MIT Big Data Initiative Annual Meeting 2014 Agenda:
DATES: NOV 12-13, 2014
LOCATION: MIT Media Lab, E14 6th floor, multi-purpose room, MIT Cambridge, MA
75 Amherst Street, Cambridge, MA 02139
DAY 1: Wednesday Nov 12 2014
8:30am Registration and Breakfast
9:00am Introduction, MIT Big Data Initiative at CSAIL
Sam Madden and Elizabeth Bruce, MIT Big Data Initiative at CSAIL co-Directors
9:15-9:45 KEYNOTE: "BIG DATA AND SYSTEMIC RISK"
MUNTHER DAHLEH, Acting Director of Engineering Systems Division and Professor EECS, MIT
9:45-10:45am BIG DATA APPLICATIONS
"Making Roads Safer by Making Drivers Better"
Prof. Hari Balakrishnan, Professor of Computer Science, MIT CSAIL and CTO, Cambridge Mobile Telematics
"Bayesian Regression and Bitcoin"
Prof. Devavrat Shah, Associate Professor, MIT CSAIL, Laboratory for Information and Decision Systems
"Places Database: Large Scale Visual Scene Recognition"
Prof. Antonio Torralba, Associate Professor, MIT CSAIL, Graphics and Vision
10:45-11:15am BREAK
11:15-11:45am KEYNOTE: "DEEP LEARNING: OVERVIEW & TRENDS"
ANDREW NG, Chief Scientist of Baidu and Associate Professor of Computers Science at Stanford University
11:45-12:30pm BIG DATA PREDICTIVE ANALYTICS & MACHINE LEARNING
"Towards a Recommender System That Suggests Models and Parameters for Data"
Kalyan Veeramachaneni, Research Scientist, MIT CSAIL, The ALFA Group
"Unfolding Psychological State: Mortality Modelling in Intensive Care Units"
Marzyeh Ghassemi, Ph.D Student, MIT CSAIL, Clinical Decision Making Group
"Methods and Models for Interpretable Classification"
Berk Ustun, Ph.D. Student in EECS, MIT, Prediction Analysis Lab
12:30-1:30 LUNCH
1:30-2pm “STATISTICAL LEARNING AND BIG DATA"
Prof. Josh Tenanbaum, Computational Cognitive Science, MIT
What are the limits of statistical learning in the context of big data? What is state of the art in “deep learning” today and how do we assess its value and its limitations?
2:00-3:30pm BIG DATA AND PRIVACY
Session Chairs: Elizabeth Bruce (MIT), Mona Vernon (Thomson Reuters) and Danny Weitzner (MIT) -- Working Group Chairs
This Big Data Privacy Session will review recent work by the Big Data Privacy Working Group in developing use case scenarios that illustrate the unique challenges of managing privacy when it comes to big data and mapping emerging technology approaches. Panelists will discuss specific scenarios and key challenges, as well as promising technology solutions.
Introduction and Big Data Privacy Working Group - Elizabeth Bruce, MIT
Big Data Privacy & Policy - Danny Weitzner, MIT
Una-May O'Reilly, Principal Research Scientist, MIT CSAIL
ALFA Research Group
Cameron Kerry, Visiting Scholar, MIT
MIT Media Lab
Lalana Kagal, Principal Research Scientist, MIT CSAIL
Decentralized Information Group (DIG)
Salil Vadhan, CS + Applied Mathematics
SEAS, Harvard
Panel Discussion moderated by Danny Weitzner, Director of MIT CSAIL Decentralized Information Group
3:30-5:30pm BIG DATA COOL TOOLS POSTERS, DEMOS AND RECEPTION
LOCATION: MIT Media Lab
Bldg E14 6th Floor, Multi-purpose room + Winter Garden room, MIT, Cambridge, Massachusetts
5:30pm Meeting adjourns for day
6:00pm Dinner at local restaurants (members only) - confirm RSVP at registration desk
DAY 2: Thursday Nov 13
LOCATION: MIT Media Lab
Bldg E14 6th Floor, Multi-purpose room, MIT, Cambridge, Massachusetts
8:00-9:00am Big Data Advisory Board Meeting (advisory board members only)
Location: Media Lab (E14-493)
8:30-9:30am Breakfast / Networking
9:30-10:30am INDUSTRY PANEL: “BIG DATA IN PRACTICE: WHAT'S HARD? ”
The purpose of this session is to hear from industry members on what is really challenging when it comes to piloting a big data project. What are you experiencing as the limits of the systems and tools being used today – from integration and cleaning to visualization and analytics. Sam Madden will serve as a moderator and facilitate dialog to provide discussion around potential solutions and approaches from a research perspective.
John Cardante, Big Data and Analytics Technologist, EMC
Surajit Chaudhuri, Distinguished Scientist, Microsoft Research
Anu Krishnan, Manager of IT Innovation Centre for Excellence, Shell
Moderated Discussion – Sam Madden (MIT) with Mike Stonebraker (MIT) and Matei Zaharia (MIT)
10:30-11:30am SYSTEMS AND TOOLS FOR BIG DATA
"MIT Research in Data Integration"
Prof. Mike Stonebraker, Adjunct Professor, MIT CSAIL
“Designing a Composable Toolbox for Data Analysis in Spark”
Prof. Matei Zaharia, Assistant Professor, MIT CSAIL
"The MIT Datahub Project"
Prof. Sam Madden, Professor MIT CSAIL
11:30-12pm “CONNECTION SCIENCE"
Prof. Alex (Sandy) Pentland, Toshiba Professor of Media Art and Sciences
Big data allows us to begin creating accurate mathematical models of human behavior. This new capability allows us to design transportation, energy, health, finance, and organizational systems to be more productive and innovative than ever before.
12:00-12:45pm LUNCH
1:00-3:00pm BIG DATA + FINANCE
Session Chairs: Prof. John Guttag and Prof. Andrew Lo
The Big Data Finance session will highlight examples of current research directions through an interactive panel discussion with MIT faculty. Audience participants are encouraged to share their thoughts about the applications of Big Data in the financial services sector in areas such as: consumer finance, credit and privacy; policy and compliance; and emerging digital currencies.
Welcome: Daniela Rus, Professor of EECS and Director of the Computer Science and Artificial Intelligence Lab (CSAIL)
Introduction: Andrew Lo, Charles E. and Susan T. Harris Professor of Finance at the MIT Sloan School of Management, Director of MIT's Laboratory for Financial Engineering, and CSAIL PI
Panel:
Nickolai Zeldovich, Associate Professor, MIT CSAIL
Andrew Lo, Professor of Finance, MIT Sloan School of Management
Vinod Vaikuntanathan, Assistant Professor, CSAIL
Antoinette Schoar, Professor of Finance, MIT Sloan School of Management
Roberto Rigobon, Professor of Applied Economics, MIT Sloan School of Management
Moderated Discussion: Andrew Lo
3:00-3:30pm REFRESHMENTS AND NETWORKING
3:30pm Meeting Adjourns