Past Research Spotlights
|September- December, 2010||
Modelling of Complex Social Systems (MoCSSy) ProgramThe unifying theme of this project is the modelling of the complex dynamics that drive the linked epidemiologies of crime, disease, homelessness and other social ills in urban neighborhoods. The program brings together an interdisciplinary research group of academics, practitioners, and service providers that have a proven track record of success. The MoCSSy Program is funded by SFU Community Trust Endowment Fund and is housed at the IRMACS Centre. Two main goals of this novel, interdisciplinary program are: - to generate a modelling and visualization tool set that is applied to elevate the knowledge and understanding of urban complex systems at an unprecedented level, and - to develop a new generation of researchers who understand and address problems related to the complex dynamics of urban systems through computational and mathematical modelling. Among the current research projects in the MoCCSy Program here we mention "Co-offending Networks Analysis". In this project a group of researchers from the SFU School of Computing Science, the SFU Department of Criminology, and the IRMACS Centre have been building a method on how to infer the co-offending network from large scale real world crime event data. For more details about this project and for the full list of current and past MoCSSy research projects and their descriptions see mocssy.irmacs.sfu.ca/research. The MoCSSy's Graduate Certificate Program offers a unique opportunity for graduate students to apply their interdisciplinary knowledge to research, in an environment that is second to none in Canada - the IRMACS Centre. As a member of the IRMACS Modelling Consortium, the MoCSSy Program, together with other research groups from the Consortium, is aiming to significantly contribute to the accomplishment of the following objectives stated in SFU's "Academic Vision, Outcomes and VPA Goals for 2013": Seek for opportunities for interdisciplinary and multidisciplinary teaching and research; Support opportunities for new and interdisciplinary program development; and * Establish support mechanisms/structures to promote interdisciplinarity in teaching and research.
About the Project Leader: Dr. Vahid Dabbaghian has been the Director of the MoCSSy Program since June 2009. He completed his Ph.D. thesis on computation of representations of finite groups in 2003 at Carlton University under the supervision of Dr. John D. Dixon. Dr. Dabbaghian divides his research interests between the field of Computational Algebra and the field of Mathematical Modelling. He has published multiple scientific papers and technical reports. Dr. Dabbaghian is a co-author of the book "Modelling in Healthcare" published by the American Mathematical Society in 2010.
|June - August, 2010||
Boolean Function Generation for Complex Systems
This project is about algorithms for generating the minimal operating and failure modes of a complex system controlled by many boolean (true-false) variables. This is a fundamental algorithmic question that has unexpected theoretical properties and is poorly understood computationally. However, these "boolean functions" arise naturally in models of complex systems, notably in computational biology. Complex systems are often controlled by many boolean (binary) variables, whose values are either "true" or "false". We would like to characterize how these variables affect a particular behaviour of the system, which itself is boolean. Suppose the behaviour is monotone in the sense that, given a setting of the variables that permits the behaviour, if additional variables are set to "true" the behaviour is still permitted. Then this behaviour is a monotone boolean function of the variables. Such a function is characterized uniquely by both the minimal sets of variables permitting the behaviour and the minimal sets of variables inhibiting the behaviour. This situation is common in complex systems, such as those that comprise computational biology. As an example, a metabolic network can be characterized in its metabolites and reactions. In a steady state many of these reactions operate simultaneously. When some of these reactions are knocked out, various behaviours of the system will be blocked. We then have a boolean function which can be described either through elementary modes, i.e. minimal sets of reactions supporting the behaviour, or minimal cut sets blocking the behaviour. The goal of the project is to develop efficient algorithms to enumerate these minimal sets, and to understand them both theoretically and computationally. The project is motivated in part by the novel algorithm of Fredman and Khachiyan which generates these forms with a surprisingly good worst-case complexity, but is not well understood in practice. These ideas also have an interesting connection to fundamental questions in computational geometry on describing polyhedra.
About the Project Leader: Dr. Tamon Stephen is an assistant professor in the Department of Mathematics of Simon Fraser University. He completed his Ph.D. thesis "The Distribution of Values in Combinatorial Optimization Problems" under the direction of Alexander Barvinok at the University of Mitchigan in 2002. Dr. Stephen was a postdoc at the Institute of for Mathematics and its Applications at the University of Minnesota. Dr. Stephen works in the field of operations research. His research focus is in combinatorial optimization, both at a theoretical level and in practice (computationally). In his own words,``I like projects that touch on different areas and disciplines, and my research has ventured into algorithms, combinatorics, discrete geometry and computational biology." Dr. Stephen is a member of the Centre for Operations Research and Decision Sciences at SFU, the Operations Research Group at SFU, and the Discrete Math Group at SFU.
|April - May, 2010||
Combinatorial Models of Synteny Conservation in Genomes
Genomic rearrangements are large-scale evolutionary events that disrupt gene order along chromosomes. The computational analysis of gene orders, their structure and their evolution relies on combinatorial models and algorithms designed in terms of sequences of signed. This project is centered on detection of con served gene clusters, the assignment of evolutionary relations in the presence of multigenes families and the computation of evolution hypothesis. Detecting some clusters is a difficult problem with applications in very applied domains, like pathogenomics. This part of the project aims at designing methods to (1) detect highly rearranged clusters, (2) discriminate between conserved clusters due to evolutive pressure and conserved clusters due to phylogenetic proximity and (3) be computationally efficient in order to process large datasets. Our goal is to develop a gene matching strategy that is not based on an evolutionary model but on the conservation of local synteny and also consider sequence alignments results used to define gene families and a statistical model of synteny conservation significance. The third main part of the project deals with the analysis of gene order datasets produced using the methods developed in the two previous sub-projects for phylogenomic analysis, including computing gene order phylogenies, ancestral gene orders and statistics on genome rearrangements. Attention is also given to the problem of generating â€œgene orderâ€ datasets for eukaryotic genomes, where genes only do not cover enough genome to be reliable markers. We investigate two classical approaches, whole genome alignments and comparative mapping technique, and a new method, based on virtual hybridation. Our approach for most of the above problems relies on sound and well understand combinatorial models for the analysis of signed permutations and sequences, like, but not limited to, common intervals and max-gap clusters. An important focus is on designing and implementing efficient algorithms based on these models.
About the Project Leader: Dr. Cedric Chauve is an associate professor in the Department of Mathematics of Simon Fraser University. Before coming to SFU in 2007, he was a professor in the Computer Science Department of University of Quebec at Montreal (UQAM). Besides his membership at the IRMACS Centre, Dr. Chauve is a member of the SFU Discrete Mathematics Group, Bioinformatics Training Program for Health Research, where he is an associate faculty, Comparative Genomics Laboratory (CGL, UQAM), and Laboratoire de Combinatoire et Informatique Mathematiques (LaCIM, UQAM). His current research deals primarily with mathematical and computational questions arising from comparative genomics. This includes problems on genome rearrangements, gene families evolution, and computational analysis of RNA. Part of Dr. Chauve's scientific work is in enumerative combinatorics and algorithms design.
Applications and Advancements of Algorithms for Nonsmooth Optimization
The Home and Community Care (HCC) branch of health care deals with individuals who require long-term non-hospitalized care. As various demographic factors change, the demand for this form of care will also change. The goal of this project is to develop predictive models that can be used to help explore how HCC will be impacted over the next 10 to 20 years. Of particular interest is how HCC system will be impacted by the increase in average age of British Columbia's population. Future work will refine these models and develop new models for other aspects of the health care system.
About the Project Leader: Dr. Hare received his Ph.D. in Mathematical Optimization from Simon Fraser University. Following this he was a postdoctoral fellow at IMPA - Brazil and at McMaster University. He worked as a Project Leader with the Complex Systems Modelling Group for two years before becoming the Program Director of the MoCSSy Program. He is currently an Assistant Professor at UBC, Okanagan Campus, but maintains collaborations with many MoCSSy researchers. His research focuses mainly on Modelling and Optimization with Applications to Healthcare.
Problems in the Design & Analysis of Computer Experiments
Rapid growth in computer power has made it possible to study complex physical phenomena that might otherwise be too time consuming or expensive to observe. Scientists are able to adjust inputs to computer simulators (or computer codes) in order to help understand their impact on a system. Many such computer simulators require the specification of a large number of input settings and are computationally demanding. This project involves the design and analysis of computer experiments, with emphasis on the study of physics based on engineering simulators. Initial project goals include model calibration and integration of field data with simulator output.
About the Project Leader: Dr. Derek Bingham is an Associate Professor and Canada Research Chair in Industrial Statistics in the Department of Statistics and Actuarial Science at Simon Fraser University. He first came to Simon Fraser in 1995 as a PhD student, after earning a B.Sc. in Applied Math from Concordia University, Montreal, Quebec, and an M.Sc. in Statistics from Carleton University, Ottawa, Ontario. After obtaining his Ph.D. in 1999, Dr. Bingham moved to the Department of Statistics at the University of Michigan, Ann Arbor, Michigan, as an Assistant Professor. In 2003, Dr. Bingham joined the Department of Statistics and Actuarial Science at Simon Fraser as the Canada Research Chair in Industrial Statistics.
|July - August, 2009||Bio-inspired Robotics
Project description: The success of biological organisms in solving problems encountered in their environments is attributed to the process of natural selection, the rigors of this process ensuring the efficacy of the results. Problems that biological systems face are often similar to those faced by engineers. Given the effectiveness with which some of these have been overcome, biologically inspired concepts should be considered seriously when designing new solutions. With the continuing emergency of biomimetics as a distinct scientific discipline, the systematic search for biomimetic solutions to particular problems is an increasingly important focus. Adaptability, autonomy, miniaturization, holistic design, reliability, robustness, self-repair, self-replication are the main traits that can be found in many biological organisms that are of particular interest in space systems design, with its particular requirements and constraints. Dr. Menon and his team design robotic systems inspired by natural principles. They work is truly interdisciplinary and it involves (1) the study of biological systems and the analysis of their physiological, chemical, biomechanical and neurological properties, and (2) the design of robotic systems including the development their mechanical, electrical, electronic and control subsystems. The final objective is the development of high performing robotic prototypes based on the physical principles found in natural organisms.
About the Project Leader: Dr. Carlo Menon is Assistant Professor at School of Engineering Science and Associate Member in the School of Kinesiology at Simon Fraser University. Dr. Menon is the supervisor of the MEchatronics 'N' Robotics for Viable Applications (MENRVA) Lab at SFU. His current research interests include: free-flying space robotics, bioinspired climbing mechatronic systems for servicing, rescue and space applications, bioinspired strain/force sensors, dexterous robotic hand, and forearm assistive-training device to improve autonomy of the elderly. At the 57th International Astronautical Conference on 6 October 2006 in Valencia, Spain, Dr. Menon was presented a prestigious Luigi G. Napolitano Award by the Education Committee of the International Astronautical Federation. In 2007, Dr. Menon was a recipient of the BIONIS Award by Swedish Biomimetics 3000 Ltd., a UK affiliate of SWEDISH BIOMIMETICS 3000, a venture philanthropic organization that supports the rapid development of biomimetically inspired technologies and processes.
|May - June, 2009||Cosmological Tests of Fundamental Physics
The project explores the following two aspects of the interplay between theory and cosmological observations. 1. Search for Statistical Non-Gaussianity in the Cosmic Microwave Background (CMB) Temperature Maps. Part of the motivation for this project is to try to detect line discontinuities in the CMB maps, which would be left by cosmic strings. Any detection of primordial non-Gaussianity on cosmological scales would be a major breakthrough in physics and would help researchers understand the initial state of our universe. 2. Structure Formation in Modified Gravity Models. The motivation for this project is one of the most urgent unsolved problems in Science today: a need to understand the root cause of the ongoing acceleration of our universe. Cosmology provides the opportunity to test predictions of different models of cosmic acceleration with measurements of CMB, weak lensing, supernovae, clustering of matter and various derivatives from these.
About the Project Leader: Dr. Levon Pogosian is Assistant Professor in the Department of Physics at Simon Fraser University. Dr. Pogosian describes himself as a "physicist working in theoretical cosmology". He works in particle cosmology with interests in the composition and evolution of the Universe, dark energy and modified gravity, observational probes of physics beyond Standard Model, topological defect solutions in quantum field theory and their implications for particle physics and cosmology, cosmic (super)strings and other characteristics of Brane Inflation, cosmological magnetic fields, cosmic microwave background (CMB), and tests of cosmological Gaussianity. .
|March - April, 2009||Intellectual Property Issues in Cultural Heritage: Theory, Practice, Policy
A major international research initiative "Intellectual Property (IP) Issues in Cultural Heritage: Theory, Practice, Policy" has been co-developed by Dr. George Nicholas (Simon Fraser Unversity), Dr. Julie Hollowell (Indiana University) and Dr. Kelly Bannister (University of Victoria) and funded by SSHRCs MCRI program. A team of 50 scholars and 25 partnering organizations is working to explore and facilitate fair and equitable exchanges of knowledge relating to archaeology. The team is concerned with the theoretical, ethical, and practical implications of commodification, appropriation, and other flows of knowledge about the past, and with how these may affect communities, researchers, and other stakeholders. The Project provides a foundation of research, knowledge and resources to assist archaeologists, academic institutions, descendant communities, scholars, policy makers, and other stakeholders in negotiating more equitable and successful terms of research and policies through an agenda of community-based research and topical exploration of IP issues.
About the Project Leader: Dr. George Nicholas is Professor in the Department of Archeology at Simon Fraser University. Dr. Nicholas is a co-editor of the series â€œWorld Archaeological Congressâ€™ Research Handbooks in Archaeologyâ€ and between 2001-2007 he was the Editor-And-Chief of Canadian Journal of Archaeology. His main research interests are biodiversity, phylogeny and evolutionary heritage. Dr. Nicholas' interests are broad ranging in terms of research questions, temporal and geographic focus, and theoretical orientation. What links various themes in his research has been Dr. Nicholas' concern with (a) landscape, both cultural and archaeological and (b) the quest for representativeness in both the archaeological record and our approach to, and interpretation, of it.
|January - February, 2009||Helping Entangle the Web of Life with Directed Graphs
All life is related, and a family tree of species is its ultimate representation. Events on the tree can even be dated using molecular data, and so we can tell not only who is related to whom, but by how much. There are interesting problems associated with both building and using trees of species. For one, it seems many species are mosaics of genes derived from different ancestors, much like a child having several mothers. We will help analyze this pattern of evolution based on the theory of directed graphs, with input from collaborators in New Zealand and Germany. Another interesting problem is comparing the true tree of life with what we might expect it to look like under different models of evolution, both with respect to its shape (akin to variation in family sizes) and with respect to the timing of events (when families grow and shrink). This latter comparison assumes that the true tree is properly dated, which is an interesting technical problem in itself. Finally, every time we threaten a species with extinction we threaten a bit of the tree, which will be lopped off forever. The pattern of extinction in nature affects the pattern by which the tree shrinks, and we are interested in modeling this form of evolutionary topiary.
About the project leader: Dr. Arne Mooers is an Associate Professor in the Department of Biology at Simon Fraser University. His main research interests are biodiversity, phylogeny and evolutionary heritage Arne grow up on a little farm in New Brunswick. He spent a year as an exchange student in the Swiss Alps as a teenager, and then went to McGill University to do his undergraduate degree in biology. After graduation he took a year off to travel and work, and then went to Merton College, Oxford, to do a Doctor of Philosophy with Professor Paul Harvey. This was followed by a year that Dr. Mooers describes as â€œanother year semi-offâ€. He did his post-doc at the University of British Columbia, under supervision of Professor Dolph Schluter. The next three years Arne spent in Amsterdam working at the Zoological Museum of the University of Amsterdam. Finally he came back to Vancouver for a job at Simon Fraser