Computer Science Engineering graduate passionate about tech and building impactful solutions
I'm a Computer Science and Engineering graduate with a passion for technology and innovation. I love exploring new domains, solving complex problems, and building efficient solutions.
My interests span across software development, artificial intelligence and machine learning and cybersecurity. Seeking opportunities to work with emerging technologies and contribute to projects that drive meaningful impact.
A data-driven Streamlit web application that analyzes Formula 1 drivers' distinctive driving styles using official telemetry data. Compare any two F1 drivers across key performance metrics including braking aggressiveness, throttle control, cornering consistency, and gear shift patterns. The app visualizes these comparisons through charts.
A machine learning-based web application that predicts whether a microbe is resistant or susceptible to a selected antibiotic using XGBoost classifiers. Users can select a microbe and antibiotic through a user-friendly interface and receive predictions along with possible alternative treatments if resistance is detected.
A machine learning application that detects phishing emails using Natural Language Processing. Built with Python, scikit-learn, and Streamlit, featuring TF-IDF vectorization and Logistic Regression classifier trained on 175K+ email samples. Includes web interface for real-time email analysis with confidence scoring.
Feel free to connect with me on LinkedIn or send me a mail! Open to discussing new opportunities and collaborations.