September 19 | 1-2:30 pm
Sutardja Dai Hall, Banatao Auditorium
Maximizing Human Potential Using Machine Learning-Driven Applications
Speaker: Vivienne Ming, Chief Scientist at Gild
The elusive quest to identify and place skilled professionals has become an obsession in the talent wars of the tech industry (not to mention in schools from K though Postdoc). Respected companies such as Google have applied enormous resources to predicting the best developers and managers, and yet they also periodically acknowledge the shortcomings of their existing methodology (e.g., no more brainteasers). We will discuss the concept of continuous passive-implicit assessment, applied to both learners and professionals, from kindergärtners to (future) CEOs. Building cognitive models using unstructured data and ubiquitous sensors allows the assessment not only of concept mastery, but meta-learning development as well (e.g., “Grit” and “Social-Emotional Intelligence”). Such models can then be used to predict which content will be an effective learning experience for a given learner, identify ad hoc cohorts for collaborative learning, and access the value added across educational institutions.
Dr. Vivienne Ming,named one of 10 Women to Watch in Tech in 2013 by Inc. Magazine, is a theoretical neuroscientist, technologist, and entrepreneur. She is Chief Scientist at Gild, an innovative startup that builds better companies by unleashing human potential in their work-force using machine learning. Dr. Ming also co-founded her own cutting-edge startup, Socos, which applies cognitive modeling to create adaptive, personalized educational technology. She is a visiting scholar at UC Berkeley’s Redwood Center for Theoretical Neuroscience, pursuing her research in cognitive prosthetics, and in her free time, Dr. Ming explores augmented cognition using technology like Google Glass. One such project has been the development of a predictive model of diabetes to better manage blood glucose levels. She sits on the board of StartOut and Our Family Coalition, and speaks on issues of LGBT inclusion and gender in technology, recently receiving the State Farm Good Neighbor Award from Equality California. She lives in Berkeley with her wife and their two children. Her work and research have received extensive media attention including the New York Times, NPR, Nature, O Magazine, Forbes, and The Atlantic.
October 3 | 1-2:30 pm
190 Doe Library
Getting Land Change Right: Science, Open Source Software, and Global Data
Speaker: Richard Sharp, Lead Software Developer, Natural Capital Project
The Natural Capital Project (NatCap) aims to integrate the values of nature into all major decisions affecting the environment and human well-being. Their ultimate objective is to improve the state of biodiversity and human well-being by motivating greater and more cost-effective investments in both.
NatCap develops simple, use-driven approaches to valuing nature, works closely with decision makers, and provides free, open source ecosystem service software tools to a broad community of users. They are a partnership combining research innovation at Stanford University and the University of Minnesota with the global reach of conservation science and policy at The Nature Conservancy and the World Wildlife Fund. They work with leaders around the world to test and demonstrate how accounting for nature’s benefits can support more sustainable investment and policy decisions.
Rich Sharp leads the software development projects that support ecosystem service assessment and planning at the Natural Capital Project. Previously he was an assistant professor of computer science at St. Lawrence University and earned his Ph.D. in computer science from The Ohio State University. His research interests include developing computational software for natural science applications, high performance computing applications, cloud computing, and scientific visualization.
October 17 | 1-2:30 pm
190 Doe Library
Improving The Netflix Recommender System
Speaker: Carlos Gomez Uribe, Vice President of Product Innovation at Netflix
Today’s world forces us to make frequent decisions and often involve selecting one option amongst thousands of possibilities. These decisions arise in situations as simple as picking a book to read, a song to listen to or a movie to watch. At Netflix, our product is a subscription service that allows members to stream any movie or TV show in our large catalog via internet streaming. Having a recommender system that highlights the most relevant portion of our catalog for every single Netflix member is key to our business. In this talk, I will go over the various algorithms that make up our recommender system and share the process we use to improve upon it.
Carlos Gómez Uribe is the Vice President of Product Innovation at Netflix, leading the teams responsible for the video recommendation and search algorithms that connect Netflix members with movies and TV shows to enjoy. Carlos is a scientist and engineer turned product leader with years of experience applying mathematical and statistical modeling techniques in a variety of industries. Prior to Netflix, Carlos worked at Google, McKinsey & Company, Merrill Lynch and Analog Devices. His education includes a PhD in Medical and Electrical Engineering, a Master’s Degree in Electrical Engineering and Computer Science, and Bachelor degrees in Mathematics and in Electrical Engineering and Computer Science, all from the Massachusetts Institute of Technology.
November 7 | 1-2:30 pm
190 Doe Library
Big Data Management with the Myria Cloud Service
Speaker: Magda Balazinska, Assistant Professor, Computer Science at U. Washington
Many tools exist today for managing increasingly large collections of data. An important challenge, however, is that Big Data management tools must be both fast and easy-to-use. In this talk, we present the Myria system and service that we have developers in the database group at the University of Washington (in collaboration with the eScience Institute). The service is designed to meet the needs of modern data scientists, focusing on performance and productivity. We present an overview of the design of the tool, its key features, and a concrete analysis from the astronomy domain that uses the tool. We also present in more detail one innovative feature of Myria: its Personalized Service Level Agreements.
Magdalena Balazinska is an Associate Professor in the department of Computer Science and Engineering at the University of Washington. She’s the director of the IGERT PhD Program in Big Data and Data Science. She’s also a Senior Data Science Fellow of the University of Washington eScience Institute. Magdalena’s research interests are in the field of database management systems. Her current research focuses on big data management, scientific data management, and cloud computing. Magdalena holds a Ph.D. from the Massachusetts Institute of Technology (2006). She is a Microsoft Research New Faculty Fellow (2007), received an NSF CAREER Award (2009), a 10-year most influential paper award (2010), an HP Labs Research Innovation Award (2009 and 2010), a Rogel Faculty Support Award (2006), a Microsoft Research Graduate Fellowship (2003-2005), and multiple best-paper awards.
November 14 | 1-2:30 pm
190 Doe Library
Ask, Measure, Learn
Speaker: Lutz Finger, Director Data Science & Data Engineering at LinkedIn
Data is changing our world. Predictions using massive data not only have improved many products. At the same time, they have, in some industries, disrupted business models and created new ones. What does an organization need to do to generate a new competitive advantage out of data? The answer might be surprising: “Change the state of mind.”
Lutz Finger, Director of Data Science at LinkedIn and co-author of the book, Ask Measure Learn, will show how to work with data to obtain usable results. Companies do not need big data. They essentially want small and actionable advice. Some predictions will need big data to surface relevant information, but not all. The key to success for many companies, however, is to enable “data-driven” decision making”.
December 12 | 1-2:30 pm
190 Doe Library
Data and Technology for Social Good: What works, what doesn’t, and what Bayes Impact is doing about it
Speaker: Rayid Ghani, Research Director, Computation Institute & Senior Fellow, Harris School of Public Policy, University of Chicago
Data is a hot topic these days, and so is “social good,” but not many people think critically about what having impact actually entails. Bayes Impact engages on a range of projects in the social sector where we think data science can be a key lever. Interestingly, this also means knowing when data, or technology in general, is not the most critical piece.
Everett Wetchler is a Data Scientist with Bayes Impact. Formerly VP of Engineering at Kensho Finance and Senior Software Engineer at Google(.org), Everett’s main passion in life are empowering people and ice cream, in no particular order.