The Cross-Fertilization track runs on an exceptional basis, and provides an opportunity to welcome speakers from different disciplines who are working in areas which use simulation modeling or analysis methods related to simulation as part of their work. The goal of the track is to welcome leading researchers who use simulation in ways which might stimulate new approaches in the Winter Simulation Community and new collaborations with others who also use simulation in important areas.
This year we are pleased to welcome three leading scholars in the Cross-Fertilization Track.
Paulette Clancy is the Bodman Professor of Chemical and Biomolecular Engineering at Cornell. She is the Director of the Cornell Institute for Computational Science and Engineering and Associate Director of the Energy Institute. She was the first woman to Chair an Engineering department at Cornell. She was educated as a chemist at London and Oxford Universities and joined the faculty in 1987. Her research studies atomic-scale modeling of semiconductor materials using techniques from the electronic scale, to molecular and mesoscopic scales: Ab initio, Molecular Dynamics, Kinetic Monte Carlo. Her team focuses on establishing links between processing-structure-properties to fulfill desired constraints.
Dr. Clancy’s talk on The Search for New Strategies to Facilitate Materials Discovery will focus on the potential impact of engaging Bayesian optimization on the search for new and/or improved materials in situations where the data are expensive to calculate and heterogeneous in nature. One completed case study will explain how such methods were used to find polymorphs (different structures of the same material that appear as the processing conditions are changed, e.g., by being placed under shear). Here the material’s preferred structural configurations are changed by shearing to favor other morphologies that have better charge-carrying capability and hence better performance as a semiconductor. Other case studies will be offered as research in progress to suggest how optimization and search techniques could tame the current complexity that defines the discovery of new materials with chosen properties.
Oliver Gutsche is a staff scientist at the Fermi National Accelerator Laboratory and member of the CMS collaboration of 2,500 physicists, which is operating one of the 4 detectors at the Large Hadron Collider (LHC) at CERN in Geneva, Switzerland. His research focuses on new physics beyond the established theory of particle physics called the Standard Model, especially in the areas of Super Symmetry and Dark Matter. Dr. Gutsche coordinates the computing needs, architects computing systems and leads the computing team for the High Energy, Neutrino and Muon Particle Physics experiments at the laboratory. This includes large scale computing solutions used for the LHC experiments to analyze multi-Petabyte size datasets on distributed computing infrastructures of as many as 100,000 cores.
Dr. Gutsche will speak about Dark Matter and Super Symmetry: Exploring and explaining the Universe with simulations at the LHC.The Large Hadron Collider (LHC) at CERN in Geneva, Switzerland, is one of the largest machines on this planet. It is built to smash protons into each other at unprecedented energies to reveal the fundamental constituents of our universe. The 4 detectors at the LHC record multi-Petabyte datasets every year. The scientific analysis of this data requires equally large simulation datasets of the collisions based on the theory of particle physics, the Standard Model. The goal is to verify the validity of the Standard Model or of theories that extend the Model like the concepts of Super Symmetry and an explanation of Dark Matter. I will give an overview of the nature of simulations needed to discover new particles like the Higgs Boson in 2012, and review the different areas where simulations are indispensable: from the actual recording of the collisions to the extraction of scientific results to the conceptual design of improvements to the LHC and its experiments.
Alexander Rutherford is Scientific Director, Complex Systems Modelling Group, The IRMACS Centre, at Simon Fraser University. Dr. Rutherford holds a Ph.D. in Mathematical Physics from the University of British Columbia and held postdoctoral fellowships at the Swiss Federal Institute of Technology (ETH) in Zurich, Switzerland, and the International School for Advanced Studies (SISSA) in Trieste, Italy. His research spans a wide range of fields within the mathematical sciences. In health research, he works on epidemiological modelling, optimal disease, and operations research in acute care. He also works on operations research of the criminal justice system and criminology. In mathematical physics, his main focus has been on quantum-mechanical many-body problems.
Dr. Rutherford will speak about Control of an Injection Drug User HIV Epidemic: Simulation modelling on complex networks. HIV continues to present a serious public health problem in many marginalized communities. We have developed a network simulation model of the HIV epidemic among injection drug users and female sex workers in Vancouver’s Downtown Eastside. The model is calibrated using data from public health surveillance and cohort studies of this community. Potential strategies to control the epidemic include harm reduction programs, such as distribution of clean needles and supervised injection sites. Many HIV positive individuals are unaware of their HIV status and strategies for HIV testing are an important part of any response to an HIV epidemic. Upon diagnosis, HIV patients enter a continuum of care, involving both engagement and retention in treatment. Simulation modelling is used to assess the potential impacts of combinations of these strategies for combating this HIV epidemic.