Data Analytics
Data science research uses principles from computation, machine learning, statistics, and mathematics, to develop methods to analyze data and gain insight and knowledge about underlying systems to improve decision making. Data analytics is highly interdisciplinary with significant overlap with many areas, including human system integration, optimization, and stochastic systems.
This area includes:
Big Data Analytics: Techniques for analyzing large amounts of data to visualize patterns and discover the underlying principles governing the operational performance of industrial systems.
Predictive Analytics: Methods for predicting future outcomes, assessing and quantifying uncertainty about the future behavior of systems, and identifying the risk associated with decisions under varying environmental conditions.
Adaptive Learning: Fostering adaptive learning processes that use one or more sources of data collected over time to optimize dynamic decision-making and risk management.
RELATED NEWS
-
U-M IOE takes home awards from the INFORMS Annual Meeting
IOE faculty and students bring in awards from the 2023 Institute for Operations Research and the Management Sciences Annual Meeting.
-
Helping people get back to work using deep learning in the occupational health system
University of Michigan researchers have produced a new prediction model using longitudinal information and deep learning to better predict the return to work time for people with occupational injuries.
-
Preventing prescription dispensing errors using machine intelligence
In the United States over four billion prescriptions are dispensed every year. Of those four billion around 2.4 million are incorrectly dispensed, which can be a fatal error. A team of researchers from the University of Michigan looks to machine intelligence to help humans reduce their dispensing errors.
-
IOE Faculty Launch New Data Analytics Workshop
Inspired by the growing need for data analytics expertise, the Industrial and Operations Engineering (IOE) Department recently launched a course aimed at industry professionals.
-
Salar Fattahi introduces a new data analytics course for IOE
U-M IOE assistant professor, Salar Fattahi, teaches a new data analytics course that combines optimization techniques and data science with real-world case studies.
-
IOE undergraduates prep for a modern workforce with expanded data analytics courses and support
U-M IOE makes curriculum changes to enhance the data analytics and computing skills of its undergraduate students, including creating a new advanced analytics course for seniors.
-
Salar Fattahi joins the IOE faculty
Salar Fattahi joins the U-M IOE faculty as an assistant professor this fall.
-
Seth Guikema elected President of the Society for Risk Analysis
U-M IOE Associate Professor Seth Guikema has been elected President of the Society for Risk Analysis, an international community with over 2,000 members.
-
Mitigating uncertainties in remote computer numerical control using data-driven transfer learning
U-M IOE’s Raed Al Kontar receives research funding from Cyber-physical Systems, a National Science Foundation program, for a project centered on the refinement of computer numerical control as a cloud service.
-
Jon Lee selected for Centre de Recherches Mathématiques Scholar-in-Residence Program
U-M IOE’s Jon Lee, has been selected as a Simons CRM Professor by The Centre de Recherches Mathématiques (CRM).