Hello ,
I'm Kavya sree Oleti Ramanjulu

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About Me

About Me

I'm Kavya Sree Oleti Ramanjulu

Software Engineer | TIBCO Developer

I am Kavya Sree Oleti Ramanjulu, a dedicated and accomplished software developer with a robust educational background and extensive professional experience. I have a proven track record of optimizing integration solutions and enhancing transaction efficiency through my roles at Tata Consultancy Services and Infosys Ltd. My expertise spans multiple programming languages, integration platforms, web technologies, and cloud services, alongside a strong proficiency in CI/CD pipelines, Agile methodologies, and various SDLC models. I have successfully collaborated with diverse clients, including TFS, Telstra, and Citibank, delivering strategic solutions that meet their unique requirements. I am passionate about leveraging advanced technologies to drive innovation, evidenced by my recent project on AI-driven solutions for the healthcare sector. I continuously strive for excellence, as reflected in my certifications in AWS, Azure, and TIBCO.

Email : ramanjulukavya@gmail.com

Location : Seattle, WA, willing to recolate

Open to work : Actively looking for a full-time position

Skills & Abilities

My Education

MS in Computer Science

California State University, Dominguez Hills

STEM 3.929/4.00

2022 August - 2024 May

BE in Electronics and Communication Engineering

Panimalar Engineering College, affiliated to Anna University

CGPA : 8.96/10

Gold Medalist : Awarded the 26th Rank among 17,534 candidates

2014 August - 2018 July

Higher Education

Swami Vivekanand Inter College

CGPA : 9.68/10

2012 August - 2014 July







Projects

OPTIMIZING CLINICAL DECISIONS: RAG-ENHANCED AI TEXT RETRIEVAL WITH OPENAI AND LANG CHAIN

Enhancing clinical text retrieval, this project employs GPT-3.5 turbo for language processing and Lang Chain for data indexing. Using Retrieval-Augmented Generation (RAG) and vector databases, it improves accuracy in extracting information from pathology reports crucial for cancer diagnosis. TruLens evaluates RAG's performance, ensuring precise analysis and showcasing AI's potential in healthcare.

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PRIZE COLLECTING TRAVELLING SALESMAN PROBLEM USING MULTI-AGENT REINFORCEMENT LEARNING

Optimized hyperparameters to get the optimized solution for prize collecting travelling salesman problem using multi-agent reinforcement learning. Compared its performance with other algorithms.

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SENTIMENTAL ANALYSIS ON AMAZON PRODUCT REVIEWS

Used cutting-edge data refining methods like tokenization, removing stopwords, and TF-IDF vectorization to prep Amazon product reviews for sentiment analysis. Employed Multinomial Naive Bayes, Logistic Regression, and Random Forest models to precisely classify Amazon reviews, empowering businesses with actionable insights for better decisions and happier customers.

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MINIMUM ENERGY PATH IN IOT SENSOR NETWORK USING DIJKSTRA’S ALGORITHM WITH PRIORITY QUEUE

This project aims to find the minimum-energy data offloading path in an IoT sensor network using Dijkstra’s algorithm with a priority queue. The network is modeled as a graph where nodes represent sensor nodes, and edges represent the communication links between them. The objective is to ensure efficient data transfer with minimum energy consumption.

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DATA COLLECTION IN IOT SENSOR NETWORK USING ROBOTS

This project aims to implement and evaluate three algorithms for data collection in an IoT sensor network using robots: Greedy 1, Greedy 2, and MARL. The network is modeled as a graph where nodes represent sensor nodes and edges represent the communication links between them. The objective is to ensure efficient data collection with minimal energy consumption using a battery-powered robot.

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Experience

Research Assistant | On Campus

Sept 2023 - May 2024

TLTC Supplemental Instructor | On Campus

Sept 2022 - May 2023

TIBCO Developer | Full Time

Feb 2022 - Aug 2022

Technology Analyst | Full Time

April 2021 - Dec 2021

Senior Software Engineer | Full Time

Jan 2020 - Mar 2021

Systems Engineer | Full Time

Sept 2018 - Dec 2019

System Engineer Trainee | Full Time

May 2018 - Aug 2018

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