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One of a Series: MIT Holidays

MIT Closed - Martin Luther King, Jr. Day

January 21, 2019

Mastering Innovation and Design-Thinking

January 28-30, 2019, 9 AM - 5 PM

Insanely successful companies, like Apple, Virgin, Toyota, and others, innovate continuously because of their culture of design-thinking. When done right, this thinking links inspiration and passion to execution and delivery—positively affecting every facet of the product and service.

For you to be successful at work, you need to know how to think like a designer when approaching an engineering task alone, but you especially need design-thinking skills when working within a team or leading a team. By applying a design-centered approach you’ll be able to conceive of radically innovative solutions, deeply understand who your real stakeholders are and what they care about, create vision that gets buy-in from senior management and colleagues, avoid hazards, and create solutions that people love both emotionally and intellectually.

Using a 10-step design process and a 3-step vision creation and communication process, you’ll experience the design process first hand in this interactive class that will expand your thinking and help you and your teams create more powerful solutions. You’ll learn how to create materials that align technical and non-technical audiences, understand the vital importance of the psychology behind how people interact with technology, how to manage creativity, and how to assess the effectiveness of your solutions.

WHO SHOULD ATTEND
This course is targeted for design engineers, research engineers, project engineers or managers, product engineers, members of the technical staff, applied scientists, and research scientists. The course would also be of interest to those who supervise early career professionals and those in academia (e.g. engineering and science graduate students, and post-docs).

Designing Efficient Deep Learning Systems - March session

March 27-28, 2019

Deep learning is widely used for many artificial intelligence (AI) applications including computer vision, speech recognition, robotics, etc. While deep learning delivers state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Accordingly, designing efficient hardware systems to support deep learning is an important step towards enabling its wide deployment, particularly for embedded applications such as mobile, Internet of Things (IOT), and drones.

Who Should Attend
This course is designed for research scientists, engineers, developers, project managers, startups and investors/venture capitalists who work with or develop artificial intelligence for hardware and systems, as well as mobile or embedded applications:

* For project managers and investors/venture capitalists whose work involves assessing the viability or potential impact of a deep learning system and selecting a research direction or acquisition, this course aims to provide an overview of the recent trends as well as methods to assess the technical benefits and drawbacks of each approach or solution based on a comprehensive set of metrics.
* For research scientists and engineers whose work involves designing and building deep learning systems, this course aims to provide an overview of the various state-of-the-art techniques that are being used to address the challenges of building efficient deep learning systems.
* For startups and developers whose work involves developing deep learning algorithms and solutions for embedded applications and systems, this course aims to provide the insights necessary to select the best platform for your goals and needs. It will also highlight techniques that can be applied at the algorithm level to improve the energy-efficiency and speed of your proposed solution.

One of a Series: MIT Holidays

MIT Closed - Patriots' Day

April 15, 2019

One of a Series: MIT Holidays

MIT Closed - Memorial Day

May 27, 2019

Tribology: Friction, Wear, and Lubrication

June 24-28, 2019

The study of friction, wear, and lubrication has long been of enormous practical importance, since the functioning of many mechanical, electromechanical and biological systems depends on the appropriate friction and wear values. In recent decades, this field, termed tribology, has received increasing attention as it has become evident that the wastage of resources resulting from high friction and wear is greater than 6% of the Gross National Product. The potential savings offered by improved tribological knowledge, too, are great.

The background of most engineers in this important technological area, however, is seriously deficient. For example, an undergraduate engineering student receives less than an hour of instruction in tribology. Moreover, most reference works of tribology provide little guidance to solving real-world problems.

Accordingly, this program presents current insights into tribology in a pedagogical form, focusing on such fundamental concepts as surface energy, elastic and elastoplastic deformation, microfracture, and surface interactions at the micro- and nano-scale. Additionally, special considerations are given to the application of fundamental knowledge to control friction and wear behavior through lubrication and the selection of materials and coatings in practical situations. Furthermore, modern experimental methods are discussed and several case studies are used to indicate how fundamental tribology knowledge can be applied in the design of tribological components and systems.

Who Should Attend
The program is intended for two kinds of participants: those who are active or intend to be active in research on some aspect of tribology, and those who have encountered practical friction and wear problems and wish to learn novel methods of solving them.

The course requires at least a first-year college course in mathematics, applied mechanics, and materials. Some lectures introduce more advanced concepts in these areas and in physical chemistry and thermodynamics. These will be reviewed where necessary to provide the required background.

One of a Series: MIT Holidays

MIT Closed - Independence Day

July 4, 2019

Downstream Processing

July 22-26, 2019

Continuing discoveries in molecular biology, genetics, and process science provide the foundation for new and improved processes and products in today's biochemical process industry. The production of therapeutic proteins, which is made possible by discoveries in biotechnology, will generate sales exceeding $100 billion in 2010. In addition, biotechnology has led to marked improvement and expansion in the traditional biochemical process industry for production of enzymes, diagnostics, chemicals, pharmaceuticals, and foods. Continued introduction of new technology necessitates innovation in process development scale-up and design. As a consequence, there is the need to design new, as well as to improve existing, processes. An integral and cost intensive part of these processes is associated with downstream processing for product isolation and purification.

WHO SHOULD ATTEND
The course covers fundamental principles of downstream processing with practical examples and case studies to illustrate the problems and solutions faced by the practitioner. It is intended to provide both insight into and an overview of downstream processing for individuals actively engaged in process research and development, as well as those who manage and innovate in the biochemical process industry. Increasingly, scientists and engineers engaged in fermentation and cell culture development attend the course to better understand the context of the whole process. Attendees include:

* Engineers and scientists interested in design, economics, validation optimization and scale-up of biochemical product recovery;
* Protein biochemists and chemists involved in design of recovery processes;
*Managers responsible for biochemical process development;
* Entrepreneurs, attorneys, and business leaders wanting an overview and insight into biochemical manufacturing.

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