Gareth McKinley Professor of Teaching Innovation in Mechanical Engineering
The digital future is here, and the threat of disruption looms large. In a rapidly expanding digital marketplace, legacy companies without a clear digital transformation strategy are being left behind. COVID-19 crisis has accelerated the transition to a digital future. To succeed companies must embark on the difficult path of digital transformation…and that doesn’t mean creating another app. But what does digital transformation mean for your company and your business? How can we stay on the top of these rapid changes? What challenges have many high-profile companies faced? How can you prepare to succeed in a changing digital climate?
Join the MIT Industrial Liaison Program for a webinar: Rapid Prototyping with MIT Professor Neil Gershenfeld, the director of MIT's Center for Bits and Atoms and Associate Professor Skylar Tibbits, the founder of the Self-Assembly Lab at MIT. This two-hour rapid prototyping online seminar will provide an update on how to make (almost) anything, breaking down boundaries between the digital and physical worlds to Self-Assembly a process by which disordered parts build an ordered structure through only local interaction.
Alan Jasanoff Professor of Biological Engineering, Brain & Cognitive Sciences, Nuclear Science & Engineering
Polina Anikeeva Associate Professor, Materials Science & Engineering, Brain & Cognitive Sciences
John Fernandez Director, Environmental Solutions Initiative Principal Investigator, Urban Metabolism Group
Computing near the sensor is preferred over the cloud due to privacy and/or latency concerns for a wide range of applications including robotics/drones, self-driving cars, smart Internet of Things, and portable/wearable electronics. However, at the sensor there are often stringent constraints on energy consumption and cost in addition to the throughput and accuracy requirements of the application. In this talk, we will describe how joint algorithm and hardware design can be used to reduce energy consumption while delivering real-time and robust performance for applications including deep learning, computer vision, autonomous navigation/exploration and video/image processing. We will show how energy-efficient techniques that exploit correlation and sparsity to reduce compute, data movement and storage costs can be applied to various tasks including image classification, depth estimation, super-resolution, localization and mapping.
Will Tashman Founder Uncountable