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    11.30.17
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RECENT VIDEOS

28 Results | Page 1 | 2 | Last | Next
 

11.16.2017
38 mins
ILP Video

Track 6: Bio-inspired metal-coordination crosslinking: easy access to broad dynamics for new engineering of polymer mechanics

Niels Holten-Andersen
Henry L Doherty Assistant Professor in Ocean Utilization
MIT Department of Materials Science and Engineering
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11.16.2017
30 mins
ILP Video

Track 6: Structural biopolymers - using Nature's building blocks as an inspiration for advanced manufacturing

Benedetto Marelli
Paul M Cook Career Development Assistant Professor of Civil and Environmental Engineering
MIT Department of Civil and Environmental Engineering
Structural biopolymers are materials engineered by Nature as building blocks of living matter. These materials have unique and compelling properties that allow for their assembly and degradation with minimal energy requirements as well as their performance at the biotic/abiotic interface. By combining basic material principles with advanced fabrication techniques, it is possible to define new strategies to drive the assembly of structural biopolymers in advanced materials with unconventional forms and functions such as edible coating for perishable food, inkjet prints of silk fibroin that change in color in the presence of bacteria, three dimensional monoliths that can be heated by exposure to infrared light and flexible keratin-made photonic crystals.
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11.16.2017
32 mins
ILP Video

Track 6: Build AI products faster, cheaper

Kalyan Veeramachaneni
Principal Research Scientist
MIT Laboratory for Information and Decision Systems
Artificial intelligence is being embedded into products to save people time and money. Experts in many domains have already begun to see the results of this, from medicine to education to navigation. But these products are built using an army of data scientists and machine learning experts, and the rate at which these human experts can deliver results is far lower than the current demand. My lab at MIT, called Data to AI, wanted to change this. Recognizing the human bottleneck in creating these systems, a few years ago we launched an ambitious project: we decided ?to teach a computer how to be a data scientist." Our goal was to create automated systems that can ask questions of data, come up with analytic queries that could answer those questions, and use machine learning to solve them?in other words, all the things that human data scientists do. After much research and experimentation, the systems we have developed now allow us to build end-to-end AI products that can solve a new problem in one day. In this talk, I will cover what these new technologies are, how we are using them to accelerate the design and development of AI products, and how you can take advantage of them to actually build AI products faster and cheaper.
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11.16.2017
27 mins
ILP Video

Track 7: Harnessing high temperature materials for extraction and processing

Antoine Allanore
Thomas B King Assistant Professor of Metallurgy
MIT Department of Materials Science and Engineering
The demand for materials, particularly minerals and metals, has experienced an exceptional growth in the last decades. In parallel, the costs of the corresponding processing technologies have reached levels that are unsustainable for most countries. Increasing access to cost effective and clean electricity sets the stage for novel processes that can match new expectations from society. In this context, recent research and development results pertinent to materials processing are presented, in particular for oxides and sulfides. In parallel, novel experimental methods and predictive capacity for high temperature systems are shown, paving the way to transformative processes and materials.
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11.16.2017
30 mins
ILP Video

Track 7: Germanium: Low Cost, High Performance Solar Cells and Photonics Devices

Jurgen Michel
Senior Research Scientist, Materials Research Laboratory
Senior Lecturer, MIT Department of Materials Science and Engineering
Device performance is in most cases connected to the materials quality. In many cases, high quality materials are available, but at a cost that is commercially not viable. We have been working on improving the quality of germanium for use as a virtual substrate for III-V semiconductor materials and for active silicon-based photonic devices. Germanium as a virtual substrate would enable low cost, high efficiency solar cells as will be presented in one example. An example for advanced germanium based devices are single photon detectors, operating at room temperature in the near infrared.
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11.16.2017
34 mins
ILP Video

Track 5: Faster, Smarter, Greener: The Future of the Car and Urban Mobility

Charles Fine
Chrysler Leaders for Global Operations Professor of Management
Professor of Operations Management and Engineering Systems
MIT Sloan School of Management
To support societal demands for mobility fluidity, co-existing with a sustainable planet, mobility systems for a digitally powered society must be efficient and innovation friendly. Efficiency requires intelligent use of assets and aggressive use of best technology, while consumers expect freedom in personal choices as well as fairness. Future society will demand Connected, Heterogeneous, Intelligent, and Personalized (CHIP) mobility. We propose a framework where Heterogeneous transportation modes are Connected both digitally and physically, and Intelligent apps can access data on usage, congestion, prices, and weather, for example, and enable real time and Personalized travel planning throughout a city, whether a traveler wants to optimize time, cost, carbon footprint or touristic aesthetics. This framework proposes that urban planners create policies to support such a vision and that the traditional auto industry is likely to enjoy a less dominant role in architecting mobility frameworks. Governments and city administrations will be joined by traditional auto industry players as well as a range of new-generation entrepreneurs and investors, technology startups, and app developers, all of which have contributions to make in redefining future mobility.
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11.16.2017
33 mins
ILP Video

Track 6: Computational Manufacturing

Wojciech Matusik
Esther and Harold E Edgerton Career Development Associate Professor of Electrical Engineering and Computer Science
MIT Department of Electrical Engineering and Computer Science
Wojciech Matusik is an Associate Professor of Electrical Engineering and Computer Science at the Computer Science and Artificial Intelligence Laboratory at MIT, where he leads the Computational Fabrication Group. Before coming to MIT, he worked at Mitsubishi Electric Research Laboratories, Adobe Systems, and Disney Research Zurich. He studied computer graphics at MIT and received his PhD in 2003. He also received a BS in EECS from the University of California at Berkeley in 1997 and MS in EECS from MIT in 2001. His research interests are in direct digital manufacturing and computer graphics. In 2004, he was named one of the world's top 100 young innovators by MIT's Technology Review Magazine. In 2009, he received the Significant New Researcher Award from ACM Siggraph. In 2012, Matusik received the DARPA Young Faculty Award and he was named a Sloan Research Fellow.
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11.16.2017
44 mins
ILP Video

Track 5: Panel Discussion: Policies, economics, business models and technologies for mobility of the future

Venkat Sumantran
James Womack
Valerie Karplus
Carlos Lima Azevedo
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11.16.2017
37 mins
ILP Video

Track 5: City of the future: how changes to physical and digital infrastructure will effect and be effected by mobility

Kent Larson
Principal Research Scientist
Director, Changing Places
MIT Media Laboratory
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11.16.2017
27 mins
ILP Video

Industry Keynote: Accelerating Takeda's R&D Successes

Andrew Plump
Chief Medical and Scientific Officer, Takeda Pharmaceutical Company
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11.15.2017
35 mins
ILP Video

Track 1: Transforming Nanotechnologies into Applications

Max Shulaker
Emanuel E Landsman (1958) Career Development Assistant Professor of Electrical Engineering and Computer Science
MIT Department of Electrical Engineering and Computer Science
While trillions of sensors that will soon connected to the ?Internet of Everything? (IoE) promise to transform our lives, they simultaneously pose major obstacles, which we are already encountering today. The massive amount of generated raw data (i.e., the ?data deluge?) is quickly exceeding computing capabilities, and cannot be overcome by isolated improvements in sensors, transistors, memories, or architectures alone. Rather, an end-to-end approach is needed, whereby the unique benefits of new emerging nanotechnologies ? for sensors, memories, and transistors ? are exploited to realize new system architectures that are not possible with today?s technologies. However, emerging nanomaterials and nanodevices suffer from significant imperfections and variations. Thus, realizing working circuits, let alone transformative nanosystems, has been infeasible. In this talk, I present a path towards realizing these future systems in the near-term, and show how based on the progress of several emerging nanotechnologies (carbon nanotubes for logic, non-volatile memories for data storage, and new materials for sensing), we can begin realizing these systems today. As a case-study, I will discuss how by leveraging emerging nanotechnologies, we have realized the first monolithically-integrated three-dimensional (3D) nanosystem architectures with vertically-integrated layers of logic, memory, and sensing circuits. With dense and fine-grained connectivity between millions of on-chip sensors, data storage, and embedded computation, such nanosystems can capture terabytes of data from the outside world every second, and produce ?processed information? by performing in-situ classification of the sensor data using on-chip accelerators. As a demonstration, we tailor a demo system for gas classification, for real-time health monitoring from breath.
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11.15.2017
34 mins
ILP Video

Track 1: Chemistry of the Graphene Surface for the Creation of Functional Nanomaterials

Timothy Swager
John D. MacArthur Professor of Chemistry
MIT Department of Chemistry
The utility of carbon nanomaterials is highly dependent upon the precision upon which they can be assembled and functionalized. New methods enable high impact applications in sensing, mechanical, membrane, and energy storage/conversion. Approaches to the formation of functional assemblies of carbon nanotubes will be described that involved the non-covalent immobilization of the materials into functional assemblies. In a non-covalent method, no direct chemical bonds are made to the carbon nanotubes, thereby leaving their electronic properties intact. New covalent connections to the graphene surfaces (sidewalls) of the carbon nanotubes will also be discussed and how these materials can serve to modify their electronic properties for devices as well as hard wire functional assemblies to the carbon nanotubes to provide interactions with chemicals (sensors) or electrocatalysis (energy conversion). Many of these methods are also applicable to the functionalization of graphite to create new forms of graphene. We will also show how high purity graphene can be produced in using new scalable electrochemical methods.
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