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Systems Science Seminar Series

SUMMARY: The Systems Science Seminar Series covers a wide-range of topics, providing an opportunity for presenters to share and attendees to become exposed to latest and often cutting-edge research from different fields and disciplines. Agent-based simulation, artificial intelligence, artificial life, genetic algorithms, machine learning, neural networks, signal processing, social networks, system dynamics, and science itself are just a few of the many diverse topics that have been presented, all in an informal environment where questions and discussion are encouraged. The Seminar Syllabus is also available here.

QUESTIONS AND COMMENTS: If you have questions or comments, would like to present a seminar, or if you have suggestions for topics or speakers, please email Andey Nunes at

SEMINAR ANNOUNCEMENT LISTSERVE: to receive seminar announcements email  We'll soon be setting up a Google Group for this.

Past seminar links and records can be found on our Seminar Archive page


Winter 2016 Schedule

  • 1/8/16 -- John G Anasis, PhD Systems Science, "A Combined Energy and Geoengineering Optimization Model (CEAGOM) for Climate Policy Analysis" [Announcment] [Recording] Model Files: [CEAGOM Users Guide] [Concentration Limit] [Unrecoverd Cost Template] [Cumulative Emissions Limit] [Emissions Limit] [No Climate Limits] [Temperature Limit] [Dissertation]
  • 1/15/16 -- Barry Oken, PhD Neurologist OHSU and PhD Systems Science candidate, "Stress Physiology in Humans: a Systems Approach to Stress, Stressors, and Resilience." [Announcement] [Recording]
  • 1/22/16 -- Patrick Leyshock, PhD Senior Research Associate, Computational Biology, OHSU, "Computational Biology and T-cell Receptor Sequencing" [Announcement] [Recording]
  • 1/29/16 -- Vivek Shandas, PhD Associate Professor Urban Studies and Planning at PSU, "Analytics for Characterizing Urban Heat Islands in Data Rich and Poor Locations" [Announcement] [Recording]
  • 2/5/16 -- Antonie Jetter, PhD Associate Professor Engineering and Technology Management at PSU, "Fuzzy Cognitive Maps for Collaborative Modeling: An introduction" [Announcement] [Recording]
  • 2/12/16 -- Andey Nunes, PSU Systems Science masters student, "Facilitated discussion on systems science in public health" [Announcement] [Recording]
  • 2/19/16 -- Janne Boone-Heinonen, PhD, MPH and Lynne C Messer, PhD, MPH PSU School of Community Health, Center for Public Health Studies, Developmental Origins of Health and Disease (DOHaD), "Mitigating fetal programming of chronic disease: conceptual framework, initial evidence, and methodological challenges" [Announcement] [Recording
  • 2/26/16 -- Diana Fisher, PSU Systems Science Program PhD candidate, " Do Student-Built System Dynamics Models Help Students Better Differentiate Between Linear and Exponential Behavior Over Time? Results of a Short Experiment." [Announcement]
  • 3/4/16 -- David Maier, Professor Computer Science PSU Maseeh College of Engineering and Computer Science [Announcement]
  • 3/11/16 -- Jonathan Strauss, PSU Systems Science Program [Announcement]


DATE: Friday, January 8, 2015, 12:00 - 1:00 PM

LOCATION: Harder House, Room 104

PRESENTER: John G. Anasis

PRESENTATION TITLE: A Combined Energy and Geoengineering Optimization Model (CEAGOM) for Climate Policy Analysis

SUMMARY: One of the greatest challenges that will face humanity in the 21st century is the issue of climate change brought about by emissions of greenhouse gases. Energy use is one of the primary sources of greenhouse gas emissions. However, it is also one of the most important contributors to improved human welfare over the past two centuries and will continue to be so for years to come. This quandary has led a number of researchers to suggest that geoengineering may be required in order to allow for continued use of fossil fuels while at the same time mitigating the effects of the associated greenhouse gas emissions on the global climate. The goal of this research was to develop a model that would allow decision-makers and policy analysts to assess the optimal mix of energy and geoengineering resources needed to meet global or regional energy demand at the lowest cost while accounting for appropriate emissions, greenhouse gas concentration, or temperature rise constraints. The resulting software model is called the Combined Energy and Geoengineering Optimization Model (CEAGOM). CEAGOM was then used to analyze the recently announced U.S.-China emissions agreement and to assess what the optimal global energy resource mix might be over the course of the 21st century, including the associated potential need for geoengineering. These analyses yielded optimal mixes of energy and geoengineering resources that could be used to inform regional and global energy and climate management strategies.

BIO: John Anasis just completed his Ph.d in Systems Science at Portland State in fall term, 2015.  He also holds a bachelor’s degree in electrical engineering with a minor in physics from the University of Portland and a master’s degree in public administration from Portland State.  John has been an electrical engineer in the electrical utility industry for over 30 years with extensive experience in the operation of large high-voltage power grids and policy issues related to the transmission of electric power.   In addition to his experience in the power industry, John has a strong interest in climate science, physics, cyber security, and the relationships between science, technology, and religion.   John comes from a large extended family and is an active member of Holy Trinity Greek Orthodox Cathedral in Portland.



DATE: Friday, January 15, 2016, 12:00 - 1:00 PM

LOCATION: Harder House, Room 104


PRESENTATION TITLE: Stress Physiology in Humans: a Systems Approach to Stress, Stressors, and Resilience.

SUMMARY: This talk focuses on the biology of stress and resilience and their biomarkers in humans from the system science perspective. A stressor pushes the physiological system away from its baseline state towards a lower utility state. The physiological system may return towards the original state in one attractor basin but may be shifted to a state in another, lower utility attractor basin. While some physiological changes induced by stressors may benefit health, there is often a chronic wear and tear cost due to implementing changes to enable the return of the system to its baseline state and maintain itself in the high utility baseline attractor basin following repeated perturbations. This cost, also called allostatic load, is the utility reduction associated with both a change in state and with alterations in the attractor basin that affect system responses following future perturbations. This added cost can increase the time course of the return to baseline or the likelihood of moving into a different attractor basin following a perturbation. Opposite to this is the system’s resilience which influences its ability to return to the high utility attractor basin following a perturbation by increasing the likelihood and/or speed of returning to the baseline state following a stressor. The talk will emphasize topics most relevant to moving the stress and resilience field forward from a more quantitative and perspective. 

BIO: Dr. Oken has been a neurologist and researcher in the human neurophysiology, behavioral neurology and cognitive neuroscience fields for 30 years. Mind-body medicine with its impact on the stress system has been a research focus for the last 15 years. He has been interested in the effects of chronic psychological stress on biomarkers of stress and resilience in part to evaluate improvements from mind-body medicine interventions. He also directs an NCCIH T32, providing funding since 2005 of 30 post-doctoral fellows with an interest in a career in academic complementary medicine. His strong skills in quantitative analysis of physiological data were enhanced by his recent graduate coursework facilitated by the recently completed NIH-NCCIH K24 award “Advancing physiological signal analysis for mind-body research”. The coursework and related comprehensive examination resulted in a Master of Science in Systems Science and a scheduled PhD dissertation defense on February 19, 2016. 



DATE: Friday, January 22, 2016, 12:00 - 1:00 PM

LOCATION: Harder House, Room 104

PRESENTER: Patrick Leyshock

PRESENTATION TITLE: Computational Biology and T-Cell Receptor Sequencing

SUMMARY: Leyshock will begin with an overview of Computational Biology work at OHSU, then take a closer look at T­cell sequencing pipeline under development. The pipeline itself will be discussed, as well as its implications for cancer immunotherapies.

BIO: Dr. Leyshock is a Research Systems Engineer for the Computational Biology Program, leading data integration projects for several OHSU labs. Leyshock's analytic skills and diverse work experience make him a valuable asset to the Program. A Reed College graduate, Leyshock has earned both an M.A. from Arizona State University and a PhD in Computer Science from Portland State University. His doctoral dissertation research focused on tools and methods for analyzing array­structured scientific data.



DATE: Friday, Month day, 2016, 12:00 - 1:00 PM

LOCATION: Harder House, Room 104

PRESENTER: Vivek Shandas; Jackson Voelkel

PRESENTATION TITLE: "Ensemble Data Analysis for Assessing Urban Heat Islands in Data Rich and Poor Environments."

SUMMARY: With ever-increasing populations in urban areas, and major changes to our climate system, a public health imperative is to prepare for dangerous weather events in cities. Extreme weather events, such as heat waves, impact the most vulnerable human populations, and are known to kill more urban dwellers than any other natural disaster. If public health agencies are to prevent excess mortality and morbidity, then identifying those areas and communities most prone to heat stress can provide guidance for timely interventions. Yet we still lack a systematic approach for identifying specific locations where extreme weather events might have profound and fatal impacts on human populations. In two case studies exemplifying data-rich and data-poor regions we aim to created predictive urban heat island (UHI) models. We achieve this with land-use GIS data, Random Forest modeling, and vehicle-mounted GPS-tagged temperature observations. Our models suggest that morning, afternoon, and evening heat distributions have different variables which help to explain the variation in temperatures.

BIO: Vivek Shandas has an interdisciplinary training that spans the social and biophysical sciences. His research interests focus on understanding the dynamics of socio-ecological systems specifically in cities. Through projects that examine multiple spatial and temporal scales, he aim to characterize, monitor, and model the interactions between humans and the environment. By using qualitative, quantitative, and mixed-methods, the outcomes of his research aims to engage communities in identifying feedbacks among human behavior, environmental change, and human health and well-being. Notable areas of research include, water use behavior among urban residents, urban vegetation and human health, urban ecosystem services, and participatory mapping.

Jackson Voelkel is a Geospatial Research Analyst at the Sustaining Urban Places Research (SUPR) Lab. One of his main focuses is creating land and urban canopy descriptors from lidar data and developing methodologies for integrating them with planning and sustainability research. He also focuses on the automation of complex workflows, streamlining of bulky processes to ease computational burdens across multiple users, and cartography among an assortment of other geospatial research topics.



DATE: Friday, February 5, 2016, 12:00 - 1:00 PM

LOCATION: Harder House, Room 104

PRESENTER: Antonie Jetter

PRESENTATION TITLE: Fuzzy Cognitive Maps for Collaborative Modeling: An introduction

SUMMARY: Fuzzy Cognitive Map Modeling is a system modeling approach that has its roots in social science and artificial intelligence. FCM are comparatively easy to create, are well understood by audiences with limited modeling expertise, and are easy to update to reflect the insights of additional model contributors. Accordingly, FCM modeling is gaining popularity in ecological modeling and collaborative planning. The talk will introduce fundamentals and illustrate the use of FCM with several examples from ongoing research projects.

BIO: Antonie Jetter is an Associate Professor of Engineering & Technology Management at Portland State University.  She teaches courses on new product development, entrepreneurship, and technology marketing to graduate students in engineering. Her research is focused on new product development, managerial cognition, and decision making and leads to insights and methods for managing the early stages of product innovation. In her dissertation, Antonie has pioneered the use of Fuzzy Cognitive Map as a product planning tool. Ongoing research uses Fuzzy Cognitive Maps to model community risk perceptions, drivers of technology acceptance among elderly patients and their caregivers, and differences in the mental models of product development engineers and product users. Antonie holds an MBA (1998) and a Ph.D. in Technology and Innovation Management (2006) from RWTH Aachen University, Germany and has seven years of industry experience in a large technology firm and a high/tech start up.



DATE: Friday, February 12, 2016, 12:00 - 1:00 PM

LOCATION: Harder House, Room 104

PRESENTER: Andey Nunes

PRESENTATION TITLE: Systems Science Seminar Discussion Topic: Public Health

SUMMARY: Andey will lead a discussion of the Carey, et al. 2015 paper titled, “Systems science and systems thinking for public health: a systematic review of the field.” (Citation: Carey G, Malbon E, Carey N, et al. Systems science and systems thinking for public health: a systematic review of the field. BMJ Open 2015;5:e009002. doi:10.1136/bmjopen-2015-009002)

The intention is to highlight the authors’ findings and spark some lively conversation. users can access the paper at:

BIO: Andey Nunes is a second year Masters student in the Systems Science Program. He is currently pursuing graduate certificate programs in Applied Statistics and Environmental & Resource Economics. Andey holds a Bachelor of Science in Environmental Studies:Earth Systems Science (emphasis in chemical analysis) from San Francisco State University (2012). His research areas of interest include: industrial ecology, ecosystems services, ecological economics, labor history, and cultures of resistance.



DATE: Friday, February 19, 2016, 12:00 - 1:00 PM

LOCATION: Harder House, Room 104

PRESENTER: Janne Boone-Heinonen, PhD, MPH and Lynne C Messer, PhD, MPH

PRESENTATION TITLE: Mitigating fetal programming of chronic disease: conceptual framework, initial evidence, and methodological challenges

SUMMARY: In this seminar, Drs. Boone-Heinonen and Messer will discuss how prenatal development can “program” susceptibility to disease later in life. They will focus on how contextual and behavioral factors can potentially mitigate the long-term effects of adverse fetal programming. They will highlight methodological challenges related to the complexity of this emerging area of investigation. The seminar will close with an interactive discussion about the role of systems science in studying fetal programing mitigation.

BIO: Dr. Boone-Heinonen’s research investigates early life, behavioral, and environmental determinants of diet, physical activity, and obesity throughout the life course. Dr. Messer is a reproductive/perinatal, social and environmental epidemiologist whose work focuses on the social-environmental causes of persistent health disparities. Both Drs. Boone-Heinonen and Messer use interdisciplinary statistical methods with large population-based cohorts to address methodological challenges in obesity and reproductive epidemiology.



DATE: Friday, February 26, 2016, 12:00 - 1:00 PM

LOCATION: Harder House, Room 104

PRESENTER: Diana Fisher

PRESENTATION TITLE: Do Student-Built System Dynamics Models Help Students Better Differentiate Between Linear and Exponential Behavior Over Time? Results of a Short Experiment

SUMMARY: A classroom experiment involving two teachers and four classes (two experimental and two control) of algebra II students at a local high school was performed to determine whether having students build System Dynamics models of linear and exponential scenarios strengthened their understanding of the difference between the growth/decay patterns of these two function types.  Differentiating linear and exponential scenarios seems very basic, yet many high school students do not understand the difference sufficiently, even after weeks of traditional mathematics lessons involving both function types.  

BIO:  Ms. Fisher is a PhD candidate in System Science at PSU.  She is the recipient of the Lifetime Achievement award, bestowed by the International System Dynamics Society, the Presidential Award for Excellence in Teaching, and first place recipient of Intel's Innovation in Teaching Award.   She has taught System Dynamics (SD) modeling, both as part of her algebra, pre-calculus, and calculus classes, and also a year-long SD modeling course for over 20 years.  She has provided system dynamics modeling workshops for math and science teachers, sponsored by NASA, as well as designing and directing two National Science Foundation Projects where she taught SD modeling lessons for math, science, and social science teachers, serving as the lead Principal Investigator.  She has published two books in System Dynamics: Lessons in Mathematics: A Dynamic Approach and Modeling Dynamic Systems: Lessons for a First Course. Her first two degrees are in Mathematics.   She offers a sequence of three online SD modeling courses (with graduate credit option) each summer:  Introduction to System Dynamics Modeling for Math and Science Instructors: Basic Models,  More Advanced Models, Creating Original Models from the News.




DATE: Friday, March 4, 2016, 12:00 - 1:00 PM

LOCATION: Harder House, Room 104

PRESENTER: Professor David Maier, Maseeh Professor of Emerging Technologies, Portland State University

PRESENTATION TITLE: Helping Scientists Connect Their Datasets

SUMMARY: Scientific datasets associated with a research project can proliferate over time as a result of activities such as sharing datasets among collaborators, extending existing ones with new measurements, and extracting subsets of data for analysis. As such datasets begin to accumulate, it becomes increasingly difficult for a scientist to keep track of their derivation history, which complicates data sharing, provenance tracking, and scientific reproducibility. Understanding what relationships exist between datasets can help scientists recall their original derivation history. For instance, if dataset A is contained in dataset B, then the connection between A and B could be that A was extended to create B.  In our initial work, we developed a set of relevant relationships, proposed the relationship-identification methodology for testing relationships between pairs of datasets, developed a set of algorithms for efficient discovery of these relationships, and organized these algorithms into a new system called ReConnect to assist scientists in relationship discovery. We evaluated existing alternative approaches that rely on flagging differences between two spreadsheets and found that they were impractical for many relationship-discovery tasks. Additionally, a user study showed that ReConnect can improve scientists' ability to detect useful relationships between datasets.  While ReConnect helps with identifying relationships between two datasets, it is infeasible for scientists to use it for determining relationships between all possible pairs in a large collection. In this talk, we introduce an end-to-end prototype system, ReDiscover, that identifies, from a collection of datasets, the pairs that are most likely related. Our preliminarily evaluation shows that ReDiscover can predict selected relationships with high precision and within reasonable computational cost.

BIO: David Maier is Maseeh Professor of Emerging Technologies at Portland State University. Prior to his current position, he was on the faculty at SUNY Stony Brook and Oregon Graduate Institute. He has spent extended visits with INRIA, University of Wisconsin at Madison, Microsoft Research and National University of Singapore. He is the author of books on relational databases, logic programming and object-oriented databases, as well as many papers in database theory, object-oriented technology, scientific databases and data-stream processing. He received the Presidential Young Investigator Award from the National Science Foundation in 1984 and was awarded the 1997 SIGMOD Innovations Award for his contributions in objects and databases. He is also an ACM Fellow and IEEE Senior Member and serves on the Board on Mathematical Sciences and Their Applications at The National Academies. He holds a dual B.A. in Mathematics and in Computer Science from the University of Oregon (Honors Col lege, 1974) and a Ph.D. in Electrical Engineering and Computer Science from Princeton University (1978).



DATE: Friday, March 11, 2016, 12:00 - 1:00 PM

LOCATION: Harder House, Room 104

PRESENTER: Jonathan Straus

PRESENTATION TITLE: Toward an Information-Age Paradigm for Integrating Research, Publication and Theory Development in the Social Sciences?

SUMMARY: The application of the scientific method to social psychology and related disciplines has long been rife with controversies, and recent failures to replicate many of the results from classical psychology experiments prompt continued doubts about the general validity of social scientific theories. I present a framework that attempts to reconcile the interdependent (but often antagonistic) relations between reliability and validity in individual empirical studies, iterative verification and validation of inherently multi-level social phenomena, and how such necessary synergies are suppressed under the current paradigm of research and publishing. Along this vein, we explore some tentative solutions informed by the successes of contemporary knowledge-building projects (including the crowd-sourcing of certain data collection procedures, modular networked ‘wiki’-like pages of related theories and studies, and indexing of experimental replications) that may be incorporated in sensible measures by both small and large publishing institutions.

BIO: Jonathan Straus is a Master’s Student in the Systems Science Program. He has dabbled in psychology, with a particularly keen interest in experimental social psychology and (more generally) modeling and epistemology in the social sciences



(past seminar links and records can be found on our Seminar Archive page)