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DTSTART;TZID=UTC:20160929T160000
DTEND;TZID=UTC:20160929T170000
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SUMMARY:MICDE Seminar: Jeremy Lichstein\, University of Florida
DESCRIPTION:Bio: Jeremy Lichstein is an assistant professor of Biology at the University of Florida. Professor Lichstein got his Ph. D. from Princeton University and was a postdoctoral research fellow at Princeton’s department of Ecology and Evolutionary Biology. He was the recipient of the University of Florida Excellence Award for Assistant Professor\, and was named a Florida Climate Institute Fellow for 2016-2017. His research interests are forest dynamics\, biodiversity\, carbon cycle and climate change. \nBiodiversity and the changing Earth System: computational challenges and new answers to old questions\nTerrestrial ecosystems currently offset roughly 25% of global annual anthropogenic fossil fuel emissions. However\, the fate of this carbon sink is highly uncertain\, in large part because global models diverge in their predictions of ecosystem responses to climate change\, drought\, and other perturbations. Although there is little agreement on how terrestrial ecosystems will respond to global change on decadal and longer time-scales\, there is wide consensus that current global models are overly simplistic in their representation of important ecological processes. I will discuss our current understanding of how tree functional diversity is maintained in forests\, the consequences of including more realistic levels of functional diversity in global models\, and the computational challenges that need to be overcome in order to introduce ecological realism into the Earth System Models that the scientific and policy communities rely on for climate projections. A key result that is emerging from empirical and theoretical studies is that shifts in species composition across time or space (beta diversity) have different (and sometimes opposite) effects on ecosystem stability as local (alpha) diversity. \nThis seminar is co-sponsored by the U-M department of Ecology and Evolutionary Biology
URL:https://micde.umich.edu/event/micde-2016-fall-seminar-series-jeremy-lichstein-university-of-florida/
LOCATION:1210 Chemistry & Willard H Dow Laboratory\, 930 University Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:MICDE Seminar Series
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DTSTART;TZID=UTC:20160922T160000
DTEND;TZID=UTC:20160922T170000
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SUMMARY:MICDE Seminar: Rob Gardner\, University of Chicago
DESCRIPTION:Bio: Robert Gardner is a Senior Scientist at the Computation Institute from the University of Chicago\,  and aSenior Scientist in the Enrico Fermi Institute. He spent his early academic career doing experimental high-energy physics research at different universities in the Midwest. He has been a member of the ATLAS experiment using the Large Hadron Collider at the CERN Laboratory\, Geneva\, Switzerland since 1998. His experimental work led him to specialize in developing and improving distributed computing technologies necessary for discoveries at the frontier of particle physics. He was instrumental in developing early research computing grids in the U.S.: the International Virtual Data Grid Laboratory (iVDGL)\, and the first deployment of the Open Science Grid (OSG) (NSF\, Department of Energy). He have also generated systems for metrics collection for distributed systems (Grid Telemetry\, PI\, NSF-ITR). Currently\, he directs the ATLAS Midwest Tier2 Center\, which is comprised of integrated computing facilities from the University of Chicago\, Indiana University\, and the University of Illinois. \nLeadership cyberinfrastructure for science and the humanities\nIn the past two decades high energy physics transformed its computing model from one relying on a single high performance computing center at the host laboratory to one incorporating resources distributed across institutional boundaries and geographic regions. Given the complexity of detectors and scale of data\, the international collaborations of the Large Hadron Collider at CERN demanded it. By removing barriers to resource sharing\, the resulting data and computation platform democratized the physics process across collaborations. Accelerated modes of scientific discovery by thousands of physicists were forged using hundreds of data centers linked by very high bandwidth networks. Meanwhile the explosion of commercial\, social and enterprise data has driven innovation in resource abstraction and the creation of new service platforms\, offering fresh opportunities to accelerate science and intellectual inquiry at all scales and across all domains. In this talk I’ll discuss the strategic significance that cyberinfrastructure technology plays in this regard and describe models for creating ubiquitous “substrates” that remove obstacles to connecting campuses\, facilities\, instruments and researchers. \nThis seminar is co-sponsored by the U-M department of Physics
URL:https://micde.umich.edu/event/micde-2016-fall-seminar-series-rob-gardner-university-of-chicago/
LOCATION:340 West Hall\, 1085 South University Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:MICDE Seminar Series
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DTSTART;TZID=UTC:20160921T170000
DTEND;TZID=UTC:20160921T180000
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SUMMARY:Graduate Studies in Computational & Data Sciences Info Session - Central Campus
DESCRIPTION:Learn about graduate programs that will prepare you for success in computationally intensive fields — pizza and pop provided \n\nThe Ph.D. in Scientific Computing 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.”\nThe Graduate Certificate in Computational Discovery and Engineering 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. This year we will offer a new practicum option through the Multidisciplinary Design Program.\nThe Graduate Certificate in Data Science is focused on developing core proficiencies in data analytics:\n1) Modeling — Understanding of core data science principles\, assumptions and applications;\n2) Technology — Knowledge of basic protocols for data management\, processing\, computation\, information extraction\, and visualization;\n3) Practice — Hands-on experience with real data\, modeling tools\, and technology resources.
URL:https://micde.umich.edu/event/graduate-studies-in-computational-data-sciences-info-session-central-campus-2/
LOCATION:2001 LSA Building\, 500 State St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Info Session
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DTSTART;TZID=UTC:20160919T170000
DTEND;TZID=UTC:20160919T180000
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CREATED:20230905T171442Z
LAST-MODIFIED:20230905T171442Z
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SUMMARY:Graduate Studies in Computational & Data Sciences Info Session - North Campus
DESCRIPTION:Learn about graduate programs that will prepare you for success in computationally intensive fields — pizza and pop provided \n\nThe Ph.D. in Scientific Computing 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.”\nThe Graduate Certificate in Computational Discovery and Engineering 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. This year we will offer a new practicum option through the Multidisciplinary Design Program.\nThe Graduate Certificate in Data Science is focused on developing core proficiencies in data analytics:\n1) Modeling — Understanding of core data science principles\, assumptions and applications;\n2) Technology — Knowledge of basic protocols for data management\, processing\, computation\, information extraction\, and visualization;\n3) Practice — Hands-on experience with real data\, modeling tools\, and technology resources.
URL:https://micde.umich.edu/event/graduate-studies-in-computational-data-sciences-info-session-north-campus-2/
LOCATION:Johnson Rooms\, Lurie Engineering Center\, 3rd Floor\, 1221 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Info Session
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