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DTSTART;TZID=Europe/Berlin:20180801T120000
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SUMMARY:Presentation by Dr. Christina Schenk of Carnegie Mellon University
DESCRIPTION:Dr. Christina Schenk\, an ALOP Alumni and current post doctoral fellow at Carnegie Mellon University\, will join us for research collaboration and speak during our research seminar on August 1\, 2018 on the following topic: \nParameter Estimation for Pharmaceutical Processes – Advancements and Case Studies \nAbstract: \nThe development of drug manufacturing processes involves dealing with spectroscopic data. When dealing with\n spectroscopic data\, the identification of parameters and variances still remains a challenging task. In many cases\n kinetic parameter identification from spectroscopic data has to be performed without knowing the absorbing\n species in advance\, such that they have to be estimated as well. However\, kinetic parameter estimation is\n important in order to lower production costs\, i.e. save measurements and equipment. Furthermore\, scaling up\n from laboratory to industrial level relies on accurate kinetic parameter values.\n That is why\, we take a closer look at the development of optimization-based procedures in order to estimate the\n variances of the noise in the system variables and spectral measurements. Then\, with the estimated variances\n we determine the concentration profiles and kinetic parameters simultaneously using adequate strategies. The\n work is based on the approach proposed by Chen et al. (2016) using maximum likelihood principles for simultaneous\n estimation of reaction kinetics and curve resolution from process and spectral data. For this a new\n software environment was developed which is continuously enhanced. These investigations and advancements\n are presented within this talk and illustrated by several case studies of pharmaceutical processes. \nJoint work with Lorenz T. Biegler (Carnegie Mellon University)\, Lu Han (Pfizer Inc.) and Jason Mustakis (Pfizer Inc.) \nReferences\n W. Chen\, L. Biegler\, and S. Muñoz. An approach for simultaneous estimation of reaction kinetics and curve resolution\n from process and spectral data. Journal of Chemometrics\, 30:506–522\, 2016. doi: 10.1002/cem.2808.\n URL http://dx.doi.org/10.1002/cem.2808. \n 
URL:https://alop.uni-trier.de/event/presentation-by-dr-christina-schenk-of-carnegie-mellon-university/
CATEGORIES:Scientific Research Collaboration
ORGANIZER;CN="Research Training Group ALOP at Trier University":MAILTO:OptimizationDays@uni-trier.de
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DTSTART;VALUE=DATE:20180813
DTEND;VALUE=DATE:20180817
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SUMMARY:Summer School 2018 - Mixed Integer Nonlinear Programming
DESCRIPTION:The Research Training Group on Algorithmic Optimization proudly announces its third annual Summer/Autumn School from August 13-16\, 2018. This year’s focus will be on Mixed Integer Non-Linear Programming. \n  \nConfirmed speakers are: \nOliver Bastert & Zsolt Csimadia (FICO\, Xpress Optimization) \nChristoph Buchheim (TU Dortmund) \nSven Leyffer (Argonne National Labratory) \nJeff Linderoth (University of Wisconsin-Madison) \n  \nOrganizers:  \n \nUlf Friedrich\, Volker Schulz\, Sven de Vries  \nYou may download a preliminary schedule here \nPlease find all the details at alop.uni-trier.de/MINLP
URL:https://alop.uni-trier.de/event/autumn-school-2018-mixed-integer-non-linear-programming/
LOCATION:Trier University E Building\, Universitätsring 15\, Trier\, 54296\, Germany
CATEGORIES:Workshop
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