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X-WR-CALNAME:Computational Optimisation Group
X-ORIGINAL-URL:http://optimisation.doc.ic.ac.uk
X-WR-CALDESC:Events for Computational Optimisation Group
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DTSTART:20110101T000000
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DTSTART;TZID=UTC:20120426T140000
DTEND;TZID=UTC:20120426T140000
DTSTAMP:20260418T155802
CREATED:20170124T102149Z
LAST-MODIFIED:20170124T102149Z
UID:607-1335448800-1335448800@optimisation.doc.ic.ac.uk
SUMMARY:Seminar: Development and application of automatic force field parameterization software for molecular simulation
DESCRIPTION:Title: Development and application of automatic force field parameterization software for molecular simulationSpeaker: Dr. Lee-Ping WangAffiliation: Stanford UniversityLocation: Room 218Time: 2:00pm \nAbstract. Force fields are empirical potential energy functions that describe molecules and their interactions; they constitute the physical foundation for simulations of atomic and molecular motion. The accuracy of a force field is determined by empirical parameters\, and the choice of optimal parameters has been a difficult challenge for decades. The molecular simulation community is in need of an automatic and systematic method for force field parameterization\, which would revolutionize the field by providing greatly improved simulation accuracy and reproducibility of force field development. With this goal in mind\, I have developed an open-source software package called ForceBalance to perform automatic force field parameterization. The software is built around a standardized procedure for force field development\, interfaces easily with classical and quantum simulation codes\, and has the ability to produce force fields that are optimized to reproduce any experimental or theoretical reference data. I will introduce the concepts and implementation of ForceBalance\, provide a simple demonstration of the software\, and discuss opportunities for collaboration. \nAbout the speaker. Lee-Ping Wang graduated from U.C Berkeley with a B.A. in Physics in 2006. He entered graduate school in the chemistry department at MIT\, where he worked with Prof. Troy Van Voorhis on various topics in theoretical chemistry such as water splitting catalysis\, QM/MM methods\, and force field development\, graduating with a Ph.D. in 2011. Lee-Ping is now working as a postdoctoral fellow at Stanford University with Profs. Todd Martinez and Vijay Pande where he is continuing to refine force field development methods and applying them to biomolecular simulation.
URL:http://optimisation.doc.ic.ac.uk/event/seminar-development-and-application-of-automatic-force-field-parameterization-software-for-molecular-simulation/
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BEGIN:VEVENT
DTSTART;TZID=UTC:20120427T150000
DTEND;TZID=UTC:20120427T150000
DTSTAMP:20260418T155802
CREATED:20170124T102149Z
LAST-MODIFIED:20170124T102149Z
UID:606-1335538800-1335538800@optimisation.doc.ic.ac.uk
SUMMARY:Seminar: Robust Dynamic Risk Measures
DESCRIPTION:Title: Robust Dynamic Risk MeasuresSpeaker: Dimitra BampouAffiliation: Imperial College LondonLocation: Room 218 Huxley Building Time: 3:00pm \nAbstract. Recent progress in the theory of dynamic risk measures has found a strong echo in stochastic programming\, where the time consistency of dynamic decision making under uncertainty is currently under scrutiny. In this talk we first review the concepts of coherence and time consistency of dynamic risk measures and then discuss their ramifications for stochastic programming. Next\, we extend these concepts to stochastic programming models subject to distributional ambiguity\, which motivates us to introduce robust dynamic risk measures. We discuss conditions under which these robust risk measures inherit coherence and time consistency from their nominal counterparts. We also propose an approximation scheme based on polynomial decision rules for solving linear multistage stochastic programs involving robust dynamic risk measures. The theoretical concepts are illustrated through numerical examples in the context of inventory management. \nAbout the speaker.
URL:http://optimisation.doc.ic.ac.uk/event/seminar-robust-dynamic-risk-measures/
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