Teaching Assistant North Carolina

Meet Malde

+1-980-***-**** **********@*****.*** https://www.linkedin.com/in/meet-malde/ https://github.com/meetmalde8055 Experience

Teaching Assistant

University of North Carolina at Charlotte 08/2023 - 05/2024

• Assisted Professor as a Teaching Assistant for the Data Structures and Algorithms course, facilitating student learning through over 10 review sessions and addressing queries, resulting in a 95% satisfaction rate.

• Guided code reviews, troubleshooting methods to improve students’ problem-solving abilities, with a focus on optimizing efficiency and adhering to industry best practices.

• Managed interactive sessions on algorithm analysis and organized 5 workshops on algorithm design paradigms.

• Conducted research on advanced data structures, implementing and analyzing their suitability, performing empirical studies on performance metrics, and summarizing strengths, weaknesses, and optimization strategies in a detailed report. Software Developer Pune, India

Pimpri Chinchwad Police Commissionerate 03/2020 - 05/2022

• Spearheaded the development of a Complaint Registration and Management System, enhancing case resolution by 30% through improved data organization and leveraging WAMP architecture with Electron framework for cross-platform offline functionality.

• Implemented real-time validated complaint forms, advanced search and filter features, and dynamic status updates using jQuery, resulting in a 15% reduction in support ticket volumes and increased the user engagement by 10%.

• Developed server-side scripting, session management and user authentication using PHP and MYSQL that reduced the latency by 30% which increased the number of applications processed per hour by 25%.

• Designed and implemented AES encryption to safeguard sensitive information, creating secure login modules, encrypted complaint submission forms, and protected data storage solutions. Ensured that decrypted details were exclusively accessible to authorized personnel such as SHOs, Investigators, Supervisors, and Super Users, thereby enhancing data security.

• Collaborated closely with Cyber Security Officers and clients to gather detailed requirements and customize system functionality. Engaged in troubleshooting and debugging to ensure the system met stringent security standards and user needs. Technical Skills

Programming Languages: Java, Python, C/C++, HTML5, CSS, Javascript, PHP, Typescript, R Frameworks/Libraries: ReactJs, Angular 8, Bootstrap, Spring Boot, Style Components, NodeJs, Django Tools/Platforms: MySQL, SQLite, MongoDB, Tableau, Git, AWS, Azure, CI/CD and TDD, Microsoft Office Suite Programming Skills: Object Oriented Design, Data Structures and Algorithms, Architectural Design Patterns Education

University Of North Carolina at Charlotte Charlotte, USA Masters in Computer Science — GPA: 3.85/4 08/2022 - 05/2024 Relevant Courses: Data Structure and Algorithms, Machine Learning, Visual Analytics, Network Based Application Development, Software System Design Implementation, Big Data Analytics MIT World Peace University Pune, India

BTech in Computer Science — GPA: 8.8/10 08/2018 - 05/2022 Projects

IPL Dashboard [Spring Boot, Spring Batch, JPQL, React.js, REST API, AWS]

• Developed a Full Stack Web IPL Dashboard using Spring Boot for backend processing and REST API creation, enabling data ingestion and processing logic.

• Integrated React.js frontend, utilizing React Effects and State for UI interactivity, while adding match API functionalities and styling components for enhanced user experience.

• Designed and implemented UI pages for Team, Match Detail, and Home, culminating in the deployment of the application to AWS for accessibility and scalability.

Modern YouTube Clone Application [React JS, Material UI 5, RapidAPI]

• Developed a modern YouTube clone application using React JS and Material UI 5.

• Utilized RapidAPI for integrating essential functionalities such as video fetching, search, and user authentication.

• Successfully deployed the application, providing users with a seamless and intuitive video streaming experience. Stock Market Prediction and Forecasting [Python, ML algorithms, Matplotlib]

• Implemented a machine learning model for predicting stock market values using Long Short Term Memory (LSTM) and Linear Regression algorithm, achieving a prediction accuracy rate of 85%.

• Conducted research on 20 literature sources and applied Lasso Regression to 6 months of Apple stock prices data.

• Utilized graphical analysis to address the gradient issue, achieving a 5% MAPE in 30-day stock price predictions.

Contact this candidate