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DTSTART;TZID=America/Detroit:20241101T120000
DTEND;TZID=America/Detroit:20241101T130000
DTSTAMP:20260624T105002
CREATED:20241012T182153Z
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SUMMARY:FSML Lecture Series - Nicholas Galioto: Discovery of Cellular Reprogramming Methodology Through Single-cell Foundation Models
DESCRIPTION:Zoom link \nBio: Nick Galioto is a second-year postdoctoral research fellow in the Department of Computational Medicine and Bioinformatics at the University of Michigan (UM). He received his PhD at UM in aerospace engineering in 2023 under the advising of Alex Gorodetsky and remained in the lab for an additional year as a postdoc. In the Gorodetsky lab\, Nick researched how to use stochastic models of dynamical systems to improve system identification. Now\, Nick works in the Rajapakse lab researching how to create data-driven models of the dynamics of cell reprogramming. \n  \nDiscovery of Cellular Reprogramming Methodology Through Single-cell Foundation Models\n  \nAbstract: Cell reprogramming\, the transformation of a cell from one cell type to another through the introduction of exogenous transcription factors (TFs)\, is a rapidly developing research area that could lead to groundbreaking therapeutic technologies in areas such as tissue regeneration\, disease modeling\, and personalized medicine. However\, many challenges still exist that obstruct its practical viability. Discovering which TFs induce reprogramming requires a combinatorial search\, and testing a single candidate set of TFs experimentally can cost tens of thousands of dollars and take multiple months. Moreover\, even when an effective set of TFs is known\, cell conversion efficiency lies only around 5%. Faced with these challenges\, researchers have developed computational surrogate models to rapidly explore the TF search space at a fraction of the cost of wet lab experimentation. Unfortunately\, these models have seen limited success in practice due to the difficulty of capturing the complex gene-gene interactions within the cell\, most of which are still not well understood. With the recent high-profile rise of transformer-based foundation models for natural language\, researchers are now turning to the transformer to push past\, current performance limitations in a wide range of digital biology tasks\, including cell reprogramming. Of particular interest in these models is the attention mechanism\, which is potentially well-suited for capturing long-range gene-gene interactions at a higher fidelity than previously possible. In this talk\, I will describe how the transformer architecture has been adapted for cellular biology and analyze the utility of one such model\, Geneformer\, in identifying TFs for cell reprogramming. Specifically\, I will present the results of an in silico perturbation experiment for reprogramming fibroblast cells to hematopoietic stem cells and compare the outcomes to experimental results found in the literature. I will conclude the talk with a discussion of the drawbacks and limitations of the Geneformer model and provide an assessment of what will be needed in the future for digital biology to fully reap the benefits of large-scale foundation models.
URL:https://micde.umich.edu/event/lecture-discussionsciml-lecture-series-7/
LOCATION:Walter E Lay Auto Lab – 2052
CATEGORIES:Engineering,FSML,Science
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20241107T180000
DTEND;TZID=America/Detroit:20241107T190000
DTSTAMP:20260624T105002
CREATED:20241029T230120Z
LAST-MODIFIED:20241030T170447Z
UID:10000787-1731002400-1731006000@micde.umich.edu
SUMMARY:Taking the Next Step: Graduate Studies in Computation/AI for Science and Engineering at U-M
DESCRIPTION:PhD in Scientific Computing director Eric Johnsen will speak about opportunities for undergraduate or master’s students seeking a graduate education in Computation and Artificial Intelligence for Science and Engineering at the University of Michigan. Food will be provided. Please register to attend. \nPlease register via the link: https://sessions.studentlife.umich.edu/p/track/12857 \nZoom option available after registering.
URL:https://micde.umich.edu/event/taking-the-next-step-2024/
LOCATION:GG Brown Laboratory – 2147
CATEGORIES:Aerospace Engineering,Ai In Science And Engineering,Artificial Intelligence,Astronomy,Biology,Biomedical Engineering,Biosciences,Biostatistics,Chemical Engineering,Chemistry,Civil and Environmental Engineering,Climate and Space Sciences and Engineering,College Of Engineering,Complex Systems,Computation,Computational Science,Computational Social Science,computer science,computing,Earth And Environmental Sciences,Ecology And Evolutionary Biology,Economics,Education,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Epidemiology,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,High Performance Computing,Industrial and Operations Engineering,Interdisciplinary,Kinesiology,Machine Learning,Materials Science,Mathematics,Mechanical Engineering,Medicine,Micde,Michigan Engineering,Naval Architecture and Marine Engineering,Neuroscience,Nuclear Engineering and Radiological Sciences,Pharmacy,Physics,Politics,Prospective Graduate Students,Psychology,Public Health,Public Policy,Rackham,Research,Robotics,Scientific Computing,Statistics,Talk,Undergraduate,Undergraduate Students,Virtual,Workshop
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2024/10/Happening@UM.png
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20241111T121500
DTEND;TZID=America/Detroit:20241111T131500
DTSTAMP:20260624T105002
CREATED:20240924T215158Z
LAST-MODIFIED:20250107T180016Z
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SUMMARY:Ph.D. in Scientific Computing Student Seminars: Vishal Subramanian / Heting Fu
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we request that all who plan to attend register in advance. \nIf you have any questions\, please email micde-phd@umich.edu. \n\nAccelerating Fock exact exchange calculations using Tucker Tensor techniques \nDensity Functional Theory (DFT) is widely used to predict the electronic structure and properties of a broad range of materials. Although exact in theory\, DFT simulations rely on exchange-correlation (Exc) functionals that are approximated in practice. The accuracy of DFT calculations is solely dependent on the accuracy of the Exc functionals. Hybrid exchange-correlation functionals are a class of functionals that have been shown to match experimental observations more closely compared to other Exc functionals. However\, the use of hybrid Exc functionals necessitates the computation of Fock exact exchange\, significantly increasing the computational cost. Furthermore\, the nature of Fock exact exchange demands a substantial increase in memory requirements and communication across processors. The latter is a serious issue as it affects the scalability of the code\, restricting routine simulations to a few tens of atoms. In this work\, we have developed a Tucker Tensor-based approach that significantly reduces the computational cost of Fock exact exchange calculations. We have incorporated an innovative communication pattern that reduces communication without significantly increasing peak memory usage. Consequently\, we have developed a robust\, efficient\, and scalable algorithm that achieves an order-of-magnitude speedup over the current state of the art. \nVishal Subramanian (Materials Science & Engineering and Scientific Computing) \nVishal Subramanian is a PhD candidate in the Materials Science and Engineering department. He is interested in harnessing the power of linear algebra and high-performance computing to develop robust\, and efficient algorithms that can compute material properties accurately. His work with Prof. Gavini’s group developing algorithms and scalable implementations for fast density functional theory (DFT) calculations on large-scale systems earned him the 2023 Gordon Bell Prize – the highest honor given in high-performance computing. \n\nTopology Optimization for Die Casting with Nonplanar Parting Surfaces \nThis talk presents a density-based topology optimization method for the simultaneous design of die-castable geometry\, die drawing directions\, and arbitrarily nonplanar parting surface. Viewing a die casted part as a two-component system consisting of the cavities of die halves\, an arbitrarily nonplanar parting surface is represented as the boundaries between adjacent partitioned domains similar to the joints in multi-component topology optimization (MTO). The draw direction of each die half is represented as a probability distribution to avoid premature convergence\, and the undercut of a part geometry in the draw direction is evaluated using the gradient of the density field. Several numerical examples are presented to demonstrate the advantages of the inclusion of nonplanar parting surfaces as optimization variables. \nHeting Fu (Mechanical Engineering and Scientific Computing) \nHeting Fu is a Ph.D. candidate under the guidance of Professor Kazuhiro Saitou in Mechanical Engineering. His research involves multi-component\, multi-material\, and multi-process topology optimization.
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-student-seminars-6/
LOCATION:Undergraduate Science Building – 1250
CATEGORIES:Micde,Phd Seminar
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DTSTART;TZID=America/Detroit:20241115T120000
DTEND;TZID=America/Detroit:20241115T130000
DTSTAMP:20260624T105002
CREATED:20241012T182154Z
LAST-MODIFIED:20260522T154425Z
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SUMMARY:FSML Lecture Series - Hongfan Chen: Global Geomagnetic Perturbation Forecasting with Quantified Uncertainty using Deep Gaussian Process
DESCRIPTION:Zoom link \nBio: Hongfan Chen is a third-year PhD student in the Department of Mechanical Engineering at the University of Michigan. His research interests include data assimilation\, uncertainty quantification\, and machine learning applications in space weather. \nGlobal Geomagnetic Perturbation Forecasting with Quantified Uncertainty Using Deep Gaussian Process\nAbstract: Accurately predicting the horizontal component of the ground magnetic field perturbation (dBH)\, as a proxy for Geomagnetically Induced Currents (GICs)\, is crucial for estimating the impact of geomagnetic storms and remains a topic under active investigation. The current state-of-the-practice Geospace model is computationally expensive for fine-grid global simulations while existing machine learning methods consistently tend to underestimate dBH. Additionally\, these models either lack uncertainty quantification (UQ) or provide UQ that lacks calibration. In this work\, as part of the NextGen SWMF project funded by NSF\, we develop a data-driven\, grid-free global model using deep Gaussian process (DGP)\, a Bayesian non-parametric approach that forecasts the dBH for the full surface of Earth with calibrated uncertainty. The model uses solar wind measurements and the Dst index as input\, and it is trained based on ground magnetometer station data provided by SuperMAG over the period 1995-2022. The model’s predictions are evaluated based on the Heidke skill score (HSS) for a total of 22 geomagnetic storms in 2015. We further test the model on the 2024 May 10-12 storm. The results demonstrate that our model outperforms the state-of-the-art model\, with predictions exhibiting high accuracy in mid-latitudes and high-latitude regions in the northern hemisphere. \n 
URL:https://micde.umich.edu/event/lecture-discussionsciml-lecture-series-8/
LOCATION:2636 GGBA\, 2350 Hayward St\, Ann Arbor\, MI\, United States
CATEGORIES:Engineering,FSML,Science
ATTACH;FMTTYPE=image/jpeg:https://micde.umich.edu/wp-content/uploads/2024/10/Hongfan_Chen.jpg
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20241118T121500
DTEND;TZID=America/Detroit:20241118T131500
DTSTAMP:20260624T105002
CREATED:20240924T215200Z
LAST-MODIFIED:20241101T183341Z
UID:10000770-1731932100-1731935700@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we request that all who plan to attend register in advance. \nIf you have any questions\, please email micde-phd@umich.edu.
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-student-seminars-12/
LOCATION:Undergraduate Science Building – 1250
CATEGORIES:Micde,Phd Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20241119T170000
DTEND;TZID=America/Detroit:20241119T180000
DTSTAMP:20260624T105002
CREATED:20240824T040046Z
LAST-MODIFIED:20240824T040046Z
UID:10000743-1732035600-1732039200@micde.umich.edu
SUMMARY:Scientific Computing Student Club General Meeting
DESCRIPTION:Join Us at the Scientific Computing Club’s General Meeting! Don’t miss out on a chance to contribute your ideas and help shape the future of our club. Let’s connect\, collaborate\, and create something amazing together! \nWhere: TBD \nWhen: November 19th\, 2024\, Tuesday\, 5:00 – 6:00 PM \nMeeting Agenda: TBD
URL:https://micde.umich.edu/event/scientific-computing-student-club-general-meeting-7/
CATEGORIES:SC2,Workshops
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