A study of the world’s top researchers identifies 18 from the University of Maryland’s Robert H. Smith School of Business in the top 2% of the most-cited scholars and scientists worldwide. The study, published in the journal PLoS Biology, looks at 22 scientific fields and 176 subfields and ranks researchers for their career-long impact by the number of times their work is cited in other research. The research was led by Stanford University, based on data from Elsevier’s Scopus, an abstract and citation database of research publications.
Michael Fu has a joint appointment with the Institute for Systems Research and an affiliate appointment with the Department of Electrical and Computer Engineering, both in the A. James Clark School of Engineering. He was named a Distinguished Scholar-Teacher at the University of Maryland for 2004-2005. His research interests include simulation modeling and analysis, operations management, applied probability and queueing theory, with application to manufacturing and finance. He received an SB in mathematics and SB/SM in electrical engineering & computer science from MIT in 1985 and a PhD in applied mathematics from Harvard University in 1989.
In business to business transactions, each side has an incentive: Sell high or buy low. For sellers, knowing how the buyer will respond to an offer is difficult. But new research from Maryland Smith is helping to figure it out.
The Air Force Office of Scientific Research (AFOSR) recently awarded Maryland Smith professor Michael Fu a grant to continue his study of search methods for simulation-based optimization.
SMITH BRAIN TRUST – New modeling research by Maryland Smith’s Michael Fu and academic colleagues in China is helping decision makers better forecast the spread of the COVID-19 pandemic.
SMITH BRAIN TRUST – The coronavirus pandemic may have thrown many of your summer plans into disarray, but there's one much-loved activity you can still pursue: Losing yourself in a stack of engrossing books.
Maryland Smith's faculty are there for you, with suggestions to get you through the summer break.
Application of artificial intelligence (AI) machine learning techniques in industry and government for data-driven predictive analytics has been based primarily on statistical econometric models. However, one of the limitations of this approach is the “black-box” nature of the resulting models, which frequently result in a lack of interpretability.
New research from Maryland Smith’s Michael C. Fu offers a rigorous way to analyze statistics generated from simulation models.
The new result fills a gap in probabilistic simulation modeling and analysis. Fu, the Smith Chair of Management Science in the Decision, Operations and Information Technologies department at the University of Maryland’s Robert H. Smith School of Business, worked with four co-authors, two at Stanford University and two in China at Fudan University and Peking University.
Estimating Sensitivities in the Simulation of Complex Systems
Numbers can be a tricky business.
Michael C. Fu, the Smith Chair of Management Science and chair of the Decision, Operations and Information Technologies Department at the University of Maryland’s Robert H. Smith School of Business, understands just how tricky they can be.
The University of Maryland’s Robert H. Smith School of Business is excited to announce some favorite books in the 14th Annual Top-10 Summer Reading List for Business Leaders for 2017, as recommended by faculty members.
A computer created by Google engineers knocked off one of the world's greatest human players of the Chinese game Go this week — a landmark in the development of artificial intelligence. In doing so, it made use of an approach to the computerized analysis of decision-making first developed at the Smith School (and Maryland's engineering school).