Name: Manavi Uttam Ghorpade
Profile: Software Developer
Email: manavighorpade@gmail.com
Phone: 530-591-5243
Degree: M.S. in Computer Science
Skills
C++About me
Hey there! Welcome to my little corner of the internet. I'm a proud Computer Science graduate from California State University, Chico. I’ve got a solid grip on Data Structures and Algorithms, and I love tackling problems with a creative twist. Whether it's cracking a complex algorithm or solving a brain-busting puzzle, I live for that "Eureka!" moment.
I’m fluent in C++, Java & Python.
When I’m not lost in code:
Mountains are my playground: I love hiking and finding new trails.
Dance like nobody's watching: Seriously, I’ve got moves.
Furry friends: Volunteering at the local animal shelter is my happy place.
Publications
1. Diabetes Detection System (Click here)
- ⭐ Impact Factor: 3.3
- 📚 Citations: 120
- 👁️ Views: 4500
- 📥 Downloads: 1300
2. A Doctor's Appointment Booking System using Recommendation Model (Click here)
- ⭐ Impact Factor: 3.8
- 📚 Citations: 200
- 👁️ Views: 6000
- 📥 Downloads: 1500
Projects
Advanced driver assistance system (ADAS)
Technologies used: C++, Python, OpenCV, Nvidia jetson Nano
- Generated multicore embedded system using Nvidia jetson Nano 2g developer kit
- System assists drivers in the lane, traffic light, stop-sign, and pedestrian detection
- Successfully implemented AMP (Asymmetric multiprocessing) and SMP (Symmetric multiprocessing) using C++ and OpenCV which improved performance by 100% and obtained an average of 40 FPS
- Used HOG Descriptor, SVM model, ROI, Masking, Regression, Edge detection, Slope calculations, and Image preprocessing to improve driver safety and obtained an F-measure of 0.96
Food pantry management application
Technologies used: Automated testing, Jest, PostgreSQL, React, Docker, Agile methodologies, Git, CI/CD, TypeScript
- Updated food pantry management project (NodeJS to React and MongoDB to PostgreSQL) with Docker and automated testing
- Implemented a process to approve each backlogged Dependabot PR independently to ensure updates don't cause regression or other issues
- Added CI workflow for testing all pull requests and main branch with coverage reports and status badges to ensure continuous integration and delivery
- Led the creation and execution of comprehensive test plans, resulting in a reduction in bugs by 40% and an overall improvement in product quality
Inventory Management System for Home
Technologies used: MongoDB, React, NodeJS, Express, Django, Python, GCS, AWS
- Full-stack web development using two stacks: MongoDB/React/NodeJS/Express, Django/Python
- Cloud providers used: GCS and AWS
- Deployed each stack within Docker images and provided a load balancer on the back-end
- Differentiated performance and accessibility by working on both stacks individually
- Developed CI/CD pipelines to automate the software delivery process and ensure seamless integration of code changes
Gold Chase Game
Technologies used: C++, Python, OpenCV, Multithreading (Pthread), Makefile, Embedded Systems, Computer Vision
- Created multiplayer console game application- using C++, vagrant, distributed programming, signals, pipes
- Implemented semaphores for synchronization, shared memory to coordinate multiple processes, Signal handling, and message queues for automatic screen updates and chat functionality
- Aiming to complete the project within 4 weeks and reduced the deployment time by 50%
E-commerce Application for Online Shopping
Technologies used: HTML, CSS, JavaScript, Django, Python, AWS
- Designed and implemented a user-friendly e-commerce interface using HTML, CSS, and JavaScript
- Created back-end functionality for user authentication, product management, and order processing using Django and Python
- Integrated payment gateway APIs like Razorpay for secure online transactions
- Deployed the application on AWS, conducted testing and debugging, and collaborated with team members for project progress updates
Fake News Detection using NLP
Technologies used: Natural Language Processing (NLP), Scikit-learn, Python, NumPy, Pandas, Matplotlib, Scatterplots, Data Preprocessing
- Developed a set of prediction models with python using classification algorithms like passive aggressive, gradient boost, logistic regression, and support vector
- Utilized vectorization for textual data which increased the computational speed and achieved an accuracy of all models above 94%
- Performed data visualization using seaborn, matplotlib, scatterplots
Social Media website
Technologies used: MongoDB, React, NodeJS, Express, Bootstrap, Django/Python, AWS, GCP, SQL
- Constructed a social media web application using MongoDB, React, NodeJS, Express, Bootstrap, and Django/Python
- Hosted and deployed the application on cloud providers like GCS and AWS, ensuring high availability and scalability for worldwide users
- Built RESTful APIs to enable seamless communication and data management between the client-side and server-side components
- Migrated database from SQLite to SQL to enhance performance and scalability without impacting user experience
- Troubleshot end-user issues and led technology projects to enhance web application workflows and meet functional requirements and strategic goals
Chess Game
Technologies used: HTML, CSS, JavaScript, Django, Python
- Generated a Chess game web application using Python and Django framework
- Utilized HTML, CSS, and JavaScript to create an intuitive and visually appealing user interface
- Implemented Chess movement functionality using Django Forms and Models, with form validation that reports errors to the user
- Created a per-user board model, allowing each logged-in user to play a game independently, saving their progress in the database
- Conducted thorough research on user needs and preferences, resulting in a user-friendly interface and a 20% increase in user engagement
Organizer Website
Technologies used: HTML, CSS, JavaScript, Bootstrap, GCP, Django, Python
- Implemented a full-stack web service using HTML, CSS, JavaScript, Bootstrap, Django, and Python
- Formulated a personal to-do list feature (Tasks) and expense tracker feature (Budget) with add, edit, delete, and toggle completed state functionalities
- Utilized chartist.js library to create pie charts and bar charts to display summarized data
- Deployed Dockerized applications to Google Cloud Platform for remote accessibility
Custom kNN algorithm
Technologies used: Python, seaborn, matplotlib, scatterplots- Built custom kNN algorithm from scratch in Python without using any external ML libraries
- Tested kNN on classifier and regressor datasets (Sklearn) and acquired 95% accuracy
- Achieved 100% efficiency as that of Sklearn’s kNN and visualized the results with matplotlib, seaborn, and scatterplots
Maximum flow in the network
Technologies used: C++, Java, Python
- Analysed and implemented the Edmonds-Karp algorithm, Dinic's algorithm, and Push-relabel algorithm using highly optimized C++, Java and Python code
- Performed and compared asymptotic analysis of the algorithm's run time
- Generated test cases using real-world and synthetic data of different sizes and different complexity
Netflix Data Analysis Dashboard
Technologies used: BeautifulSoup, Python, Tableau
- visualized Netflix's content library, offering insights into movies and TV shows available on the platform
- Created an interactive Tableau dashboard for analysis of content distribution by country, ratings, genres, and more
Video Game Sales Analysis
Technologies used: BeautifulSoup, Python, Tableau, Scikit-learn, PyTorch, Keras, Pandas, NumPy
- Utilized BeautifulSoup for web scraping, compiling a high-quality dataset of over 100,000 data points with 99% data integrity
- Created an interactive Tableau dashboard for real-time sales trend exploration, boosting decision-making efficiency by 75%
- Developed machine learning models (RNN, Random Forest, LSTM) in Python, with LSTM achieving RMSE of 0.05 and R2 score of 0.98
Diabetes Detection System
Technologies used: Python, Swift, XCode- Worked in a team to develop Android and iOS applications for the detection of blood sugar levels (diabetes) by scanning the human retinal image
- Developed image recognition model using Python (Sklearn) for android application and Swift, XCode for iOS application
- Trained model by providing own dataset and improved accuracy to 99%