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Vivienne Ming (DC’03, ’06)

April 2013

Inc. Magazine Names Alumna As One of 2013’s 10 Women to Watch in Tech

For some people, co-founding and running the educational technology company Socos would be more than enough to keep them busy.

But, not for Vivienne Ming (DC’03, ’06). Ming, who received her master’s degree and Ph.D. in psychology from Carnegie Mellon University, is also a theoretical neuroscientist at UC Berkley’s Redwood Center for Theoretical Neuroscience and chief scientist at the startup Gild.

Founded in 2011, Socos transforms students’ essays, emails and discussions into models of their conceptual knowledge in order to help their teachers adapt instruction in real time. They have consulted with the Gates Foundation, the Bertelsmann Foundation and the White House Office and Science and Technology on how to fundamentally change education and end standardized testing.

Ming has recently been recognized for her work. Inc. Magazine named her one of the year’s “10 Women to Watch in Tech,” and the San Francisco Business Times gave her a “Most Influential Women of the Bay Area” award.

Dietrich College News caught up with Ming to learn more.

What motivated you to start Socos?

One day my wife, Norma Ming (DC'03, '06), and I were talking about how we could maximize the individual potential of students using automated tutors (we're romantics that way). This theme, maximizing human potential, holds throughout all of my work and it was a question I had been pondering for many years. As an undergrad I researched automatic expression recognition and imagining how it might be used to monitor and adaptively maintain student engagement. My wife had been exploring these questions as a doctoral student of Ken Koedinger and Marsha Lovett in the Psychology Department, where we met.

The power of the cognitive tutors built by Carnegie Learning had amazed us. Inspired by them, we created a system capable of automatically learning a map of subject matter directly from the students themselves. It’s designed to construct models of the conceptual domain of a course, such as Intro to Biology, directly by reading student homework, emails, online discussions and more. As it refines its model, our system begins providing predictive feedback to instructors and students.

In our vision, teachers follow their own teaching plans while Socos provides feedback on student progress and individualized recommendations. Some day, such a system should even be able to replace traditional testing, relieving students of the anxiety and bias of high stakes exams.

At the Redwood Center for Theoretical Neuroscience, your research focuses on the relationship between artificial intelligence and the brain. Could you tell us about some of the projects you’re working on?

My passion for years has been augmented cognition and neuroprosthetics. The former is the study of how technology can expand cognitive capabilities; the later looks at how to directly interface technological and neural systems, for example, replacing missing limbs or eyes with brain-connected robotic prosthetics. By understanding not just “how” but “why” our brains work as they do will allow us to repair and even augment the existing cognitive, affective and perceptual abilities.

One line of my research draws algorithms from machine learning research to construct theoretical models of perception and attention. For example, my former student Engin Bumbacher and I designed a model which learned pitch perception remarkably human-like simply by “listening” to recordings of human speech. These models give us insight into why we see and hear the world as we do, while also providing an understanding “neural coding” needed so that neuroprosthetics can communicate directly with the brain.

More recently my interest in augmented cognition has brought me to technologies such as Google Glass. I have begun working with a team on applications for Glass such as contextual memory augment and real-time emotion processing. I have a pair now and am very exited about the potential to apply brain-inspired algorithms to enhance our engagement with the world.

Finally, my son was recently diagnosed with Type 1 (Juvenile) Diabetes and it has driven me to apply many of the algorithms I've learned from machine learning and brain research to a predictive model of diabetes. This is how the nerdy mom of a sick child copes.

Gild is a tech company that uses machine learning to predict optimal candidates for technology jobs. What is your role as chief scientist?

I typically spend my days in one of three ways: dreaming, convincing others to dream with me, and working out technical requirement to turn dreams into reality. The dream for Gild is maximizing the potential of developers (and some day designers, scientists and others) by predicting the best candidate for a job or project without regard for their credentials or social connections. I develop the algorithms that allow these predictions and run a lab full of great data developers to research and implement our predictive systems.

As Chief Scientist I also spend much of my day communicating Gild's dreams and capabilities to investors, press, customers and other scientists. Much like an academic scientist, speaking and writing are a huge part of the job. It is a wonderful experience talking about using truly cool science that is getting people job interviews they might never have been invited.

By the way, when I say that we don't take credentials into account, it turns our that degrees from some schools truly do predict better coding skills. Our models say very good things about CMU.

How do you have time to do all of this?!

While I'm usually happy to maintain the illusion that I'm a superhero, no one can truly do all these things by themselves. It only happens because I have managed to stumble upon wonderful teams who work to bring each of my endeavors to life. My team at Gild is amazing, and they keep the shop running while I dream my day away. I've also been so fortunate as a neuroscientist to have superlative collaborators, like Dr. Mike DeWeese in the Physics Department, and graduate students. In fact, one of those students, Engin Bumbacher, is a co-founder of Socos as well. And then there is Norma. She is absolutely the most amazing person I know. None of it would be possible without her.

When I look for motivation I just need to think of that world as I want it to be – for me, for my children, for all of us – and take a step in that direction.

How did your training at Carnegie Mellon help to prepare you for these multiple roles?

My time at CMU laid so many foundations for my approach to the world today. Some are quite tangible, such as my exposure to Carnegie Learning and their amazing technology or meeting my wife/co-founder. Others are more abstract, like CMU's collaborative spirit and entrepreneurial drive. When I was choosing a graduate program I can still remember that there were two schools about which everyone had an opinion: CMU and an unnamed school on the Charles River. The latter engendered both positive and negative opinions, but the collaborative culture of CMU was universally lauded. It was this quality that showed me how one person can accomplish more.

As a researcher and Chief Scientist my training in cognitive (Psychology Dept.) and computational (Center for the Neural Basis of Cognition - CNBC) neuroscience are my bread and butter. Being an applied computational research has opened up some many opportunities for me. And CMU's connection to solving concrete problems in the world, making things that make the world better, gave support my belief that we can all strive to lead lives of substance.

What do you see yourself doing 10 years from now?

Given all my work in augmented cognition I hope to find myself the beneficiary of that technology. I'm wearing a pair of Google Glass right now, taking a picture of my baby girl and sending it off to her Grandma. I dream about extending technologies like this to make us literally smarter. Imagine an InstantEMT app for glass that turns the user into a hands-on first responder, taking heart-rate and temperature measurements with the camera and connecting the user with a real emergency nurse who can see what you see. There is so much I want to see happen 10 years from now.

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