Rada Mihalcea, has been named a Fellow of the Association for Computing Machinery (ACM). ACM Fellows comprise an elite group that represents less than 1% of the Association’s global membership. This distinction recognizes those with far-reaching accomplishments that define the digital age.
443 leading scientists are elected in 2019 as Fellows of the American Association for the Advancement of Science (AAAS), in honor of their invaluable contributions to science and technology. U-M leads the way with 22 elected Fellows, including three MIDAS faculty members:
Brian Athey, Computational Medicine and Bioinformatics
Bill Currie, School for Environment and Sustainability
Jun Li, Computational Medicine and Bioinformatics
The 2019 Discover Innovate Impact (DII) National Data Science Challenge winning teams were recently announced and the GuanLab Team (Yuanfang Guan and Xianghao Chen) won the Task 1, Sepsis Onset Prediction prize. This was a national data science challenge established to advance human health through machine learning hosted by The University of Texas (UTHealth) School of Biomedical Informatics, sponsored by Cerner Corporation, and powered by AWS. Congratulations to GuanLab Team!
By Alex Piazza
Data science is an important tool that can help researchers tackle important societal challenges ranging from mobility and health to public safety and education.
But data science techniques and technologies also pose enormous potential for harm by reinforcing inequity and leaking private information. As a result, many sensitive datasets are restricted from research use, impeding progress in areas that impact society.
The University of Michigan, with a $2 million grant from the National Science Foundation (NSF), plans to establish a framework for a national institute that would enable research using sensitive data, while preventing misuse and misinterpretation.
“Data science has proven time and time again to be an invaluable resource when addressing emerging challenges and opportunities in areas of broad potential impact,” said H.V. Jagadish, director of the Michigan Institute for Data Science. “But having access to information comes with a great deal of responsibility, so our first priority is to ensure data science is not misused to disproportionately harm underrepresented groups.”
U-M researchers will partner with colleagues at New York University and the University of Washington over the next two years to deploy new techniques and technologies that enable responsible data science, while establishing an interdisciplinary community focused on the study, design, deployment and assessment of equitable data systems.
Equity is an important facet of data science that NSF aims to strengthen in the coming years, as the federal agency partners with universities such as U-M to enable new modes of data-driven discovery that will transform the frontiers of science and engineering.
The centerpiece of its ongoing effort, called Harnessing the Data Revolution at NSF, is the development of national institutes that address multidisciplinary problems in big data. U-M will help lay the groundwork for developing these institutes, which will eventually serve as a point of convergence for researchers from multiple disciplines to share expertise and address pressing challenges in data science.
“Information is being gathered about all of us, from our Google searches and online purchases to property tax records and social media activity,” said Margaret Levenstein, director of the Inter-university Consortium for Political and Social Research at U-M, which maintains the world’s oldest and largest archive of research and instructional data for the social and behavioral sciences. “You would assume the usage of data to be accurate and fair, but that is not always the case. That is why building a framework is so important because, in order for us to harness the enormous potential of big data, we need to ensure equity and privacy.”
H.V. Jagadish (U-M) is the principal investigator on this grant. Robert Hampshire (U-M), Bill Howe (UW), Margaret Levenstein (U-M) and Julia Stoyanovich (NYU) are co-principal investigators.
Dr. Robert Hampshire, MIDAS core faculty and Associate Professor of Public Policy at the Ford School, and his team, receives nearly $1 million in funding from the National Science Foundation’s Convergence Accelerator. The team leaders also include MIDAS faculty members Carol Flannagan, H.V. Jagadish and Margaret Levenstein. Read more at http://fordschool.umich.edu/news/2019/hampshire-receives-national-science-foundation-convergence-accelerator-grant.
MIDAS affiliated faculty and Associate Professor in Computer Science and Engineering, Dr. Mike Cafarella, receives funding from the National Science Foundation, in its program of Convergence Accelerator in Harnessing the Data Revolution. This project, “Simultaneous Knowledge Network Programming and Extraction”, is a direct result of his team’s project funded by MIDAS. Read more at https://www.nsf.gov/od/oia/convergence-accelerator/index.jsp.
See the publication at https://www.nature.com/articles/s41591-019-0548-6
For information on the press release: https://precisionhealth.umich.edu/news-events/features/taking-machine-learning-models-in-health-care-from-concept-to-bedside/