Transportation

With the advent of driverless vehicles and ride-sharing in an age of continued urbanization, climate change and pollution, we are undoubtedly at the brink of the next transportation revolution. Data science is at the center of this revolution. The collection of data on transportation and driver behavior is no longer a bottleneck; our current challenge is to develop sophisticated data analysis and interpretation that impact the design of future transportation to address challenges including automation, climate change and urban inequality. The MIDAS Transportation Research Hub aims to position U-M researchers at the forefront of our nation’s Big Data transportation research, develop innovative methods and tools, and apply the insight to solve real-world transportation challenges.  The MIDAS Data-Intensive Transportation Research Hub currently funds two projects.

Learning Analytics

Three questions have stirred controversies, fueled perpetual debates, and polarized educators, parents and students for as long as educational institutions have existed: What constitutes good teaching? What are effective learning practices? And, perhaps most importantly, what does “student achievement” mean? Attempts to answer these questions have evolved from philosophical musings to data-based modern educational research. Today, Big Data research adds to our power as we unravel the secret of successful learning and teaching .  The MIDAS Learning Analytics Research Hub is a new addition to U-M’s nationally renowned research in learning analytics.  MIDAS funds two initial core research projects.

Health Science

The unprecedented wealth of health data brings unprecedented opportunities and challenges to improve healthcare.  On the most microscopic level, we are now examining the genome one cell at a time, monitoring in real-time an individual’s health behavior, and prescribing medication based on the genetics and chemistry of each individual.  On the most macroscopic level, we can combine dozens of clinical record data for one patient, and can analyze the health data of an entire nation.  However, our ability to gain insight into such vast data lags significantly behind our ability to accumulate data.  The MIDAS Data-Intensive Health Science Research Hub aims to position UM researchers as national leaders as biomedical science embraces the opportunities and challenges brought about by advances in data science, catalyze the development of theories and innovative methodologies in data science, and their application to the entire spectrum of biomedical science.  The hub currently funds three projects.

Data Science for Music

When you listen to a Beethoven piano concerto, pick a song or channel to listen to on the web, send your kids to music lessons, or donate to your local symphony orchestra, do you think of data science? Unlikely. But data science is increasingly critical in the creative process and commercial activities of music. Using Big Data analytics, online music platforms tailor individualized song recommendations for their users; music theorists search for defining features in different types of music; computer scientists develop algorithms that can compose music in any style; behavioral scientists determine how to best engage concert goers; the list is endless. MIDAS recently established the Data Science for Music Research Hub and currently funds four projects.

Project Filter

Use this box to search MIDAS Funded Projects by name, faculty member, or other keyword. Use the filters below to search by major data science methodologies or applications.

Applications

Methodologies

A Computational Study of Patterned Melodic Structures across Musical Cultures

Data Science and Human Endeavor

A Data-Driven Framework for Microstructure Optimization of Additively Manufactured Piezoelectric Composites

Data Science and Human Endeavor

A Social Science Collaboration for Research on Communication and Learning based upon Big Data

Data Science and Human Endeavor, Data Science and Our Society

Achieving ML Robustness by Leveraging Physics-based Constraints

Data Science and Human Endeavor

Building a Transportation Data Ecosystem

Data Science and Human Endeavor, Data Science and Our Habitat, Data Science and Our Society

CHANGES: Collections, Heterogeneous data, and Next Generation Ecological Studies

Data Science and Our Habitat

Computational Approaches for the Construction of Novel Macroeconomic Data

Data Science and Human Endeavor, Data Science and Our Society

Data Science for Quantum Simulation

Data Science and the Physical World

Database Learning: A Query Engine That Becomes Smarter Over Time

Data Science and Human Endeavor

Decoding the Environment of Most Energetic Sources in the Universe

Data Science and the Physical World

DevEEG: A Robust Repository for Developmental Electroencephalogram Data

Data Science and Human Health

Estimating county-level age group contact rates from time use data

Data Science and Human Health

From data to knowledge: Applying the principles of data science to understand preventable inequities in care and support among COVID-19 cases in Michigan

Data Science and Human Health

Fusing Physics and Deep Learning for Solar Dynamics Forecasting

Data Science and the Physical World

Handling Selective and Imperfect Testing in Design and Inference of COVID-19 Studies

Data Science and Human Health

High-resolution spatial analysis to inform the response to COVID-19 in Michigan

Data Science and Human Health

HOME: Holistic Modeling of Education

Data Science and Human Endeavor

Identifying Real-Time Data Predictors of Stress and Depression Using Mobile Technology

Data Science and Human Health

Improved real-time surveillance of COVID-19 patients’ electronic health records using transfer learning and ordinal regression

Data Science and Human Health

Incorporation of Multilevel Ontologies of Adverse Events and Vaccines for Vaccine Safety Surveillance

Data Science and Human Health

Large Scale Interventions for Reducing Threats to Safety and Trustworthiness on Social Media

Data Science and Human Endeavor, Data Science and Our Society

LEAP: Analytics for LEarners As People

Data Science and Human Endeavor

Markovian And Non-Markovian (Discrete) Spatio-Temporal Processes with Active Decision Making Strategies For Addressing The COVID-19 Pandemic

Data Science and Human Health

Michigan Center for Single-Cell Genomic Data Analytics

Data Science and Human Health

Michigan Integrated Center for Health Analytics & Medical Prediction (MiCHAMP)

Data Science and Human Health

Optimal Design of Data Assimilation for the Prediction of Hydrological Extremes

Data Science and the Physical World

Probabilistic Methods to Infer Structure and Dynamics of Illicit Wildlife Trade Networks

Data Science and Human Endeavor, Data Science and Our Habitat

Probabilistic Modeling of Missing Data to Improve Predictions Using Metabolomics Data

Data Science and Human Health

Regularized Regression and Poststratification: Blending Data Science and Survey Methodology to Increase the Reproducibility of Population Genetics Research

Data Science and Human Health

Reinventing Public Urban Transportation and Mobility

Data Science and Human Endeavor, Data Science and Our Habitat, Data Science and Our Society

Students’ mobility patterns on campus and the implications for the recovery of campus activities post-pandemic

Data Science and Human Health

The Sound of Text

Data Science and Human Endeavor

Towards a Framework for the Characterization of Cellular & Spatial Relationships in Development and Disease

Data Science and Human Health

Understanding and Mining Patterns of Audience Engagement and Creative Collaboration in Largescale Crowdsourced Music Performances

Data Science and Human Endeavor

Understanding How the Brain Processes Music through the Bach Trio Sonatas

Data Science and the Human Mind