Siddarth Venkateswaran

As a Data Scientist, I've worked on developing full-stack AI applications for a large insure firm which involved multi-modalities (Image Classification, Object Detection, OCR, NLP). As a part of this project, apart from the AI components, I also worked on software development using Java Spring Boot as a backend and TypeScript as a front, and on containerization using Docker. Additionally, I have worked extensively on government funded research topics for AI in the field of Wines and Healthcare.

As a part of my thesis topic 'Anomaly Detection and Localization in Industrial Products', I implemented unsupervised and semi-supervised computer vision techniques for defect detection and localization on synthetic surfaces. As a result of my work, I was awarded the best Master's Thesis in my department.

As a working student in the field of Data Science, I worked on implementing recommendation systems for wines using the Autoencoders algorithm. Additionally, I lent a helping hand in the data preparation to enhance the OCR algorithm for Typeplate Readers.

As a part of my curriculum, I covered various aspects such as Statistics, Machine Learning, Deep Learning, Data Engineering and Data Visualization and Storytelling. My areas of specialization involved Computer Vision, Unsupervised Learning and Semi-Supervised Learning techniques. As a part of my work in my thesis topic 'Anomaly Detection and Localization in Industrial Products', I was awarded the best Master's Thesis in my department.