Dr. Seth Guikema

Dr. Seth Guikema is an Associate Professor in the Department of Industrial and Operations Engineering and the Department of Civil and Environmental Engineering at the University of Michigan as of August 2015. Prior to this, he was an Associate Professor in the Department of Geography and Environmental Engineering (DoGEE) at Johns Hopkins University. He is also an adjunct Professor II in the Department of Industrial Economics, Risk Management, and Planning at the University of Stavanger in Norway, and is a Senior Analyst with Innovative Decisions, Inc. in Vienna, VA.

His academic training includes a B.S. in Civil & Environmental Engineering (Cornell University), a M.S. in Civil & Environmental Engineering (Stanford University), a M.E. by thesis in Civil Engineering (University of Canterbury in New Zealand), a Ph.D. in Management Science & Engineering with a concentration in Engineering Risk & Decision Analysis (Stanford University), and a postdoctoral research position in Civil & Environmental Engineering (Cornell University). He began his faculty career at Texas A&M University in Civil Engineering and moved to DoGEE at JHU in 2008. He received tenure at JHU in 2014 and became the Carol Linde Croft Faculty Scholar there in 2015. He moved to the University of Michigan in August 2015. Seth is currently the Area Editor for Mathematical Modeling in the journal Risk Analysis, an Associate Editor for the ASCE Journal of Infrastructure Systems and is on the editorial boards of the journals Reliability Engineering and System Safety and Performability Engineering. He recently completed a three-year terms on the governing Councils of the International Society for Risk Analysis and the INFORMS Decision Analysis Society.

Dr. Guikema's research is highly interdisciplinary. Much of his group's recent work is focused on the problems of urban and infrastructure resilience and sustainability in a changing climate, though areas of application are broad. It is grounded in risk analysis, particularly data-drive risk analysis and complex systems simulation. One major topic is developing, testing, and implementing risk analysis methods based in Bayesian probability, statistical learning theory, game theory, and decision analysis. Another growing research thrust in the group is using modern simulation methods to more fully understand the role of human behavior in the evoluation of vulnerabiltiy and risk in hazard-prone regions. This work is a combination of theory and practice, spanning from new methods development, testing, and validation to close interactions with utilities to develop and implement new methods for estimating performance and risk to infrastructure systems from disasters.

Kristen Schell Profile Page

Currently a Postdoctoral Research Fellow in the Industrial and Operations Engineering Department at the University of Michigan, my research focuses on predictive and optimization modeling to support renewable energy integration into the power system, and to ensure energy system resilience under a changing climate. Recent projects include risk characterization and predictive modeling of spatially and temporally correlated wind droughts across the United States. This work seeks to inform wind farm siting, power grid resource adequacy and reliability, as well as incentive policy formation. Future research will use these predictive models to assess how wind power forecasting errors affect power system operations, as well as electricty and ancillary markets.

Sara Shashaani Profile Page

Sara Shashaani is a post-doctoral research fellow in the Guikema research group, within the department of Industrial and Operations Engineering at the University of Michigan. Sara received her Ph.D. from the school of Industrial Engineering at Purdue University in Fall of 2016. Her research interests include devising theory and algorithms for simulation optimization problems, where the objective function is noisy and unknown, and derivative-free optimization problems, where no structure about the underlying function is known or available even with noise.

Matt Hamilton Profile Page

Matt’s post-doc research focuses on understanding human adaptation to climate change in fire-prone ecosystems. His main project is a collaboration involving Dr. Guikema as well as Dr. Paige Fischer (School of Natural Resources and Environment) and Dr. Gretchen Keppel-Aleks (Department of Atmospheric, Oceanic, and Space Sciences). Matt came to the University of Michigan from the University of California-Davis, where he completed a PhD in Ecology with Dr. Mark Lubell. His doctoral research focused on how stakeholder networks address cooperation challenges in climate change adaptation governance in the Lake Victoria region, East Africa. He also holds a MS in International Agricultural Development, also from the University of California-Davis. Matt’s research uses network analysis, spatial modeling, surveys, interviews, and participatory data collection methodologies.

Tom Logan Profile Page

Tom's research integrates statistics, operations, risk analysis, and urban planning. He apply mathematical modeling to improve our understanding and planning of cities facing an uncertain future. Currently he is working on understanding the temporal evolution of cities and their multiple risks from natural disaster, in a way which allows for planning optimisation or strategy selection under deep uncertainty.

Elnaz Kabir Profile Page

Elnaz’s research interests are in the usage and creation of online and offline data-driven methods to make better predictions. Her research is mainly focused on developing statistical methods for learning from imbalanced data sets. She is currently working on two projects including tree risk assessment during storms and modeling the weather related power outages. In addition to her PhD in Industrial and Operations Engineering, Elnaz is partaking in the dual master’s program offered by the Department of Statistics at the University of Michigan.

Thomas Chen Profile Page

Thomas Chen is a doctoral student in the Industrial and Operations Engineering Department at the University of Michigan. His research interests are exploring analytical decision support tools to better manage critical infrastructure systems. Such methods include, but are not limited to: statistical learning theory, bayesian data analysis, and mathematical optimization. His on-going research involves using these tools to assess risk levels in drinking water distribution systems and formulate better maintenance/replacement programs.

Tim Williams Profile Page

Tim's goal is to further understanding of human-natural systems - their dynamics, their vulnerabilities, and how we as humans can influence them in ways that enhance both the betterment of society and the prosperity of the environment. His research focuses on modelling the interplay between food security and food, energy, and water systems, with a focus in Ethiopia. He is building an agent-based model to explore the effect of household-level decision making and exogenous intervention strategies on these outcomes. Other work involves developing quantitative methods for categorizing urban form. Here the focus is on major US cities and the potential inequities that may exist between different socio-economic and demographic groups. Tim aspires to conduct research that can be ultimately applied by decision makers to inform long-term planning, policy decisions, and behavior change.

Chengwei Zhai Profile Page

Chengwei Zhai is currently a Ph.D. student in the Department of Industrial and Operations Engineering at the University of Michigan. He received his B.S. degree in electrical engineering at Zhejiang University and the M.S.E degree in Industrial and Operations Research department at the University of Michigan. His research interests include risk analysis, decision analysis, machine learning, and massive behavioral simulation.

Valerie Washington Profile Page

Valerie is enrolled in the University of Michigan's Industrial and Operations Engineering PhD program. Her research interests include the application of optimization, simulation, and risk analysis to climate resilience and sustainable development.

Anna White Profile Page

Anna is entering the PhD program in Industrial and Operations Engineering at the University of Michigan after completing her undergraduate studies at Clemson University. Her research goals are to use mathematical modeling to shape climate change policy and sustainable investment decisions. She is interested in urban and critical infrastructure planning, specifically in public transportation, as well as risk analysis and response for natural and human-initiated disasters.


Department of Industrial and Operations Engineering
University of Michigan, 1205 Beal Ave.
Ann Arbor, MI 48109

Guikema Research Group
2015