CareConnectThis project was primarily designed to cater to healthcare facilities seeking to extend their services into the realm of homecare, facilitated by dedicated healthcare professionals. The application was developed utilizing React.js within the Android development framework, operating under a beta program. MongoDB was employed to construct the database infrastructure, while Express.js served as the framework for the API implementation.

I actively participated in a real-world project centered on a quadcopter equipped with an IP camera, tasked with obstacle detection. Employing two advanced algorithms coupled with computer vision techniques, we developed a robust system capable of accurately identifying obstacles in its flight path. This project not only showcased our proficiency in algorithmic design but also underscored our expertise in harnessing cutting-edge technologies for practical applications.

During this internship, I contributed to a web development project that entailed real-life applications, leveraging React.js for the frontend interface. In conjunction, we utilized Express.js to construct a robust API, while the backend database was meticulously crafted using MongoDB. This experience underscored the practical implementation of modern web technologies and reinforced my proficiency in full-stack development methodologies.

Experience with leveraging Vector Space Models, particularly in the context of document similarity detection using Term Frequency (TF) and Inverse Document Frequency (IDF). Proficient in Word Embedding techniques such as Word2Vec for capturing semantic and syntactic similarity within documents. Skilled in developing scoring mechanisms for free text queries to determine the relevance of documents. Objective-driven approach to addressing challenges in identifying semantic relatedness between texts, emphasizing the need for alternative similarity measures beyond direct word matching.