Jenkins and GitHub Actions for seamless integration and deployment.

Proficiency with cloud platforms and services, including AWS S3 for scalable storage, EC2 for virtual servers, and load balancers and API Gateways for efficient and secure communication within cloud-native applications.

Demonstrated experience in cloud-native application development, implementing Go routines for optimized code and utilizing Kafka for asynchronous communication between microservices, enhancing overall system scalability and responsivenes.

Possess a strong foundation in distributed computing, cloud computing, computer networks, and network security, ensuring secure and robust cloud infrastructure.

Machine Learning:

Adept in deep learning architectures, including transformers and convolutional neural networks (CNNs), gained through research paper exploration and practical application.

Proficient in model training and optimization, leveraging frameworks like PyTorch and TensorFlow while employing advanced techniques like data parallelization on GPUs for efficient large-scale training.

Demonstrated expertise in natural language processing (NLP) and Generative AI, showcased through projects utilizing OpenAI's API and vector databses and LAAMA2 fine-tuning with QLoRA.

Possess a strong foundation in machine learning fundamentals, encompassing linear regression, regression trees, bagging, boosting, and support vector machines (SVMs).

Professional Skills

Courses

Coursework :-

Data Structures and Algorithms, Object-Oriented Programming, Database management system, Data Mining and Data Warehousing, Data Science, Machine Learning and Computer Vision.

Online Courses :-

Machine learning Andrew Ng, Full stack Web development, Networking Fundamentals by Pluralsight

Technical Skills

Languages :-

C, C++, Java, Python, JavaScript, NodeJS, SQL, React

Tools & Libraries :-

Git, ServiceNow, Matlab, Simulink, NumPy, Pandas, Scikit-learn, TensorFlow, Keras, Pytorch, github actions

Education

Aug 2022- May 2024

Masters

Master of Science in Computer Science

Texas A&M University, College Station. CGPA: 3.9/4.0

Courses :

Software Engineering

Operating Systems

Machine Learning

Network Security

Jul 2017 - May 2021

Bachelors

Bachelor of Technology, Electrical Engineering

National Insitute Of Technology, Warangal. CGPA: 8.25/10

Courses :

Data Structures and Algorithms

Object-Oriented Programming

Work Experience

May 2023 - Aug 2023

Hewlett Packard Enterprise (HPE), SanJose

Software Engineerinng Intern

Developed and tested code in a Cloud Native Environment at HPE Green Lake Cloud Platform, utilizing Go and Python. Gained hands-on experience with cloud technologies including Kafka, Redis, Kubernetes, and Docker.

Enhanced test automation efficiency by leveraging Python fixtures for streamlined setup and teardown processes, resulting in a significant 70% reduction in testing time.

Achieved a significant reduction in API response time from 700ms to 260ms by leveraging Go routines, implementing Redis caching, and replacing the encoding/json library with the faster Jsoniter library.

Enabled external event integration via Kafka’s event-driven architecture for location updates and deletions.

Jul 2021 - Jun 2022

Oracle Financial Services Software Ltd., India

Application Developer

Contributed to the development of Cloud Native and On-Premise applications within an Agile environment, utilizing Java, Object-Oriented Programming (OOP), design patterns, Docker, Kubernetes, GIT, and JIRA.

Collaborated with the Data Integration team to seamlessly transfer banking data from bank files to Oracle Databases.

Pioneered a feature that identifies and discards bad files, over a specified threshold, and securely stores them in user-specified databases. This breakthrough resulted in three banking clients adopting the feature.

Implemented Multi-Threading in the Balance Computation Engine team to improve the Performance by 20%.

Took charge of the integration of a REST API, optimizing data retrieval and reducing reliance on shared databases, while progressing towards a Service-Oriented Architecture (SOA).

Projects

Bit Bid

Web Development, Django, Heroku, CI/CD, Docker

Led the agile development of BitBid auction platform developed in Django and Python as a scrum master and a developer, featuring a seamless all-pay auction design and secure Bitcoin transactions(prototype) through integrated Coinbase API.

Deployed on Heroku with CI/CD using GitHub Actions and Docker. Implemented a scalable architecture and asynchronous auction settlement using a cron job, ensuring optimal performance and user satisfaction.

Link : GitHub Code

Docu Mind (RAG)

Deep Learning, Vector Database, GPT3.5, tokenizers

Implemented a dynamic language model pipeline using Weaviate Vector Database and OpenAI text2vec tokenizer.

Leveraged the integrated system for semantic searches, enabling users to receive ChatGPT-driven insights from document snippets based on natural language queries.

Operating system

C++, Memory management, Multi-threading

Implemented dynamic memory allocation with page tables, translating physical addresses to virtual addresses.

Employed FIFO and Round-Robin algorithms for multi-threading. Developed a sequential file system with features such as inode lists and free lists, ensuring organized storage and retrieval of files.

Link : GitHub Code

Expense Sharing App

Web Development, ASP.NET MVC, C#, CI/CD, Docker, AWS

Spearheaded the development of a user-friendly expense sharing web application using ASP.NET MVC and C#, implementing intuitive features for seamless expense management, categorization, and editing

Deployed the application on AWS, leveraging Docker for containerization and establishing a robust CI/CD pipeline, enhancing project efficiency and ensuring consistent deployment

Link : GitHub Code

Image captioning

Deep Learning, LSTM, Transfer Learning, CNN

Developed an Image Captioning model using the Flickr 8k dataset, employing Transfer Learning with the InceptionV3 model for object recognition and utilizing an LSTM for processing partial captions. Got a BLEU score of 0.73.

Parallelizing Strassen’s Matrix-Multiplication Algorithm

C++, OpenMP, CUDA, Multi-Threading

Developed shared-memory parallelization using OpenMP for Strassen’s Matrix-Multiplication Algorithm, optimizing performance for matrices of size n x n.

Implemented CUDA-based parallel code, leveraging GPU architecture to accelerate Strassen’s Matrix-Multiplication Algorithm. Achieved enhanced efficiency for large-scale matrix computations with variable terminal sizes.

Fake News and Hate Speech Detection

BERT, Transformers, XgBoost, SVM, SMOTE

Fine-tuned BERT Transformer on LIAR dataset, achieving 86% accuracy and 0.7 F1 score for robust fake news and hate speech detection on social media. Addressed class imbalance using SMOTE technique.

Explored techniques like Bi-LSTMs, XgBoost, SVMs and Naive Bayes Classifier, but Finetuning BERT gave better results indicating contextual awareness is crucial for NLP tasks.

Link: GitHub Code

EduMetrics

Python, Pandas, Seaborn, scikit-learn

Conducted extensive data analysis using python, developed interactive visualizations showcasing the intricate relationship between education metrics and diverse development indicators across countries. Deployed the results on an interactive website built with Flask and React for accessibility.

Link: Website

Achievemnts, Awards and Activities

Awarded with Department Scholarship for academic excellence at Texas A&M University.
Awarded with Institute Merit Scholarship for academic excellence at NIT Warangal.
Co-founder of start-up Pool-In (Students material exchange platform to encourage re-usability).
Received the Best Captain award at ISNEE Electric Vehicle project.
Joint Secretary of Electrical Engineering Association at NIT Warangal.
Software Preparation Guide: Mentored and created a Software Job Preparation Guide for students covering Data Structures, Algorithms, and Object-Oriented Programming concepts.
Scored 328/340 in GRE (Quant: 169/170, Verbal: 159/170, AWA: 4.0/6.0).
Scored 113/120 in TOEFL.

Contact Me

Feel free to contact me for any colaborations and ideas to work on