Tag: Raed Al Kontar
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Engineering a smarter game for Michigan’s soccer teams
A unique collaboration between the University of Michigan College of Engineering and its soccer teams is transforming the game, one data-driven decision at a time.
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Raed Al Kontar receives promotion to associate professor with tenure
Since joining the U-M IOE department he has developed and taught data analytics courses that impact students and secured $1.75 million in research funding.
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New statistical tool to distinguish shared and unique features in data from different sources
Personalized PCA method overcomes the challenges of heterogeneous data analysis
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Michigan Engineering Professors to develop novel federated learning algorithms for distributed 3D printing
Kontar and Okwudire have received a grant from Cisco Systems Inc. to develop novel federated learning algorithms that address descriptive, predictive and prescriptive machine learning opportunities in large-scale distributed 3D printing.
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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.
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Raed Al Kontar receives the National Science Foundation Career Award
This award is given by the National Science Foundation through their Faculty Early Career Development (CAREER) Program. As one of the most prestigious awards, it supports early-career faculty who have the potential to serve as academic role models in research and education and to advance the mission of their department.
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Keeping the world connected, without sacrificing privacy
Engineering assistant professor Raed Al Kontar outlines a new paradigm for connected devices.
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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.