Hello! I'mRahul Purswani
Welcome to my corner of the internet! I'm a backend software engineer deeply passionate about machine learning. Currently seeking full-time opportunities starting January 2025, I'm eager to collaborate and drive success for your team. Let's connect and discuss how I can make a meaningful impact!
About me 🙋
My journey in computer science began with a Bachelor of Science degree, where I laid the foundation for my career. Now, as I pursue my Masters in Computer Science, I'm diving deeper into specialized areas like advanced algorithms, computer vision, data mining, deep learning, and natural language processing. Along the way, I've realized that the true mastery comes when I'm actively building projects aligned with the new skills I want to develop. My internship at ZeroEyes and my side projects have been invaluable in providing practical experience and shaping my skills across different areas, allowing me to apply theoretical knowledge in real-world scenarios and further honing my skills.
With a focus on backend engineering and a passion for machine learning, I'm eager to bridge these domains. Graduating in December 2024, I'm actively seeking full-time roles in backend software engineering, machine learning, and data-related positions. Let's connect and explore how we can achieve our goals together.
Software Engineering Intern
ZeroEyes Inc.
• Built a comprehensive dataset of over 1 million datapoints using Python to support client’s ML pipeline. Streamlined the data annotation process by developing a Python script with OpenCV, reducing annotation time by 30%.
• Utilized APIs to upload and manage datasets on GCP and internal tools, optimizing data handling. Researched diverse data augmentation techniques, improving model performance & balancing datasets within the pipeline.
Febuary 2024 - May 2024Research and Development Intern
ZeroEyes Inc.
• Implemented and fine-tuned ML models using TensorFlow to automate tasks in data annotation process, cutting annotation time by 15% and significantly reducing manual efforts by annotators.
• Engineered an image-to-text algorithm using PyTorch, enabling text-based image searches. Improved search speed for context specific image by 60% and improved overall user experience in retrieving relevant images. Processed over 100,000 images and analyzed embeddings to derive valuable insights for the data corpus.
May 2023 - December 2023Graduate Teaching Assistant
University of Kansas School of Engineering
• Senior Capstone: Organized and led weekly agile sprint meetings for 9 teams to discuss progress, address obstacles, and set achievable sprint goals. Assisted students with technical challenges and overall boosting team productivity.
• Compilers Construction: Facilitated interactive lab sessions for over 40 students. Explained topics from lexical analysis and parsing to code generation with hands-on examples. Evaluated and provided feedback on students’ lab work.
August 2022 - December 2024Projects 👨💻
Car Damage Detection
In this project, I developed a model to automatically detect and classify car damages. The model was deployed on an ESP32S board, enabling real-time car damage detection. Utilizing the CarDD dataset, I initially created a Convolutional Neural Network (CNN) model to perform detection and classification tasks. I then used the TensorFlow Object Detection API to train a MobileNetV2-SSD model for enhanced accuracy in identifying car damages.
This project enhanced my skills in model development, TensorFlow API, model optimization, embedded systems deployment, and managing end-to-end machine learning workflows.
Image Processing · TF Object Detection API · Quantization · Embedded Device · Tensorflow · Python · PlatformIO
IMDb Reviews Analysis
The IMDb Reviews Analysis project uncovers patterns and trends in movie reviews, providing insights into how sentiments and ratings change over time. Through Sentiment Analysis, Temporal Analysis, and Correlational Analysis, we explore the dynamics of audience opinions and their evolution. Additionally, we developed a model to accurately predict the sentiment of a review.
I learned a lot about web scraping, text processing, and tokenization. I also gained experience with vectorization techniques and data visualization. Additionally, I developed skills in analyzing large datasets to uncover meaningful insights.
Web Scraping · Natural Language Processing · Text Classification · Data Analysis · BeautifulSoup · Selenium · NLTK · Python
Skin Disease Detection
In this project, I developed an automated system using deep learning models to accurately detect and classify skin lesions. I trained custom CNN models and fine-tuned state-of-the-art models like ResNet & MobileNet to assist in early diagnosis and improve patient outcomes.
Through this project, I learned to implement custom datasets and dataloaders, build and train deep learning models, handle class imbalances, and apply data augmentation techniques, significantly enhancing my understanding of deep learning frameworks.
Image Processing · CNN · Model Finetuning · PyTorch · Python
SoccerTact
SoccerTact is a web application that provides comprehensive soccer analysis, including match based, team based and player based analysis. The application utilizes event data from StatsBomb's open data repository. We built a robust data pipeline to automatically extract data from the StatsBomb GitHub repository and store it in an SQL database.
I gained full-stack development experience, built a robust ETL pipeline, enhanced data analysis and visualization skills.
WebApp · Data Pipeline · Soccer Analytics · Data Visualization · MPLSoccer · NodeJS · JavaScript · Python · MySQL
MAPKU
MAPKU is a web application developed to assist first-year students and staff in navigating the campus. Users can search for buildings by class number, mark multiple destinations for the fastest route, and view route details (estimated time, distance). The app also provides information about campus buildings.
This project enhanced my skills in web development, user experience design, and geolocation services integration. I also gained experience in optimizing algorithms for route calculation.
WebApp · Web Scraping · GoogleMaps API · JavaScript · HTML · CSS · BeautifulSoup · Python
SMS Filtering
Developed a spam detection system using Bernoulli Naive Bayes from scratch in Python. The project involved data cleaning, feature extraction, and probabilistic modeling to classify SMS messages as spam or ham.
Gained skills in data preprocessing, binary feature matrix creation, and model implementation. Learned to calculate prior and likelihood probabilities, evaluate model performance using metrics like accuracy.
Text Processing · Model Implementation · Natural Language Processing · Python
Let's Connect!
Whether you have an exciting project in mind, want to discuss a potential collaboration, or simply wish to say hello, I'd love to hear from you! Drop me a message using the form below, shoot me an email, or connect through social media.
contactme@rahulp.dev
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