All Videos Tagged engedu (MedTech I.Q.) - MedTech I.Q.

Strategy: The Secret History of Silicon Valley

2009-03-31T21:40:03.663Z

How Stanford the CIA/NSA Built the Valley We Know Today

How much does an average Googler know about the history of the place
he works in? Silicon Valley.
Come and test your knowledge. I have seen this talk and I assure you -
even seasoned Silicon Valley veterans will find this story interesting. Silicon Valley entrepreneur Steve Blank will talk about how World War II set the stage for the creation and explosive growth of Silicon Valley, and the role of Frederick Terman and Stanford in working with government agencies
(including the CIA and the
National Security Agency) to set up companies in this area that sparked the creation of hundreds of other enterprises.

Speaker: Steve Blank
Steve Blank spent nearly 30 years as founder and executive of high
tech companies in Silicon Valley,
most recently the enterprise software firm E.piphany. He has been
involved in or co-founded eight
Silicon Valley startups, ranging from semiconductors to video games,
and personal computers to
supercomputers. He teaches entrepreneurship at U.C. Berkeley's Haas
School of Business,
Columbia University and Stanford's Graduate School of Engineering.

Imaging: Some Statistical Problems in Spectroscopy and Hyperspectral Imaging

2008-11-17T15:08:30.737Z

Every material has a distinctive spectrum. The spectrum of a material tells us about its chemistry. Hyperspectral images produce a spectrum (represented as several hundred numbers) at each pixel in an image. So hyperspectral images enable us to map variations in chemistry.

The first hyperspectral scanners, built in the 1980's and 1990's, were designed for airborne applications, primarily for mineral, environmental and military applications. However, in recent years, hyperspectral microscopes and cameras have been developed and are being used for terrestrial applications in areas such as medical diagnosis, burns analysis and skin cancer, biosecurity, pharmaceuticals, forensics and in agribusiness.

A significant focus over a number of years has been on developing fast and sophisticated algorithms and software for "unmixing" spectra into their pure ingredients, both when the pure ingredients are known and when they are unknown. This talk provides an overview of various algorithms, and demonstrates their application to some mineral, remotely sensing and biological data sets. Finally, it discusses some unsolved statistical and computational problems associated with these packages.

Speaker: Mark Berman
Mark Berman received the B.Sc.(Hons.) degree and University Medal in mathematical statistics from the University of New South Wales in 1974, and the Master of Statistics degree from the same institution in 1976. In 1978, he was awarded the Ph.D. and D.I.C. degrees in mathematical statistics by the Imperial College of Science and Technology, London.

He was a visiting lecturer in the Department of Statistics at the University of California, Berkeley during 1978-1979. Most of his time since then has been with the CSIRO Division of Mathematical and Information Sciences (CMIS), Sydney, where he is now a Chief Research Scientist. He led CMIS' Image Analysis Group from 1989 to 2000. He spent 1988 at the Melbourne Research Laboratories of Broken Hill Proprietary Ltd. where he established the Image Processing and Data Analysis Group. His research interests are in image analysis (especially hyperspectral), spectroscopy and spatial data analysis.

Since 2007, Dr. Berman has been working part time at CMIS. During this period, he has also given Ph.D courses in spectroscopy and hyperspectral image analysis at the Technical University of Denmark and Stanford University.

Robotics: 5 Years of Exploring Robotic Telepresence

2008-10-24T23:41:11.524Z

Google Tech Talks, October 16, 2008

A technical look at designing robots for the enterprise, how they can free us from time and space, and how they will spawn a new generation of collaboration, remote labor forces, and remote service industries.

Santa Monica based RoboDynamics now entering its fifth year is sending TiLR, its four foot tall robot into the real world and getting some real world feedback. The first TiLR was installed at the X PRIZE Foundation, assisting the Google Lunar X Prize team to communicate more effectively with various stakeholders around the world. Founder and CEO Fred Nikgohar discuss the challenges of designing a Robotic Telepresence platform with an emphasis on an open discussion about how this technology can transform the ways we live and work.

Speaker: Fred Nikgohar

Informatics:Current Issues in Computational Biology and Bioinformatics

2008-10-24T23:33:41.301Z

Google Tech Talks, August 26, 2008

A brief overview of bioinformatics computational problem landscape followed by a detailed look at one of
the areas: multiple perturbation analysis of cells using reverse engineering principles.

Speaker: Gary Bader
Gary is Assistant Professor at the Terrence Donnelly Centre for Cellular and Biomolecular Research (CCBR) at the University of Toronto. http://baderlab.org/

Imaging: Large image databases and small codes for object recognition

2008-10-11T19:29:48.331Z

In this Google Tech Talk, Speaker Dr Rob Fergus, Assistant Professor of Computer Science at the Courant Institute of Mathematical Sciences, New York University describes how with the advent of the Internet, billions of images are now freely available online and constitute a dense sampling of the visual world. Using a variety of non-parametric methods, he explores this world with the aid of a large dataset of 79,302,017 images collected from the Web. Motivated by psychophysical results showing the remarkable tolerance of the human visual system to degradations in image resolution, the images in the dataset are stored as 32x32 color images. Each image is loosely labeled with one of the 75,062 non-abstract nouns in English, as listed in the Wordnet lexical database. Hence the image database gives a comprehensive coverage of all object categories and scenes. The semantic information from Wordnet can be used in conjunction with nearest?neighbor methods to perform object classification over a range of semantic levels minimizing the effects of labeling noise. For certain classes that are particularly prevalent in the dataset, such as people, we are able to demonstrate a recognition performance comparable to class?specific Viola?Jones style detectors.

In the second part of the talk, he presents efficient image search and scene matching techniques that are not only fast, but also require very little memory, enabling their use on standard hardware or even on handheld devices. His approach uses the Semantic Hashing idea of Salakhutdinov and Hinton, based on Restricted Boltzmann Machines to convert the Gist descriptor (a real valued vector that describes orientation energies at different scales and orientations within an image) to a compact binary code, with a few hundred bits per image. Using this scheme, it is possible to perform real-time searches on the Internet image database using a single large PC and obtain recognition results comparable to the full descriptor. Using the codes on high quality labeled images from the LabelMe database gives surprisingly powerful recognition results using simple nearest neighbor techniques.