Recognizing the achievements of its members is an important part of the mission of the IEEE. Each year, following a rigorous evaluation procedure, the IEEE Fellow Committee recommends a select group of recipients for elevation to IEEE Fellow. Less than 0.1% of voting members are selected annually for this member grade elevation.
It is my great pleasure to inform you that the IEEE Board of Directors, at its November 2014 meeting, elevated you to IEEE Fellow, effective 1 January 2015, with the following citation:
(for contributions to blind source separation for biomedical applications)
J. Roberto B. de Marca, FIEEE
By U-T San Diego Jan. 27, 2014
TTO: Those letters often strike fear into the hearts of scientists and venture capitalists. They stand for Tech Transfer Office, the place you have to negotiate if you want to commercialize technology developed at a university or research institute.
San Diego's future success in the innovation economy depends in part on mining these new technologies. So let's meet Marian Bartlett, co-founder and lead researcher for Emotient, winner of Connect's 2013 Most Innovative New Products Award in the software category for FACET, which translates facial expressions into actionable information, enabling companies to create new levels of customer engagement.
Q: Did you start out to be a scientist?
A: I had some preconceived notions that women and girls didn't like math. Then in college I realized that I was good at it and became a math major. After college, I wanted to use my math skills with something human oriented so I contacted everyone in Boston in the visual perception field, and I was hired as a research assistant at MIT. Then I came to UCSD, where I earned a Ph.D. in cognitive science and psychology in 1998. (Her thesis became the basis of Emotient.)
Q: When did you first learn about business?
A: At UCSD, I was fortunate that one of my professors was Robert Hecht-Nielsen, the co-founder of HNC Software (HNC developed software used by the credit card and insurance industries to detect fraud and was purchased by Fair, Isaac and Co. in 2002.). Robert bridged academia and the business world, and he taught that in his classes. He had us write SBIR (Small Business Innovation Research) proposals as part of our class on neural networks. Also, my graduate adviser, Terry Sejnowksi, had previously started a business, Softmax, with some of his former postdocs that was later purchased by Qualcomm. So I was able to see firsthand how novel research can transform into a successful business.
Q: Were other women in the program?
A: In experimental psychology just under half (of the) students were women. When I moved over to the neural network machine-learning lab at Salk, I was the only one. It was aggressive, exciting and motivating.
Q: What was it like being one of a few women?
A: On rare occasions I thought that some people perceived my male graduate peers as being smarter or more capable, but I also benefited from being one of the few women in machine learning, so people remembered me.
Q: When did you start a company?
A: In 2008 with four colleagues, we started Machine Perception Technologies, which released a toolbox for the academic community called CERT — computer expression recognition toolbox. Silicon Valley venture capitalist Seth Neiman, a senior partner at Crosspoint Venture Partners, tried the demo on the website. In 2012, he became our lead investor, and we changed the company name to Emotient.
Q: Did you leave your research professor position at UCSD?
A: I wanted to remain part time at UCSD because I enjoy research, and I had commitments to students, I was the principal investigator on $3 million to $4 million in grants at the time and had $10 million total since 2001. UCSD's policies regarding intellectual property are interpreted very broadly and contain language often called the umbilical clause. If you are a faculty member, even if you do research on your own time and in separate facilities, UCSD will claim ownership. The result is to force out people who develop ideas. I was required by the investors to take a full leave or there would have been no company.
(Neil's note: I think it is sad that Bartlett had to leave UCSD. The whole issue of how a university tries to monetize intellectual property will be a topic for another column.)
Q: What's different between an academic setting and a startup?
A: At UCSD, the primary objective was to generate research papers that had the highest impact on our field. A complex research paper doesn't generate revenue. Pitching to venture capitalists and actually selling software were new skills for our team. We needed to blend our science skills with the business skills of Seth Neiman and our CEO, Ken Denman.
Q: What advice would you give to other academics who want to commercialize their technology?
A: Team up with the right partners with deep experience in the business world unless you want to spend a lot of time writing SBIR proposals.
We love Bartlett's story. Clearly she is a determined individual passionate about her work, and she understands the importance of knowing what you don't know. We hope that universities and research institutes will revisit and revise their intellectual property policies so that inventive scientists like Bartlett can maintain a foothold in both academia and business.
Neil Senturia and Barbara Bry, serial entrepreneurs who invest in early-stage technology companies, take turns in writing this weekly column about entrepreneurship in San Diego. Please email ideas to Barbara at firstname.lastname@example.org
© Copyright 2014 The San Diego Union-Tribune, LLC. An MLIM LLC Company. All rights reserved.
University of California, San Diego bioengineering professor Gert Cauwenberghs has been selected by the National Science Foundation to take part in a five-year, multi-institutional, $10 million research project to develop a computer vision system that will approach or exceed the capabilities and efficiencies of human vision. The Visual Cortex on Silicon project, funded through NSF's Expeditions in Computing program, aims to create computers that not only record images but also understand visual content and situational context in the way humans do, at up to a thousand times the efficiency of current technologies, according to an NSF announcement.
Smart machine vision systems that understand and interact with their environments could have a profound impact on society, including aids for visually impaired persons, driver assistance capabilities for reducing automotive accidents, and augmented reality systems for enhanced shopping, travel, and safety.
For their part in the effort, Cauwenberghs, a professor in the Department of Bioengineering at the UC San Diego Jacobs School of Engineering, and his team are developing computer chips that emulate how the brain processes visual information. "The brain is the gold standard for computing," said Cauwenberghs, adding that computers work completely differently than the brain, acting as passive processors of information and problems using sequential logic. The human brain, by comparison, processes information by sorting through complex input from the world and extracting knowledge without direction.
While several computer vision systems today can each successfully perform one or a few human tasks-such as detecting human faces in point-and-shoot cameras-they are still limited in their ability to perform a wide range of visual tasks, to operate in complex, cluttered environments, and to provide reasoning for their decisions. In contrast, the visual cortex in mammals excels in a broad variety of goal-oriented cognitive tasks, and is at least three orders of magnitude more energy efficient than customized state-of-the-art machine vision systems.
Cauwenberghs said the Visual Cortex on Silicon project offers a unique collaborative opportunity with experts across the globe in neuroscience, computer science, nanoengineering and physics.
The project has other far-reaching implications for neuroscience research. By developing chips that can function more like the human brain, Cauwenberghs believes researchers can achieve a number of significant breakthroughs in our understanding of brain function from the work of single neurons all the way up to a more holistic view of the brain as a system. For example, building chips that model different aspects of brain function, such as how the brain processes visual information, gives researchers a more robust tool to understand where problems arise that contribute to disease or neurological disorders.
|The Expeditions in Computing program, which started in 2008, represents NSF's largest single investments in computer science research. As of today, 16 awards have been made through this program, addressing subjects ranging from foundational research in computing hardware, software and verification to research in sustainable energy, health information technology, robotics, mobile computing, and Big Data.
See original source here: http://www.salk.edu/news/pressrelease_details.php?press_id=611
LA JOLLA, CA—Salk researcher Terrence J. Sejnowski, professor and head of the Computational Neurobiology Laboratory, has been elected a Fellow of the American Academy of Arts and Sciences, a distinction awarded annually to global leaders in business, government, public affairs, the arts and popular culture as well as biomedical research.
Sejnowski is world renowned as a pioneer in the field of computational neuroscience and his work on neural networks helped spark the neural networks revolution in computing in the 1980s. His research has made important contributions to artificial and real neural network algorithms and applying signal processing models to neuroscience.
About the Salk Institute for Biological Studies:
Faculty achievements have been recognized with numerous honors, including Nobel Prizes and memberships in the National Academy of Sciences. Founded in 1960 by polio vaccine pioneer Jonas Salk, M.D., the Institute is an independent nonprofit organization and architectural landmark.
Newsletter editor Tomoki Tsuchida sat down with Dr. Howard Poizner, Professor Emeritus of Rutgers University and director of the Poizner laboratory at UCSD. We had a chance to talk about his virtual reality laboratory and his diverse research interests across many disciplines.
Can you tell us a bit about the path that brought you here to UCSD?
You direct a laboratory with one of the most sophisticated virtual reality environments in the world. Can you describe the facility and how that relates to your main research goals?
The role of that facility is two-fold: it's both my lab and serves as a core facility that I direct for TDLC (NSF Temporal Dynamics of Learning Center, Gary Cottrell, PI). We have what as far as I know is a unique facility in the world capable of simultaneous recording of full-body motion and EEG while subjects freely move about in large-scale immersive virtual environments. The environments are highly immersive, and allow us to address questions of how the brain acts when people actually move, as opposed to when someone is stationary with their head fixed in place as is typically done.
Creation of virtual environments is crucial for experimental control since they provide powerful experimental control. The timing of events and the feedback given to the subject is completely controlled; the repeatability is exact, the measurements are very precise; and all of the data streams are synchronized through custom scripts that we've written. So we can record people's brain activity concurrently with their head, body, and limb motions as they move through locations, grasp virtual objects that have different weights and textures, learn to adapt to perturbations in the environment, make decisions and so forth. Thus, we can simultaneously study such things as the neural mapping of space in humans, learning and memory, and the cortical dynamics underlying motor control. I feel that these technological developments open up entirely new possibilities for investigating the cortical substrates of cognition and of motor control. We've recently published a detailed description of our system that goes through the various system components, their spatial and temporal precisions, how all of the devices are integrated, and give some sample applications (Snider, J. et al., in press).
What are some of the projects you're working on currently?
At another level in the platform of studies of the MURI is a project directed by Tom Liu, the director of UCSD's fMRI center. Among other things, Tom's group has been working on understanding resting brain state activity. When you're at rest, your brain is not silent, but there are lots of brain networks that are active.
Terry Sejnowski, named recipient of the 2013 IEEE Frank Rosenblatt Award.
"Todd P. Coleman is an Associate Professor in the Department of Bioengineering with affiliations in the Information Theory & Applications Center, the Institute of Engineering in Medicine, and the Institute for Neural Computation at UCSD. He directs the Neural Interaction Laboratory at UCSD where his group conducts research on flexible "tattoo electronics" for neurological monitoring, quantitative approaches to understand interacting neural signals within brains, and team decision theory approaches to design brain-computer interfaces. His research is highly interdisciplinary, at the intersection of neurophysiology, bio-electronics, and applied probability."
La Jolla, CA - INC Co-Director and Salk Institute professor Terrence J. Sejnowski, Ph.D., has been elected to the National Academy of Engineering. This places him in a remarkably elite group of only ten living scientists to have been elected to the National Academy of Sciences, Institute of Medicine as well as the National Academy of Engineering. UCSD and INC congratulate Dr. Sejnowski on this prestigious appontment and exceptional achievement.
La Jolla, CA - Salk Institute professor Terrence J. Sejnowski, Ph.D., whose work on neural networks helped spark the neural networks revolution in computing in the 1980s, has been elected a member of the National Academy of Sciences. The Academy made the announcement today during its 147th annual meeting in Washington, DC. Election to the Academy recognizes distinguished and continuing achievements in original research, and is considered one of the highest honors accorded a U.S. scientist.