Computer Science Data

Venkat Biyyapu

Dallas, TX P: +1-945-***-**** ****************@*****.***

Portfolio: https://venkat-biyyapu-portfolio.netlify.app E EDUCATION

UNIVERSITY OF TEXAS AT DALLAS Dallas, TX

M.S in COMPUTER SCIENCE Aug 2018- May 2024

Cumulative GPA: 3.879/4.0;

Relevant Coursework: ML, DBMS, OS, DataStructures, Design Analysis Algorithms, NLP, Statistical Methods for Data Science Using R, Big Data Mgmt and Analytics, AI, WPL. REVA UNIVERSITY Bengaluru, India

B-Tech, COMPUTER SCIENCE AND ENGINEERING Aug 2018 - May 2022 Cumulative GPA: 3.87/4.0;

TECHNICAL SKILLS AND CERTIFICATIONS

Programming: C, C++, Python, R, Java, HTML, CSS, JavaScript, Test and UI Automation Tools and Libraries: PowerBI, Selenium, Pandas, Numpy, React, Node.js, Express.js, Rest and Soap API, Hadoop, Spark. Databases: MySQL, Mongo DB

Certifications: Microsoft Azure Fundamentals(AZ-900), C-Programming(Codetantra),Python Programming

(HackerRank), NPTEL- Python for Data Analytics.

WORK EXPERIENCE

INFORMATICA BUSINESS SOLUTIONS PRIVATE LIMITED Bengaluru, India Intern IT Applications Analyst Aug 2021 – Jul 2022

• I developed a Python-based Web UI Automation Framework using the BDD approach in 3 months that allows testers and business analysts to create simple test cases in English and automate the testing of web applications.

• I honed my skills in assessing web service functionality, including SOAP and REST APIs, and crafted a Python-based project named Oracle SOAP APQuick Close in 3 months.

• This tool efficiently submits processes in Oracle Cloud and retrieves their reports, delivering an impressive 80% reduction in execution time compared to alternative frameworks.

• Furthermore, I utilized various Python libraries such as Pandas and NumPy(3 weeks) to write automation testing scripts for web applications and worked with Jenkins and Bit Bucket to create automation processes.

• I had data analysis and cleansing work, in which I performed statistical analysis on data and produced numerous comprehensive reports, showcasing a strong ability to translate data into meaningful insights using Microsoft Excel and Python. Lastly, during the entire 1 year, I have gained experience in writing automation testing scripts using C# and Python. PROJECTS

Theme Box Store(React, Node, Express and MongoDB) Oct 2023 – Nov 2023

• A React.js frontend for user interaction, complemented by a backend stack powered by Node.js, Express.js, and MongoDB for efficient data handling.Implemented API calls to connect the front-end and back-end, enabling seamless product searches and curated theme exploration.

Big Data Mgmt and Analytics Research Project August 2023 – Oct 2023

• The project identifies loopholes in automated car legislation through bill identification and LLM training, annotating titles related to transportation, highways, data privacy, and cybersecurity.

• Despite testing pre-trained models like Facebook BART and MDBERTA-SQuAD, categorization challenges persist, revealing suboptimal results in accurately identifying legislative context. DataStructures and Algorithm Projects (Java) Jan 2023 – Apr 2023

• Implemented 3 RMQ algorithms: Sparse Table, Hybrid One, Fischer-Heun. Comparison between Hybrid One and Fischer-Heun using input arrays of different sizes(100M to 400M) for preprocessing and query processing efficiency analysis.

• Implemented Skip Lists, and conducted extensive performance analysis for millions of operations ranging from 10M to 100M (add, check, remove). Evaluated efficiency and effectiveness. Natural Language Programming Projects (Python) Oct 2022 – Dec 2022

• Utilized Bi-LSTM for SemEval. Prepared text with tokenization, and padding. Trained model on contextual data(10k sentences), and evaluated performance for semantic analysis.

• The project focused on POS tagging. Implemented HMM for probabilistic tagging and RNN (LSTM) for context analysis— evaluation of both models' performance( accuracy 97%) in assigning POS tags to words. Flight Delay Classification (ML and Python) Sep 2022

• The project aimed to predict flight delays. Conducted data cleansing, feature engineering, and EDA. Built and compared various ML models for accuracy and most of the models provided an accuracy of around 95-98%. Object Detection Using OpenCV(Python) Sep 2021 – Oct 2021

• This project involves the development of a real-time video object detection system that accurately identifies the objects around 95% and detects multiple objects by name. It is built using Python and its libraries, specifically OpenCV. RESEARCH PAPERS

• Authored a research paper titled "OCR And Text Recognition For Assisting Visually Impaired People Using Android Smartphone," presented at the Conference(IACIT-2022), focusing on aiding the visually impaired.

• Presented the research paper "Object Detection Using OpenCV" at the Conference(IACIT-2021), highlighting work on multiple object detection in a real-time video using OpenCV.

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