Category: Optimization
-
Berahas Receives ONR Grant to Develop Advanced Optimization Algorithms
The grant will fund the development of cutting-edge algorithms for solving complex nonlinear constrained stochastic optimization problems. Albert Berahas, and Micheal O’Neill will lead the research to advance optimization methods and address real-world challenges.
-
Viswanath Nagarajan Awarded NSF Grant
The awarded project focuses on developing advanced algorithms for stochastic optimization, tackling a fundamental challenge in algorithm design: uncertainty in input parameters.
-
University of Michigan Hosts Optimaize Day to Spark Interest in Engineering Among Detroit High School Students
In partnership with the Detroit Educational Takeover Team, Optimaize Day bridges theoretical understanding of engineering with everyday applications, leaving a lasting impression on the minds of potential future engineers.
-
New statistical tool to distinguish shared and unique features in data from different sources
Personalized PCA method overcomes the challenges of heterogeneous data analysis
-
Salar Fattahi receives NSF CAREER Award for work in nonconvex problems in machine learning
Salar Fattahi discusses his award-winning CAREER proposal which aims to close the current gap between optimization and statistical learning.
-
Standardizing bilevel optimization for future researchers and practitioners
Bilevel optimization is used not only in research, but also in business to identify the best solutions for a variety of hierarchical problems. A U-M researcher aims to develop a comprehensive software package that will enable many industries to use this in everyday decision-making.
-
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.
-
U-M Industrial and Operations Engineering wins several awards at the 2022 INFORMS Annual Meeting
The Institute for Operations Research and the Management Sciences (INFORMS) annual meeting has officially wrapped up with the University of Michigan Industrial and Operations Engineering (U-M IOE) Department walking away with several awards.
-
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.
-
Dr. Salar Fattahi receives a research grant from the Office of Naval Research
University of Michigan Industrial and Operations Engineering (U-M IOE) Assistant Professor, Dr. Salar Fattahi has been awarded $430,556 from the Office of Naval Research (ONR) for scientific research regarding low-rank matrix factorization.
-
Brian Denton appointed Stephen M. Pollock Collegiate Professor of Industrial and Operations Engineering
Brian Denton has been appointed the Stephen M. Pollock Collegiate Professor of Industrial and Operations Engineering, named in honor of Stephen M. Pollock, a professor emeritus and former chair of U-M IOE.
-
Kati Moug receives 2021 Generation Google Scholarship
U-M IOE PhD student, Kati Moug, has received a 2021 Generation Google Scholarship in recognition of academic performance, leadership, and a commitment to diversity, equity and inclusion.
-
Siqian Shen receives NSF funding for transportation system redesign
U-M IOE associate professor, Siqian Shen, has received funding from the National Science Foundation (NSF) for research on redesigning transportation for a post-pandemic world.
-
Jessie Yang and Cong Shi win second place in NATO Innovation Challenge
U-M IOE faculty have been awarded second place at the NATO Innovation Challenge for their presented solution that integrates optimization and human factors for autonomous decision making.
-
Albert Berahas joins the IOE faculty
Albert Berahas joins the U-M IOE faculty as an assistant professor this fall.
-
The science behind campus bus changes during COVID-19
Engineers used smoke machines, physics-based modeling and route optimization algorithms to quantify risk.