I'm a software developer and open-source enthusiast currently building powerful wealth-tech software at valuefy. In my spare time, I enjoy creating applications to address various challenges (sometimes even imaginary ones) with the potential to help others. Despite my enthusiasm, my projects often end up in a cold GitHub repository and eventually in the Arctic Code Vault, due to my lack of motivation to promote them. During my college days, my team and I won the Smart India Hackathon 2019 by solving the issue of inconsistent data annotations in medical research. Later, during an internship, I collaborated with Prof. Dr. K. Chandrasekaran at NIT Surathkal, leading to the publication of a research paper on utilizing machine learning models to analyze risk factors in pregnancy that can lead to stillbirths, ultimately aiming to prevent them. I've experimented with various tech stacks, ranging from Web 2.0 (my professional forte) to Web 3.0 (AR/VR, blockchain), creative coding, and machine learning. My diverse experience has honed my ability to quickly learn and adapt, a valuable asset in the ever-evolving tech industry.
A cross-platform watch-party desktop video player for synchronized and seamless binging.
Download for desktop• Gesture Games | Gesture Games An in-browser gaming arena for gesture and voice controlled games. [Webapp] [Github] |
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• Gesture based Browser Control | Gesture based Browser Control A Chrome extension to enable scrolling webpages and taking screenshots with simple hand gestures. [Github] |
• Inconsistency detection in medical Annotations | Inconsistency detection in medical Annotations An end-to-end Django based web-app with UMLS parsing in back-end to detect inconsistent annotations in medical corpus, for medical data science research. [Github] |
• Malicious URL detection | Malicious URL detection A machine learning model to detect malicious phishing URLs with an accuracy of 97.7%. |
• Movie Recommendation Engine | Movie Recommendation Engine Movie Recommendation system based on Collaborative Filtering using MovieLens Data set. |