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SUMMARY:[SC2 & MICDE] Lunch with alumni: Lois K. Smith
DESCRIPTION:Lois graduated from Michigan in the Fall 2016 with a PhD from the AOSS (now Climate and Space Sciences and Engineering) department and was an MICDE fellow and is Certificate in Computational Discovery & Engineering alumni. Since graduating\, she has been in industry working as a data scientist (iSpot\, Microsoft). She is back on campus and will join the SC2 to talk about her transition to industry and how MICDE and her training in computational sciences helped on the way. \nRSVP please.
URL:https://micde.umich.edu/event/sc2-micde-lunch-with-alumni-lois-k-smith/
LOCATION:1180 Duderstadt Center\, 2281 Bonisteel Blvd\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Education,SC2
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DTSTART;TZID=America/Detroit:20180125T163000
DTEND;TZID=America/Detroit:20180125T173000
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SUMMARY:Graduate programs in computational science — INFO SESSIONS
DESCRIPTION:Students interested in computational science are invited to learn about graduate programs that will prepare them for success in computationally intensive fields. Pizza and pop will be provided. \nTwo sessions are scheduled:\n\nMonday\, Jan. 22\, 4:30 – 5:30 p.m.\, Johnson Rooms\, Lurie Engineering Center (North Campus)\nThursday\, Jan. 25\, 4:30 – 5:30 p.m.\, 2001 LSA Building (Central Campus)\n\nThe sessions will address:\n\n\nThe Ph.D. in Scientific Computing\, which is open to all Ph.D. students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their studies. It is a joint degree program\, with students earning a Ph.D. from their current departments\, “… and Scientific Computing” — for example\, “Ph.D. in Aerospace Engineering and Scientific Computing.” \n\n\nThe Graduate Certificate in Computational Discovery and Engineering\, which trains graduate students in computationally intensive research so they can excel in interdisciplinary HPC-focused research and product development environments. The certificate is open to all students currently pursuing Master’s or Ph.D. degrees at the University of Michigan. The practicum option for Master’s students through the Multidisciplinary Design Program will be explained.
URL:https://micde.umich.edu/event/graduate-studies-in-computational-data-sciences-info-session-central-campus-3/
CATEGORIES:Featured Events
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DTSTART;TZID=America/Detroit:20171121T133000
DTEND;TZID=America/Detroit:20171121T143000
DTSTAMP:20230905T171414Z
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SUMMARY:MICDE Seminar: Edward Maginn\, Department of Chemical and Biomolecular Engineering\, University of Notre Dame
DESCRIPTION:Bio: Edward Maginn received his BS in chemical engineering from Iowa State University and his PhD in chemical engineering from the University of California\, Berkeley. Prior to attending graduate school\, he worked as a process engineer for Procter and Gamble. He has been on the Notre Dame faculty since 1995 and currently holds the Dorini Family Chair of Energy Studies in the Department of Chemical and Biomolecular Engineering. He is also the chair of the department\, and was formerly the Associate Dean for Academic Programs in the Graduate School. He has won a number of awards\, including the Early Career Award from the Computational Molecular Science and Engineering Forum of the American Institute of Chemical Engineers\, the ASEE Dow Outstanding New Faculty Award\, the BP College of Engineering Outstanding Teacher Award and the NSF Career award. He is a Fellow of the American Association for the Advancement of Science and is a trustee of the CACHE Corporation. His research focuses on the development and use of atomistic molecular dynamics and Monte Carlo simulation methods to study the thermodynamic and transport properties of materials\, with special emphasis on ionic systems important in energy storage and use. \nUsing Molecular Modeling to Design New Fluids for Energy Storage and Carbon Capture\nLiquids that contain charged species\, such as electrolytes and ionic liquids\, have many important technological applications in fields such as energy storage\, separations\, and catalysis. By changing the structure of the molecules or employing mixtures\, the properties of these fluids can be altered significantly. The key questions are: How should I change the structure of the molecule or ion to get the properties I want? What type of additives should I use to improve performance? To answer these and related questions\, we use atomistic-level simulations to compute structural\, thermodynamic and transport properties of these systems. We are able to provide molecular-level explanations for experimental observations\, and we can predict properties of systems that may not yet have even been made in the laboratory. \nIn the first part of this talk\, I will describe molecular modeling research directed at improving the performance of electrolytes used in next generation “beyond lithium” batteries. Electrolytes are a critical component of batteries\, since they transport ions from the cathode to the anode during charging\, then in the reverse direction in releasing energy on discharge. Electrolytes play a leading role in a battery’s capacity for energy storage\, its lifetime and the safety of the battery. The electrolyte in a conventional lithium-ion battery consists of a lithium salt dissolved in an organic solvent. The electrolytes for next generation “beyond lithium” batteries will require new salt-solvent combinations.  Our simulations probe the way in which different electrolyte formulations\, charge carriers and additives impact the structure and dynamics of these liquids. \nIn the second half of the talk\, I will show how these same kinds of simulations can be used to develop new ionic liquids that can be used for CO2 separations / capture. Ionic liquids are pure salts that are liquid at ambient temperatures. Because they have essentially no vapor pressure and readily dissolve CO2\, people have been interested in using them for carbon capture. I will describe how our simulations have been successful in identifying new ionic liquids with properties tuned for use as conventional liquid absorbents or as supported ionic liquid membranes. \nThis is a joint seminar with the department of Chemical Engineering. Prof. Maginn is being hosted by Prof. Mayes (Chemical Engineering). If you are interested in meeting him during his visit please send an email to mcteja@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-edward-maginn-department-of-chemical-and-biomolecular-engineering-university-of-notre-dame/
CATEGORIES:Featured Events,MICDE Seminar Series
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DTSTART;TZID=UTC:20160913T161000
DTEND;TZID=UTC:20160913T170000
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SUMMARY:MICDE Seminar: Nathan Kutz\, University of Washington
DESCRIPTION:Bio: Nathan Kutz is the Robert Bolles and Yasuko Endo Professor in the department of Applied Mathematics\, and an adjunct professor of Electrical Engineering and Physics at the University of Washington. He was awarded the B.S. in Physics and Mathematics from the University of Washington in 1990 and the PhD in Applied Mathematics from Northwestern University in 1994. Following postdoctoral fellowships at the Institute for Mathematics and its Applications (University of Minnesota\, 1994-1995) and Princeton University (1995-1997)\, he joined the faculty of applied mathematics and served as Chair from 2007-2015. \nData-driven discovery of dynamical systems in the engineering\, physical and biological sciences\nWe demonstrate that the integration of data-driven dynamical systems and machine learning strategies with adaptive control are capable of producing efficient and optimal self-tuning algorithms for many complex systems arising in the engineering\, physical and biological sciences. We demonstrate that we can use emerging\, large-scale time-series data from modern sensors to directly construct\, in an adaptive manner\, governing equations\, even nonlinear dynamics\, that best model the system measured using sparsity-promoting techniques. Recent innovations also allow for handling multi-scale physics phenomenon and control protocols in an adaptive and robust way. The overall architecture is equation-free in that the dynamics and control protocols are discovered directly from data acquired from sensors. The theory developed is demonstrated on a number of example problems. Ultimately\, the method can be used to construct adaptive controllers which are capable of obtaining and maintaining optimal states while the machine learning and sparse sensing techniques characterize the system itself for rapid state identification and improved optimization. \nThis seminar is co-sponsored by the U-M Department of Mathematics.
URL:https://micde.umich.edu/event/micde-2016-fall-seminar-series-nathan-kutz-university-of-washington/
LOCATION:1360 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:MICDE Seminar Series
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