"Maximize human potential — that of others as well as your own...
"It's a philosophy that Vivienne Ming refined as a doctoral student at Carnegie Mellon University. Now the theoretical neuroscientist — involved in research, entrepreneurial technology and philanthropy — has been named one of Inc. Magazine's 10 Women to Watch in Tech in 2013. 'All of my endeavors are motivated by a desire to maximize human potential,' said Ming. 'It's a big dream, better suited to science fiction than the lab or the board room. But CMU inspired me to try anyhow.'" - CMU, "Revolutionary Potential"
- C2SV:2014 - Creative Convergence Silicon Valley (Sep 10-14, SJ), HR Tech (Oct 7, Las Vegas), and CNBC 20th Anniversary (Oct 18, Pittsburgh)
- "Silicon Valley’s Embrace of the Gay and Lesbian Community" - New York Times
- "Hiring With Science: Big-Data Brings Better Recruits" - Forbes
- "Building a More Diverse Workforce Through Software" - Re/Code
- "Your web presence just picked your next job" - Wired UK
- "Gild Says Algorithms Can Lift People Out Of Poverty" - Silicon Valley Insider & ZDnet
- "Keeping the promise of educational technology" - SXSWedu Keynote
- "Can you see the real me?" - O Magazine, yes that's right: Oprah!
Socos, Co-Founder & Managing Partner
"Socos takes data from what students already do in their classes, and builds a model of their conceptual knowledge that lets teachers adapt instruction in real time, whether to address common misconceptions or expand on unusual insights." - Inc, "10 Women to Watch in Tech in 2013"
Gild Inc., VP of Research & Insight
"How Big Data Is Playing Recruiter for Specialized Workers"
"Of late, growing numbers of academics and entrepreneurs are applying Big Data to human resources and the search for talent, creating a field called work-force science. Gild is trying to see whether these technologies can also be used to predict how well a programmer will perform in a job. The company scours the Internet for clues: Is his or her code well-regarded by other programmers? Does it get reused? How does the programmer communicate ideas? How does he or she relate on social media sites?"
"Dr. Ming’s answer to what she calls “so much wasted talent” is to build machines that try to eliminate human bias. It’s not that traditional pedigrees should be ignored, just balanced with what she considers more sophisticated measures.
In all, Gild’s algorithm crunches thousands of bits of information in calculating around 300 larger variables about an individual: the sites where a person hangs out; the types of language, positive or negative, that he or she uses to describe technology of various kinds; self-reported skills on LinkedIn; the projects a person has worked on, and for how long; and, yes, where he or she went to school, in what major, and how that school was ranked that year by U.S. News & World Report." - New York Times
The Redwood Center for Theoretical Neuroscience is a group of theorists consisting of faculty, postdocs and graduate students. We are part of the Helen Wills Neuroscience Institute at the University of California at Berkeley, located in the 5th floor of Evans Hall on the Berkeley campus.
Our goal is to develop mathematical and computational models of the underlying neurobiological mechanisms involved in perception, cognition, learning, and motor function. We collaborate with experimental neuroscience labs in the design of experiments and in the analysis of neural data. We also train students at UC Berkeley in these ideas and methods.
"The abilities to learn, remember, evaluate, and decide are central to who we are and how we live. Damage to or dysfunction of the brain circuitry that supports these functions can be devastating, leading to Alzheimer’s, schizophrenia, PTSD, or many other disorders. ...One promising approach is to build an interactive device to help the brain learn, remember, evaluate, and decide. One might, for example, construct a system that would identify patterns of brain activity tied to particular experiences and then, when called upon, impose those patterns on the brain."
"How to Make a Cognitive Neuroprosthetic", MIT Technology Review
Jitterbug, Parent & Inventor
Confronted with Type 1 Diabetes
"There are... parents who understand how to take the lead—while doctors remain set in their old ways. Instead of the formerly all-knowing doctor, Vivienne Ming’s best friend for her son is data-driven technology. When their son, Felix showed symptoms of child onset diabetes, they did what they knew best: they started collecting every bit of data they could on Felix’s eating, exercise and behavior." - Shel Israel, Age of Context
My son is amazing and so we are building:
This is a personal project of love and frustration. It is an app and mathemtical model to
- predict blood glucose level,
- infer carb ratio and basal rate,
- predict optimal insulin dosing,
- detect anomalies like poor infusion sites and illness,
- learn personalized BG impact of food, and
- accept natural language input like, "I'm going to eat a medium apple."
Director & Board Secretary
StartOut is a national 501(c)(3) nonprofit organization dedicated to creating great business leaders by fostering LGBT entrepreneurs. Currently with 57 annual events and over 5,200 participants nationwide, StartOut inspires, educates and supports LGBT entrepreneurs. We have chapters in Austin, Boston, New York, and San Francisco with Los Angeles in development.
We help create the next generation of LGBT business leaders by helping aspiring entrepreneurs start new companies, helping current entrepreneurs to grow and expand their businesses, and engaging successful entrepreneurs as role models and mentors for less established entrepreneurs. We also strive to foster LGBT leadership in the business community.
On Mic & Camera
- Girls Who Code, Aljazeera America (August 15, 2014)
- The Digital Show powered by the Wharton School, Sirius Radio (April 26, 2014)
- Architecting Better Companies by Unleashing Human Potential, CDO Vision (April 29, 2014)
- Keynote, SXSWedu (March 4, 2014)
- EdLab GroundBREAKERS, Columbia University (January 27, 2014)
- Future of Job Creation and HR Tech Summit (January 8, 2014)
- The Atlantic's inaugural Silicon Valley Summit (December 16, 2013)
- Quantified Self Global Conference Keynote (October 11, 2013)
- NPR: Here & Now (May 21, 2013)
- Robert Scoble Interview (May 13, 2013)
- CBC: Spark (June 14, 2013)
- KALX: Method to the Madness (May 10, 2013)
- "Silicon Valley’s Embrace of the Gay and Lesbian Community" New York Times
- "Hiring With Science: Big-Data Brings Better Recruits" Forbes
- "Building a More Diverse Workforce Through Software" Re/Code
- "Your web presence just picked your next job" Wired UK
- "Gild Says Algorithms Can Lift People Out Of Poverty" Silicon Valley Insider & ZDnet
- "Will Algorithms Replace Resumes? Why Neuroscientist Dr. Vivienne Ming Says Using Big Data to Find Hidden Talent Is Not Only the Wave of the Future; It's the Only Way to Bring Real Diversity to the Workplace" Tweeting for Change
- "The Future of Personalized Learning" Compass Learning
- "Parenting Techniques from Vivienne and Norma Ming" Compass Learning
- "The 3 Hottest Debates at SXSWedu" IAT
- "Down with Divas" Forbes
- "They're Watching You at Work" The Atlantic
- "Your Job, Their Data: The Most Important Untold Story About the Future" The Atlantic
- "Google Glass Developers: We're still flying half blind" CNET
- "Vivienne Ming: The Transformative Power of Being Yourself" The Advocate
- "Profiles - Vivienne Ming"New Learning Times
- "Can you see the real me?"O Magazine
- All The World's A Resumé: The Facebook Generation Enters The WorkforceForbes
- The Hot List: The 10 Hottest Women in BusinessWILES Magazine
- "What IT recruiters know about you -- whether you're looking or not"ComputerWorld
- "How big data is playing recruiter for specialized workers"New York Times
- "10 Women to Watch in Tech in 2013"Inc
- Visualizing Topics, Time, and Grades in Online ClassDiscussions Ming & Ming (2013, June). Paper presented at the 10th International Conference on Computer Supported CollaborativeLearning (CSCL). Madison, WI.
- Faculty Tools for Visualizing Online Class Discussions Ming & Ming (2013, April). Annual Meeting of the American Educational Research Association, San Francisco CA.
- Modeling student conceptual knowledge from unstructured data using a hierarchical generative model Ming & Ming (2012) NIPS2012 Workshop: Personalizing Education With Machine Learning. South Lake Tahoe, CA.
- Automated Predictive Assessment from Unstructured Student Writing Ming & Ming (2012). IARIA, Data Analytics.
- Predicting Student Outcomes from Unstructured Data Ming & Ming (2012). UMAP2012.
- Sparse codes for speech predict spectrotemporal receptive fields in the inferior colliculus Carlson, Ming & DeWeese (2012). PLoS CompBio.
- Pitch-sensitive components emerge from hierarchical sparse coding natural sounds Bumbacher & Ming (2012). ICPRAM2012.
- Evidence of efficient coding in human speech perception Ming & Holt (2009). JASA 129, Num. 3: 1312-1321.
- Efficient auditory coding Smith & Lewicki (2006). Nature 439, Num. 7079.
- Heirarchical coding of natural signals in a dynamical system model Bumbacher & Ming (2012) Cosyne2012.
- Pitch-sensitive components emerge from hierarchical sparse coding natural sounds. Bumbacher & Ming (2012) ICPRAM2012.
- A Sparse Representation of Speech Data Carlson, Ming & DeWeese (2010) Sensory Coding & the Natural Environment, Gordon Research Conference.
- Efficient coding of natural sounds using spikes predicts cochlear filters Smith & Lewicki (2005) Advances in Neural Information Processing Systems 17. MIT Press, Cambridge, Massachusetts.
- Efficient coding of time-relative structure in natural sounds using spikes Smith & Lewicki (2005) Neural Computation. Vol. 17, Num. 1.
- An approach to automatic recognition of spontaneous facial actions Bartlet, Braathen, Littlewort, Smith & Movellan (2003) Advances in Neural Information Processing Systems 15. MIT Press, Cambridge, Massachusetts.
- A sparse subspace model of higher-level sound structure Wang, Olshausen & Ming (2008) Computational and Systems Neuroscience. Salt Lake City, UT.
- The spectrotemporal density components of speech Ming (2007) Computational Cognitive Neuroscience. San Diego, CA.
- Cross-linguistic evidence of adaptation of speech statistics to the mammalian auditory code Ming & Lewicki (2007) Computational Cognitive Neuroscience. San Diego, CA.
- Learning invariant structure in speech sounds using subspace sparse coding Ming & Wang (2007) Computational Cognitive Neuroscience. San Diego, CA.
- A theoretical model of cochlear processing improves spectrally-degraded speech perception Smith & Holt (2006) Annual Meeting of the Acoustical Society of America. Providence, RI.
- Efficient auditory coding Smith& Lewicki (2006) IGERT 2006 Annual Meeting. Arlington, VA.
- A theoretical model of cochlear processing improves simulated cochlear implant hearing Smith& Holt (2006) Computational and Systems Neuroscience. Salt Lake City, UT.
- Efficient coding of acoustic structure with spike times Smith& Lewicki (2004) Presented at the Computational and Systems Neuroscience Conference. Cold Springs Harbor, NY.
- Spike codes using populations of stochastic units strong>Smith& Lewicki (2004) Presented at the Gordon Conference on Sensory Coding and the Natural Environment. Queen's College, Oxford, UK.
- An approach to automatic recognition of spontaneous facial actions Braathen, Bartlet, Littlewort, Smith& Movellan (2002) Presented at the Conference on Face and Gesture Recognition.
- Computer recognition of facial actions: A study of co-articulation effects Smith, Bartlet & Movellan (2001) Proceedings of the 8th Symposium on Neural Computation.
- Tip-of-the-Tongue incidence in Spanish-English and Tagalog-English Bilinguals Golan, Acenas, & Smith(2001) Presented at the 3rd International Symposium on Bilingualism.
I'm a terrible networker but I love to talk over tea and always enjoy a fascinating conversation.Socos: 1900 Addison #200, Berkeley, CA Email: firstname.lastname@example.org
Gild: 465 California St. #1250, SF, CA