•Collaborated with an interdisciplinary team of medical professionals and Machine Learning developers to research and analyze medicalimaging data.•Leveraged expertise in image analysis to evaluate AP and Lateral X-Ray images of wrist and knee implants, resulting in the identification of implant manufacturers.•Achieved an F1 score of 98% in the classification of AP X-Ray images for knee implant identification.

•Developed and implemented an Object Detection solution using YOLO, creating a robust Computer Vision pipeline for real-time image analysis.•Improved the model performance to make more accurate predictions; deployed on AWS.•Performed Image Segmentation to segregate different types of waste.•Analyzed the various segments of the images to perform Image Classification for the variety of waste items.

Directed a team of 100+ students in executing projects and research papers, and in organizing technical events such as Hackathons and Machine Learning workshops, fostering professional collaborations.•Mentored the students to help them in the undergraduate program.

Designed and deployed an advanced NLP-based Fake News Detection model for Cryptocurrencies, significantly improving accuracy and reducing false positives.•Hosted the application as a Web App using the Dash library in Python.