Each year eight Medallion Lecturers are chosen from across all areas of statistics and probability by the IMS Committee on Special Lectures. The Medallion nomination is an honor and an acknowledgment of a significant research contribution to one or more areas of research. Each Medallion Lecturer will receive a Medallion in a brief ceremony preceding the lecture.
Please join us for the 2017 Michigan Institute for Data Science Symposium.
The keynote speaker will be Cathy O’Neil, mathematician and best-selling author of “Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy.”
Other speakers include:
- Nadya Bliss, Director of the Global Security Initiative, Arizona State University
- Francesca Dominici, Co-Director of the Data Science Initiative and Professor of Biostatistics, Harvard T.H. Chan School of Public Health
- Daniela Witten, Associate Professor of Statistics and Biostatistics, University of Washington
- James Pennebaker, Professor of Psychology, University of Texas
More details, including how to register, will be available soon.
The Big Data in Transportation and Mobility symposium held June 22-23, 2017, in Ann Arbor, MI brought together more than 150 data science practitioners from academia, industry and government to explore emerging issues in this expanding field.
Sponsored by the NSF-supported Midwest Big Data Hub (MBDH) and the Michigan Institute for Data Science (MIDAS), the symposium featured lightning talks from transportation research programs around the Midwest; tutorials and breakout sessions on specific issues and methods; a poster session; and a keynote address from two representatives of the Smart Columbus project: Chris Stewart, Ohio State University Associate Professor of Computer Science and Engineering, and Shoreh Elhami, GIS Manager for the city of Columbus.
Speakers and attendees came from a number of organizations from across the midwest including the University of Michigan, University of Illinois, University of Nebraska, University of North Dakota, North Dakota State University, Ohio State University, Purdue University, Denso International America, Fiat Chrysler, Ford Motor Company, General Motors, IAV Automotive Engineering and Yottabyte.
“This was an extremely valuable opportunity to share information and ideas,” said Carol Flannagan, one of the organizers of the symposium and a researcher at MIDAS and the U-M Transportation Research Institute. “Cross-discipline and cross-institutional collaboration is crucial to the success of Big Data applications, and we took a significant step forward in that vein during this symposium.”
Topics addressed in talks, breakouts, and tutorials included:
- New Analytic Tools for Designing and Managing Transportation Systems
- New Mobility Options for Small and Mid-sized Cities in the Midwest
- Automated and Connected Vehicles
- Transforming Transportation Operations using High Performance Computing
- On-Demand Transit
- Using Big Data for Monitoring Bridges
At the closing session, participants outlined some areas that could be fruitful to focus on going forward, including increasing data-science literacy in the general public; diversity and workforce development in data science; public data-sharing platforms and partners; and privacy issues.
The University of Michigan is beginning the process of building our next generation HPC platform, “Big House.” Flux, the shared HPC cluster, has reached the end of its useful life. Flux has served us well for more than five years, but as we move forward with replacement, we want to make sure we’re meeting the needs of the research community.
ARC-TS will be holding a series of town halls to take input from faculty and researchers on the next HPC platform to be built by the University. These town halls are open to anyone and will be held at:
College of Engineering, Johnson Room, Tuesday, June 20th, 9:00a – 10:00a
NCRC Bldg 300, Room 376, Wednesday, June 21st, 11:00a – 12:00p
LSA #2001, Tuesday, June 27th, 10:00a – 11:00a
3114 Med Sci I, Wednesday, June 28th, 2:00p – 3:00p
Your input will help to ensure that U-M is on course for providing HPC, so we hope you will make time to attend one of these sessions. If you cannot attend, please email email@example.com with any input you want to share.
The Michigan Institute for Data Science (MIDAS) is convening a research working group on mobile sensor analytics. Mobile sensors are taking on an increasing presence in our lives. Wearable devices allow for physiological and cognitive monitoring, and behavior modeling for health maintenance, exercise, sports, and entertainment. Sensors in vehicles measure vehicle kinematics, record driver behavior, and increase perimeter awareness. Mobile sensors are becoming essential in areas such as environmental monitoring and epidemiological tracking.
There are significant data science opportunities for theory and application in mobile sensor analytics, including real-time data collection, streaming data analysis, active on-line learning, mobile sensor networks, and energy efficient mobile computing.
Our working group welcomes researchers with interest in mobile sensor analytics in any scientific domain, including but not limited to health, transportation, smart cities, ecology and the environment.
Where and When:
Noon to 2 pm, April 13, 2017
School of Public Health I, Room 7625
Brief presentations about challenges and opportunities in mobile sensor analytics (theory and application);
A brief presentation of a list of funding opportunities;
Discussion of research ideas and collaboration in the context of grant application and industry partnership.
Future Plans: Based on the interest of participants, MIDAS will alert researchers to relevant funding opportunities, hold follow-up meetings for continued discussion and team formation as ideas crystalize for grant applications, and work with the UM Business Engagement Center to bring in industry partnership.
a2-dlearn2016 is an annual event bringing together deep learning enthusiasts, researchers and practitioners from a variety of backgrounds.
The event will include speakers from the University of Michigan, University of Toronto, Toyota Research Institute and MDA Information Systems.
This symposium will bring together leaders from the public and private sectors and academia to meet the challenges posed by deployment of transformational transportation technologies. MIDAS affiliated faculty members Carol Flannagan, Al Hero and Pascal Van Hentenryck will be speaking.
For more information, visit the event website.
The Michigan Institute for Data Science (MIDAS) hosted Dr. Gary King of Harvard University for a talk titled “Big Data is Not About the Data!” on Friday, Oct. 3 as part of the MIDAS Seminar Series.
Video of the talk is now available for viewing online.
For a schedule of upcoming MIDAS Seminars, visit the seminar webpage.
ABSTRACT: Recovery from the Flint Water Crisis has been hindered by uncertainty in both the water testing process and the causes of contamination. On the other hand, city, state, and federal officials have been collecting and organizing a significant amount of data, including many thousands of water samples, information on pipe materials, and city records. Combining all of this information, and utilizing state-of-the-art algorithmic and statistical tools, we have be able to develop a clearer picture as to the source of the problems, to accurately estimate the greatest risks, and to more efficiently direct resources towards recovery.
Students interested in computational and data science are invited to learn about graduate programs that will prepare them for success in computationally intensive fields. Pizza and pop will be provided.
Two sessions are scheduled:
Monday, Sept. 19, 5 – 6 p.m.
Johnson Rooms, Lurie Engineering Center (North Campus)
Wednesday, Sept. 21, 5 – 6 p.m.
2001 LSA Building (Central Campus)
The sessions will address:
- The Ph.D. in Scientific Computing, which is open to all Ph.D. students who will make extensive use of large-scale computation, computational methods, or algorithms for advanced computer architectures in their studies. It is a joint degree program, with students earning a Ph.D. from their current departments, “… and Scientific Computing” — for example, “Ph.D. in Aerospace Engineering and Scientific Computing.”
- The Graduate Certificate in Computational Discovery and Engineering, which trains graduate students in computationally intensive research so they can excel in interdisciplinary HPC-focused research and product development environments. The certificate is open to all students currently pursuing Master’s or Ph.D. degrees at the University of Michigan. This year we will offer a new practicum option through the Multidisciplinary Design Program.
- The Graduate Certificate in Data Science, which is focused on developing core proficiencies in data analytics:
1) Modeling — Understanding of core data science principles, assumptions and applications;
2) Technology — Knowledge of basic protocols for data management, processing, computation, information extraction, and visualization;
3) Practice — Hands-on experience with real data, modeling tools, and technology resources.