Publications Database

Welcome to the new Schulich Peer-Reviewed Publication Database!

The database is currently in beta-testing and will be updated with more features as time goes on. In the meantime, stakeholders are free to explore our faculty’s numerous works. The left-hand panel affords the ability to search by the following:

  • Faculty Member’s Name;
  • Area of Expertise;
  • Whether the Publication is Open-Access (free for public download);
  • Journal Name; and
  • Date Range.

At present, the database covers publications from 2012 to 2020, but will extend further back in the future. In addition to listing publications, the database includes two types of impact metrics: Altmetrics and Plum. The database will be updated annually with most recent publications from our faculty.

If you have any questions or input, please don’t hesitate to get in touch.

 

Search Results

with M. Kozlova, R. Moss, J. Caers (2024). "Uncovering Heterogeneous Effects in Computational Models for Sustainable Decision-Making", Environmental Modelling and Software, 171, 105898.

Open Access Download

Keywords
Abstract Computational modeling is frequently incorporated into environmental decision-making in order to capture inherently complex relationships and system dynamics. The complexity of such models often lies in various heterogeneous effects that arise due to the interaction of different input factors or due to designed structural variation in the model. In the past, various sensitivity analysis approaches have been implemented in attempts to identify essential decision factors. However, existing sensitivity analysis methods fail to capture critical information in the presence of heterogeneous effects. In this paper, the recently introduced simulation decomposition (SimDec) visualization method is extended to include quantitative sensitivity analysis. The framework is tested on several decision-making problems and is shown to capture heterogeneous behavior. A formal definition and classification of heterogeneous effects for computational models is introduced. The framework is open-sourced in a variety of scientific programming languages.

with A. Alam, M. Kozlova, L. Leifsson (2023). "The Importance of Intelligent Colouring for Simulation Decomposition in Environmental Analysis", Journal of Environmental Informatics Letters , 10, 2, 63-73.

Open Access Download

Keywords
Abstract “Real world” risk analysis in environmental contexts frequently requires the need to contrast numerous uncertain factors simultaneously and to communicate difficult-to-capture interactions. Monte Carlo simulation modelling of complex environmental sytems is frequently employed to integrate uncertain inputs and to construct probability distributions of the resulting outputs. Visual analytics and data visualization can then be employed for the processing, analyzing, and communicating of the influence of any multi-variable uncertainties on the system. The simulation decomposition (SimDec) analytical technique has recently been employed in the complex assessments of environmental systems. SimDec has proved to be beneficial in revealing interdependencies in complex models, lowering computational burdens, facilitating decision-maker perceptions, and especially, making analytical components visualizable. It has been demonstrated that many analytical findings would not have been revealed without the coloured visualizations provided by SimDec. However, an ad hoc colouring scheme of the distribution output is neither sufficient nor capable of producing much of the key visualizable information requisite for an effective SimDec analysis. Instead, an approach that has recently been referred to as an intelligent colouring has been proposed. This paper outlines, highlights, and demonstrates the importance of and best-practices in an intelligent colouring scheme needed for an effective SimDec analysis of complex environmental systems.