Flavio Chierichetti
Flavio is an associate professor in the Computer Science department at Sapienza University of Rome. His interests intersect algorithmics, data mining and data modeling. Flavio obtained his PhD in Computer Science from Sapienza University; after his PhD, he held a post-doctoral position at Cornell University. Outside academia, Flavio spent various semesters as a visiting researcher at Google Mountain View.
Flavio received an ERC Starting Grant, a Google Focused Research
Award, and a SIR grant. He is also the recipient of the 2014 Best
Young Researcher in Theoretical Computer Science award of the Italian Chapter of EATCS, and co-recipient of the 2015 KDD Best Paper Award.
Title: Randomly Walking A Fine Line
Abstract: Nowadays, online networks are so large that many simple computational tasks are dauntingly hard on them. Of the many techniques that have been proposed to solve simple problems on large graphs, random walk-based ones are some of the most popular. In this talk, we will consider a number of random walks-based methods for analyzing large-scale graphs — we will discuss their applicability, the statistical guarantees that they can provide, and some of the common pitfalls in their usage.
We will address the problems of estimating the size of a graph, of selecting uniform-at-random nodes from a graph, of randomly selecting nodes with other distributions, and of approximating the relative frequency of small graphlets in a graph. While some of these problems can be solved efficiently and in a statistically sound way via random walks-based methods, others do not admit such ideal solutions and, instead, require a trade off between efficiency and correctness.
Ed H. Chi
Ed is a Research Scientist at Google, leading a team focused on recommendation systems, machine learning, and social interaction research. He has launched significant improvements of recommenders for YouTube, Google Play Store and Google+. With over 35 patents and over 100 research articles, he is known for research on Web and online social systems, and the effects of social signals on user behavior.
Prior to Google, he was the Area Manager and a Principal Scientist at Palo Alto Research Center‘s Augmented Social Cognition Group, where he led the group in understanding how social systems help groups of people to remember, think and reason. Ed completed his three degrees (B.S., M.S., and Ph.D.) in 6.5 years from University of Minnesota, and has been doing research on software systems since 1993. He has been featured and quoted in the press, including the Economist, Time Magazine, LA Times, and the Associated Press, and has won awards for both teaching and research. In his spare time, Ed is an avid photographer and snowboarder.
Title: Optimizing for User Experience with Data Science and Machine Learning
Abstract: Understanding users and optimizing for user experience are critical parts of building successful apps and services. While there had been a tremendous amount of past work studying user and social interactions, in practice, it wasn’t until quite recently that researchers are able to study these interaction mechanisms at large scales easily. In this talk, I will illustrate data-driven approaches to understand what are happy engaged users, and present case studies of how we utilize novel machine learning techniques to optimize for long-term user engagements in practice.
Dr Mounia Lalmas
Mounia is a Director of Research at Yahoo, where until recently she led a team of scientists working on Advertising Quality. She has just joined the Publisher Science team at Yahoo working on building personalised and engaging products and services. She also hold an Honorary Professorship at University College London. Her work focuses on studying user engagement in areas such as native advertising, digital media, social media, and search.
Title: Advertising Quality Science
Abstract: Native advertising is a specific form of online advertising where ads replicate the look-and-feel of their serving platform. In such context, providing a good user experience with the served ads is crucial to ensure a positive user experience and hence long-term user engagement. In this talk, I will describe work at Yahoo aiming at understanding the user experience on ads in the mobile context and building learning frameworks to identify and account for ads of low quality while ensuring a return of investment to advertisers.
Shaun Gregory
Shaun has a Bachelor of Science (Hons) from the University of Western Australia in Mathematical Geophysics and a Master of Business and Technology from the University of New South Wales.
Shaun is passionate about technology and innovation and the role they play in enabling and transforming business. In his current role as Senior Vice President and Chief Technology Officer, he oversees Woodside’s technology advancements in LNG, data analytics, IT, cognitive computing and selection of development concepts for Woodside’s growth projects.
Shaun is a member of Dean’s Council for the faculty of Engineering, Computing and Mathematics at UWA and is a Board member of Scitech WA.
Title: Think Big
Abstract: Transformation is hard. It’s more than the right tools, it’s about changing mindsets and culture. If you want a digital transformation, you must think big. Woodside is Australia’s largest independent oil and gas company. Today, we operate 8% of global LNG supply. We have over 30 years of operating history and over that time have amassed huge quantities of data and unstructured information. In this talk, Shaun Gregory will describe Woodside’s innovation journey from follower to digital leader; how Woodside is revolutionising the way it is working, how Woodside is shifting mindsets, and how its crystalised a transformation.