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    11.15.17
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    10.25.17
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    09.27.17
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    09.19.17
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RECENT VIDEOS

12 Results | Page 1 | Last | Next
 

09.20.2017
39 mins
ILP Video

From Person-and-Machine to Environment-and-Ecosystem

Brian Anthony
Principal Research Scientist
Director, Master of Engineering in Manufacturing Program
Co-Director, Medical Electronic Device Realization Center (MEDRC)
MIT Department of Mechanical Engineering
The impetus for the SENSE.nano is the recognition that novel sensors and sensing system are bound to provide previously unimaginable insight into the condition of individuals, as well as built and natural world, to positively impact people, machines, and environment. Advances in nano-sciences and nano-technologies, pursued by many at MIT, now offer unprecedented opportunities to realize designs for, and at-scale manufacturing of, unique sensors and sensing systems, while leveraging data-science and IoT infrastructure.
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09.20.2017
29 mins
ILP Video

New Tools for Understanding and Engineering the Brain

Edward Boyden
Associate Professor of Media Arts and Sciences
Associate Professor of Biological Engineering and Brain and Cognitive Sciences
Leader, Synthetic Neurobiology Group
MIT Media Lab
Understanding the brain could lead to new kinds of computational algorithms and artificial intelligences, as well as treatments for intractable disorders that affect over a billion people worldwide. However, the brain is a very complex, densely wired circuit, and understanding how it works has remained elusive. In order to map how these circuits are organized, and control their complex dynamics, we are building new tools, which include methods for physically expanding brain circuits so that we can see their building blocks, as well as molecules that make neural circuits controllable by light. Through these tools we aim to enable the systematic analysis and repair of the brain.
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09.20.2017
36 mins
ILP Video

Industry Keynote: Philips Medical Systems

Alberto Prado
VP and Head of Philips HealthWorks
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09.20.2017
34 mins
ILP Video

MIT Startup Exchange Introduction with Lightning Talks

Richie Bavasso, nQ Medical
Flanigon, Honeycomb Bio
Charles Barr, High Q Imaging
Xinjie (Jeff) Zhang, , Novarials
Andy Vidan, Composable Analytics
Andrew Warren,Glympse Bio 
Clifford Reid, Travera
Charles Fracchia, BioBright
MIT Startup Exchange actively promotes collaboration and partnerships between MIT-connected startups and industry. Qualified startups are those founded and/or led by MIT faculty, staff, or alumni, or are based on MIT-licensed technology. Industry participants are principally members of MIT’s Industrial Liaison Program (ILP).

MIT Startup Exchange maintains a propriety database of over 1,500 MIT-connected startups with roots across MIT departments, labs and centers; it hosts a robust schedule of startup workshops and showcases, and facilitates networking and introductions between startups and corporate executives.

STEX25 is a startup accelerator within MIT Startup Exchange, featuring 25 “industry ready” startups that have proven to be exceptional with early use cases, clients, demos, or partnerships, and are poised for significant growth. STEX25 startups receive promotion, travel, and advisory support, and are prioritized for meetings with ILP’s 230 member companies.

MIT Startup Exchange and ILP are integrated programs of MIT Corporate Relations.
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09.19.2017
38 mins
ILP Video

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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09.19.2017
36 mins
ILP Video

Molecular Electronics for Chemical Sensors

Timothy Swager
John D. MacArthur Professor of Chemistry
MIT Department of Chemistry
This lecture will detail the creation of ultrasensitive sensors based on electronically active conjugated polymers (CPs) and carbon nanotubes (CNTs). A central concept that a single nano- or molecular-wire spanning between two electrodes would create an exceptional sensor if binding of a molecule of interest to it would block all electronic transport. The use of molecular electronic circuits to give signal gain is not limited to electrical transport and CP-based fluorescent sensors can provide ultratrace detection of chemical vapors via amplification resulting from exciton migration. Nanowire networks of CNTs provide for a practical approximation to the single nanowire scheme. These methods include abrasion deposition and selectivity is generated by covalent and/or non-covalent binding selectors/receptors to the carbon nanotubes. Sensors for a variety of materials and cross-reactive sensor arrays will be described. The use of carbon nanotube based gas sensors for the detection of ethylene and other gases relevant to agricultural and food production/storage/transportation are being specifically targeted and can be used to create systems that increase production, manage inventories, and minimize losses.
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09.19.2017
36 mins
ILP Video

Engineering the Nanoparticle Corona for Sensors at New Biological Interfaces

Michael Strano
Professor of Chemical Engineering
MIT Department of Chemical Engineering
Our lab at MIT has been interested in how the nanoparticle corona – the region of adsorbed molecules surrounding the particle surface - can be engineered for molecular recognition. We have recently introduced a method we call CoPhMoRe or Corona Phase Molecular Recognition for discovering synthetic, heteropolymer corona phases that form molecular recognition sites at the nanoparticle interface, selected from a heteropolymer library. We show that certain synthetic heteropolymers , once constrained onto a single-walled carbon nanotube by chemical adsorption, also form a new corona phase that exhibits highly selective recognition for specific molecules. We have a growing list of biomolecules that we can detect using this approach including riboflavin, L-thyroxine, dopamine, nitric oxide, sugar alcohols, estradiol, as well as proteins such as fibrinogen. The results have significant potential in light of the fact that nanoparticles such as single walled carbon nanotubes can be interfaced to biological systems at the sub-cellular level, with unprecedented sensitivity. Several recent demonstrates indicate that spatial and temporal information on cellular chemical signaling can be obtained using arrays of such sensors. Other examples including sensor tattoos for mice, stable for more than 400 days in-vivo, will be shown. Lastly, I will highlight recent advances to control the trafficking and localization of nanoparticle systems in living plants using a mechanism that we call Lipid Exchange Envelope Penetration (LEEP). We demonstrate a living plant, interfaced with multiple nanoparticle types that can detect explosives, ATP and dopamine within or from outside the plant, and communicate this information to a user’s cell phone. Engineering the nanoparticle corona in this way offers significant potential to translate sensor technology to previously inaccessible environments.
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09.19.2017
38 mins
ILP Video

Toward nanocrystal sensors

Moungi Bawendi
Lester Wolfe Professor of Chemistry
MIT Department of Chemistry
Our laboratory focuses on the science and applications of nanocrystals, especially semiconductor nanocrystal (aka quantum dots). Our research ranges from the very fundamental to applications in electro-optics and biology. There is an ongoing effort to address the challenges of making new compositions and morphologies of nanocrystals and nanocrystal heterostructures, and new ligands so that the nanocrystals can be incorporated into hybrid organic/inorganic devices, or biological systems. We are collaborating with a number of biology and medical groups to design nanocrystal probes that meet specific challenges.
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09.19.2017
36 mins
ILP Video

Artificial Intelligence for Medical Images

Pratik Shah
Co Principal Investigator/Research Scientist, Camera Culture
MIT Media Lab
Advances in optics, biological sensing, medical imaging technologies, high throughput genetic sequencing is leading to massive datasets, which need to be analyzed. However, current Artificial Intelligence algorithms usually require 1000?s of examples of well-annotated datasets for high accuracy classification. Fluorescent biomarkers are important indicators of disease such as oral cancer, but imaging them can require specialized and often-expensive devices. Medical images, if diagnosed early with biomarker images and expert knowledge, can be valuable to prevent occurrences of serious systemic illnesses. In this lecture, we will discuss two convolutional neural network classifiers trained with disease signatures and fluorescent biomarker images to identify biomarkers in white light images as a per-pixel binary classification task. Once trained, the classifiers predict the location and intensity of fluorescent biomarkers in white light images without requiring specialized biomarker imaging devices or expert intervention. This generalized approach can be useful in other domains where diagnostic biomarker predicting can augment expert knowledge using standard white light images.
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09.19.2017
30 mins
ILP Video

It?s a Small World: The Power of Miniaturization in Cancer Diagnostics and Beyond

Tarek Fadel
Assistant Director, Marble Center for Cancer Nanomedicine
MIT Koch Institute for Integrative Cancer Research
Early and accurate detection of cancer represents an enormous opportunity for sensing technologies to impact patients' lives. I will discuss several examples of diagnostic technologies developed in the Bhatia lab that employ nanosensors to detect tumors using a simple urine test for readout. This platform technology uses nanosensors to detect enzyme activity associated with cancer invasion, and generate bar-coded reporters that can be detected by multiplexed mass spectrometry or antibody-based methods such as lateral flow assays. I will close the presentation with an introduction to the Marble Center for Cancer Nanomedicine, a new growing resource for the nanomedicine community.
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09.19.2017
27 mins
ILP Video

Making Invisible Obvious: Computational Analysis of Medical Images

Polina Golland
Professor of Electrical Engineering and Computer Science
MIT Department of Electrical Engineering and Computer Science
Polina Golland will discuss her group's research in computational analysis of MRI scans that aims to provide accurate measurements of healthy anatomy and physiology, and biomarkers of pathology. Applications range from fetal development to aging brain.
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09.19.2017
33 mins
ILP Video

Millimeter Wave Networks for Virtual Reality and other High Data Rate Applications

Dina Katabi
Andrew (1956) and Erna Viterbi Professor of Computer Science and Engineering
Director, Center for Wireless Networks and Mobile Computing (Wireless@MIT)
MIT Department of Electrical Engineering and Computer Science
The ever-increasing demand for mobile and wireless data has placed a huge strain on today?s WiFi and cellular networks. Millimeter wave frequency bands address this problem by offering multi-GHz of unlicensed bandwidth ? 200 times more than the bandwidth allocated to today?s WiFi and cellular networks. In this talk, I describe the opportunities and challenges brought in by this technology, and its applications in enabling untethered virtual reality headsets and high throughput multi-media applications.
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