ORC IAP Seminar 2014
"Analytics and Big Data"
Date: Wednesday, January 29th
Description: The "big data revolution" is in full swing, and as we move into 2014 the true power of big data is revealing itself in a variety of areas. The MIT Operations Research Center has organized a day-long seminar on the uses of big data in analytics - the scientific process of transforming data into insight for making better decisions. Four speakers will present their experiences in using big data for decision making, with applications in finance, retail, medicine, and the use of social graph data to improve services.
9:30am - 10:00am - Intro and Continental Breakfast
10:00am - 11:00am - Bala Chandran. A consultant at Analytics Operations Engineering in Boston.
11:00am - 12:00pm - Sepandar Kamvar. The LG Associate Professor of Media Arts and Sciences at MIT, the ex-head of personalization at Google, and the founder/CEO of Kaltix, a personalized search company.
12:00pm - 1:00pm - Lunch (please RSVP by 1/24/14)
1:00pm - 2:00pm - Rama Ramakrishnan. Founder and CEO of CQuotient, an email retailing company focused on hyper-personalization.
2:00pm - 3:00pm - John Guttag. The Dugald C. Jackson Professor of Electrical Engineering and Computer Science, and a previous head of the EECS department.
Student Coordinators: Iain Dunning, Christina Epstein, Jonathan Paynter
Faculty Coordinator: Dimitris Bertsimas
Speaker: Bala Chandran
Title: Reading Between the Lines of Big Data
Abstract: With the availability of higher quality and fidelity data, as well as more powerful hardware and software, the ability of advanced analytics to drive insights into large data sets has never been greater. One way to add value to a huge data set is to augment it with inferred data using sophisticated models built on medium to large subsets, that allow us to derive more meaningful insights from the parent data set. I will demonstrate this using examples from recent consulting engagements in retail and financial services.
Bio: Bala is a senior consultant at Analytics Operations Engineering, Inc., where he has worked extensively on data mining and network optimization. Prior to joining Analytics, Bala received a Ph.D. in Operations Research from Berkeley and Master’s in Business from the University of Maryland.
Speaker: Sepandar Kamvar
Title: Mining the Human Web
Abstract: In the past few years, we have seen a tremendous growth in public human communication and self-expression, through blogs, microblogs, and social networks. In addition, we are beginning to see the emergence of a social technology stack on the web, where profile and relationship information gathered by some applications can be used by other applications. This technology shift, and the cultural shift that has accompanied it, offers a great opportunity for computer scientists, artists, and sociologists to study (and organize) people at scale. In this talk I will discuss how the changing web suggests new paradigms for search and discovery. I will discuss some recent projects that use web search to study human nature, and use human nature to improve web search. I will describe the underlying principles behind these projects and suggest how they might inform future work in search, data mining, and social computing.
Bio: Sep Kamvar is the LG Associate Professor of Media Arts and Sciences at MIT, and the Director of the Social Computing Group at the MIT Media Lab. His research focuses on social computing and information management. Prior to MIT, Sep was the head of personalization at Google and a consulting professor of Computational and Mathematical Engineering at Stanford University. Prior to that, he was founder and CEO of Kaltix, a personalized search company that was acquired by Google in 2003. Sep is the author of two books and over 40 technical publications and patents in the fields of search and social computing. He is on the technical advisory boards of several companies, including Clever Sense and Etsy. His artwork has been exhibited at the Museum of Modern Art in New York, the Victoria and Albert Musem in London, and the National Museum of Contemporary Art in Athens. Sep received his Ph.D. in Scientific Computing and Computational Mathematics from Stanford University and his A.B. in Chemistry from Princeton University.
Free catered lunch for attendees who RSVP'd to Jon Paynter (jpaynter "at" mit.edu) by 1/22/14.
Speaker: Rama Ramakrishnan
Title: Big Data meets Big Math: Customer Modeling in the Retail Industry
Abstract: Retailers have historically run their businesses with product and store level data and analytics. Recently, however, this has started to change due to the growing might of Amazon and its reputation as a very smart wielder of sophisticated customer analytics technology and also due to the fear that if their competitors exploit Big Data (from site logs, customer reviews and social media) before they do, they will be left behind. As a result, retailers are paying more attention to technologies that could help them harness Big Data, understand their millions of customers at a very granular level and translate this understanding into better decisions. In this talk, we share our experiences and results from building and deploying customer-level models for highly individualized email marketing at retailers with tens of millions of customers. We describe the modeling building blocks that comprise enterprise-grade marketing science systems and the modern, highly scalable cloud-based technologies that make these systems possible.
Bio: Dr. Rama Ramakrishnan (@rama100) is Founder and CEO of CQuotient (www.cquotient.com), a company that enables omnichannel retailers to deliver truly individualized messages to each and every customer. CQuotient’s Personalized Marketing Engine™ combines advanced predictive analytics with a wide range of data to predict customer behavior and drive incremental revenue. Rama has over 20 years of experience in applying data science to business problems across a range of industries. Earlier in his career, Rama was Vice-President and Chief Scientist at Oracle Retail and ProfitLogic, a consultant at McKinsey & Company and Senior Lecturer at MIT Sloan School of Management. He has a Ph.D. from MIT in Operations Research, a B.S. from Indian Institute of Technology and holds several patents in analytics.
Speaker: John Guttag
Bio: Professor Guttag received a bachelor's degree in English from Brown University in 1971, and a master's degree in applied mathematics from Brown in 1972. In 1975, he received a doctorate in computer science from the University of Toronto. He was a member of the faculty at the University of Southern California from 1975-1978, and joined the MIT faculty in 1979.
From 1993 to 1998, Professor Guttag served as Associate Department Head for Computer Science of MIT's Electrical Engineering and Computer Science Department. From January of 1999 through August of 2004, Professor Guttag served as Head of that department. Professor Guttag currently co-heads the Computer Science and Artificial Intelligence Laboratory's Networks and Mobile Systems Group. This group studies issues related to computer networks, applications of networked and mobile systems, and advanced software-based medical instrumentation and decision systems.
Professor Guttag's current research is centered on the application of advanced computational techniques to medicine. Current projects include prediction of adverse medical events, prediction of response to therapies, non-invasive monitoring and diagnostic tools, and tele-medicine. He has also done research, published, and lectured in the areas of sports analytics, software defined radios, software engineering, mechanical theorem proving, and hardware verification.
Professor Guttag is a Fellow of the ACM and a member of the American Academy of Arts and Sciences.
RSVP to Jon Paynter (jpaynter "at" mit.edu) by 1/24/14.