Deep learning is a class of machine learning algorithms that uses multiple layers to progressively extract higher-level features from the raw input. For example, in image processing, lower layers may identify edges, while higher layers may identify the concepts relevant to a human such as digits or letters, or faces.
Speakers
![]() |
Amar Gupta MIT Principal Investigator, AI and OCR-based Hybrid Approach to Reduce Human Involvement and Effort in Document Processing and Creation of Forecasting Models (sponsored by SiliconExpert); and Coordinator, Telemedicine/Telehealth and Geographically Distributed Teams of Professionals Amar has spent the bulk of his career at MIT in an array of technical and management positions that involved analysis and leveraging of opportunities at the intersection of technology and business to foster the deployment of Artificial Intelligence and allied approaches in organizations and countries around the world. He has analyzed evolving innovations in products and services from multiple perspectives –including strategic, business, technical, economic, legal, and public policy and served as an adviser to leading US organizations, international companies, and specialized agencies of the United Nations. |
![]() |
Vik Parth Director of Product and Innovation SiliconExpert Vik Parth is passionate about teams and technologies that shape how people interact with digital information and the physical world. He is the Director of Innovation and Product Strategy at Arrow Electronics | Digital SAAS and a Research Affiliate at MIT. His work has been featured at MIT, Wired Magazine, The University of Texas at Austin, TEDx and SXSW. While a graduate researcher at the MIT Media Lab, Vik developed multimodal XR interfaces and photonics for holographic displays. He also served as the team captain of the award-winning MIT Hyperloop II team, where he drove development of the world's first autonomous electric hovercraft for Elon Musk’s SpaceX and The Boring Company. |