My own portfolio website Preethi M preethim12202@gmail.com | +1 (443)-(851) -(9844) | Baltimore, MD
EDUCATION University of Maryland, Baltimore County, (USA) Baltimore, MD MS, Computer Science; GPA- 3.567 December 2023 Velagapudi Ramakrishna Siddhartha Engineering College, (India) Vijayawada, India BTech, Information Technology, GPA: 3.39/4 June 2021
TECHNICAL SKILLS • Programming Languages: • Python, Java, C, MATLAB, R. • Frameworks and Tools: Git-Scikit-learn, NLP, TensorFlow, Keras API, Django, Flask, MATLAB GUI, React, Angular, Node.js, Express.js, Web/Internal APIs, SpringBoot, Spring MVC. • • Cloud Technologies: AWS Resources: AWS Redshift, AWS Glue, S3, EC2, Azure.
• Web Development HTML5, CSS3, Bootstrap, JavaScript, PHP, XML, JQuery, AJAX, WordPress. • Database Systems: MySQL, SQL Server, SQLite3, MongoDB, Oracle, DynamoDB, Postgress SQL.
• Applications: Android Studio, Visual Studio, Udemy, .NET, Jupyter Notebook, Ubuntu (Linux), IntelliJ, Docker desktop, Adobe Photoshop.
CERTIFICATIONS: AWS Certified Cloud Practitioner
WORK EXPERIENCE
Data Engineer Feb 27,2024 – Present
Consultant, SasInfo Inc, USA
• Supported the setup and configuration of AWS Cloud services, including EC2 instances and S3 buckets, under the guidance of senior team members.
• Assisted in data migration tasks by transferring on-premises data to AWS S3 storage using AWS CLI and AWS Management Console.
• Participated in basic AWS Cloud Practitioner responsibilities, such as managing user access and permissions, and monitoring AWS resource usage and billing.
• Contributed to the development of basic Python scripts to automate routine tasks related to AWS resource management, enhancing operational efficiency.
Web Development, May 10,2020 - Nov 10,2020
Intern Exposys data labs, India.
• Developed a user-friendly Travel-website using Python/Flask, HTML, CSS, and JavaScript, catering to the needs of modern travelers, and enhancing their trip planning experience.
• Designed and implemented web APIs to facilitate seamless communication between clients and a travel chatbot, leveraging NLP (Natural Language Processing) techniques like NLTK, nltk.stem, pickle, and wordnetlemmatizer, ensuring intuitive interaction with users.
• Enhanced the chatbot’s capabilities by training it with a rule-based dataset in JSON format, enabling it to understand user queries and provide relevant responses, thereby improving user satisfaction and engagement.
• Created internal APIs for efficient database management, establishing connections to SQLite3 to securely store user authorizations, session data, and hotel information.
• Assisted in testing and debugging website functionalities, ensuring a seamless and error-free user experience, and providing support during the website’s launch and subsequent updates.
Web Development July 1,2021 - Dec 30,2021
Intern,QuestGlobal, India
• Spearheaded the development of RuralHub, a Node.js based ecommerce web application offering shared office spaces for employees of various companies. Designed and implemented the user interface using HTML, Bootstrap, CSS, and JavaScript to ensure enhanced usability and a seamless browsing experience.
• Played a key role in the UI/UX design process, approached the client to create visually appealing and user-friendly interfaces, incorporating best practices to enhance accessibility and engagement.
• Integrated Express.js into the backend architecture, facilitating rapid development and deployment of RESTful APIs, enabling seamless communication between client-side interface and server-side functionalities, enhancing scalability and performance. • Implemented OAuth 2.0 to enhance the authentication process, ensuring secure and efficient access to the user login page. • Used MongoDB database for efficient data storage and retrieval, facilitating smooth booking processes. • Demonstrated entrepreneurial spirit by identifying a market need and creating a platform that enables companies' employees to work peacefully closer to their hometowns, contributing to improved work-life balance and productivity. Graduate Assistantship (Grader) – Network Security August 27,2023 -Dec 27,2023 University of Maryland Baltimore, County, USA • Evaluated and assessed students’ homework, assignments, exams, and projects. • Provided guidance and assistance to students who had questions or concerns related to network security.
PROJECTS Recommending the best product based on user requirements using opinion mining. https://ieeexplore.ieee.org/document/9544690 Dec 2020 - July 2021 • Extracted different product’s reviews and ratings data from Amazon official website using Parsehub web scrapper. • Performed exploratory data analysis on diverse product review datasets, applying NLP techniques like Count Vectorizer and Vader for sentiment classification. • Visualized sentiment categories using WordClouds and developed a sentiment analysis model using logistic regression with a 75% accuracy rate. • Calculating the overall score out of 100 for each product and thus recommending the highest scored product to the customers. Implement Distributed File System with Docker Containers using Python Feb 2022-May 2022 • Developed a distributed file system using Python/Django, for efficient data management across multiple servers. • Used MongoDB for secure storage of authentication, authorization, and encrypted master keys. • Streamlined server deployment with Docker containers, ensuring seamless information synchronization, and implemented robust data encryption at rest using the Fernet cryptography library for enhanced security. System Upgrades Report as a Service Sept 2022 – Dec 2022 • Built a robust backend system utilizing text processing and web scraping techniques. • Used BeautifulSoup4 and Requests libraries to extract content from software versions release notes. • SQLite3 for efficiently storage and organization of scraped data, with unique identifiers assigned using the UUID library for accuracy and reliability. Image Morphing using Beier-Neely Algorithm Sept 2022 – Dec 2022 • Implemented the Beier-Neely algorithm for image morphing between two distinct human faces, achieving seamless blending and transformation effects. • Extracted facial landmarks using the DLIB package, enabling the creation of 16 frames through image wrapping and cross-dissolving techniques. • Designed the front-end user interface using Python/Flask, allowing users to upload source and destination images, resulting in a smooth animated sequence of 16 frames morphing the source image into the destination image.