Past Events

Seminars are held Tuesdays and Thursdays in POB 6.304 from 3:30-5:00 pm, unless otherwise noted. Speakers include scientists, researchers, visiting scholars, potential faculty, and ICES/UT Faculty or staff. Everyone is welcome to attend. Refreshments are served at 3:15 pm.

Monday, Dec 10

  • Additional Information

    Hosted by Ron Elber

    Sponsor: ICES Seminar-Molecular Biophysics Series

    Speaker: Peter Tieleman

    Speaker Affiliation: University of Calgary

  • Abstract

    Biological membranes have a complex composition with hundreds of different lipids and a high protein concentration. The nature of the lateral structure of membranes is hotly debated as experiments reach increasingly higher spatial and temporal resolution and simulations increasingly larger time and length scales. Coarse-grained simulations with the Martini model have enabled a significant jump in time and length scale for detailed simulations, and currently can reach of the order of 100 microseconds on systems of ca. 100 x 100 nm size on relatively available computers. We are particularly interested the interactions between lipids and membrane proteins. The local environment around membrane proteins is uniquely shaped by the protein surface, resulting in a local composition and membrane properties that differ significantly from the average properties of the lipids that make up the membrane model. This may play an important role in shaping the lateral structure of biological membranes. This type of simulation also enables detailed studies on more specific interactions. I will illustrate this with simulations of lipid interactions with P-glycoprotein, a human ABC transporter involved in multidrug resistance.


Friday, Dec 7

Color of Turbulence: Low-complexity stochastic dynamical modeling of turbulent flows **Different Room, Time**

Friday, Dec 7, 2018 from 2PM to 3PM | POB 2.402 (Electronic)

Important Update: Note: Different Room, Different time
  • Additional Information

    Hosted by Mohamadreza Ahmadi

    Sponsor: ICES Seminar

    Speaker: Armin Zare

    Speaker Affiliation: Post-doctoral Research Associate, Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles.

  • Abstract

    This talk describes how to account for second-order statistics of turbulent flows using low-complexity stochastic dynamical models based on the linearized Navier-Stokes (NS) equations. The complexity is quantified by the number of degrees of freedom in the linearized evolution model that are directly influenced by stochastic excitation sources. For the case where only a subset of correlations are known, we develop a framework to complete unavailable second-order statistics in a way that is consistent with linearization around turbulent mean velocity. In general, white-in-time stochastic forcing is not sufficient to explain turbulent flow statistics. We develop models for colored-in-time forcing using a maximum entropy formulation together with a regularization that serves as a proxy for rank minimization. We show that colored-in-time excitation of the NS equations can also be interpreted as a low-rank modification to the generator of the linearized dynamics. Our method provides a data-driven refinement of models that originate from first principles and it captures complex dynamics of turbulent flows in a way that is tractable for analysis, optimization, and control design.

    Bio
    Armin Zare received the B.Sc. degree in Electrical Engineering from Sharif University of Technology, Tehran, Iran, in 2010, and the Ph.D. degree in Electrical Engineering from the University of Minnesota, Minneapolis, in 2016. He is currently a Post-doctoral Research Associate in the Ming Hsieh Department of Electrical Engineering at the University of Southern California, Los Angeles. He is broadly interested in the modeling and control of distributed systems in addition to large-scale and distributed optimization. His primary research interests are in the modeling and control of wall-bounded shear flows using tools from optimization and systems theory. He was the recipient of the Doctoral Dissertation Fellowship from the University of Minnesota in 2015 and a finalist for the Best Student Paper Award at the 2014 American Control Conference.


  • Additional Information

    Hosted by William Ruys and Max Bremer

    Sponsor: ICES Seminar-Student Forum Series

    Speaker: Wei Li

    Speaker Affiliation: ICES, UT Austin

  • Abstract

    Kaggle is the world's largest community of data scientists and machine learners, owned by Google Inc. Kaggle got its start by offering machine learning competitions and now also offers a public data platform, a cloud-based workbench for data science, and short form AI education. In the first part of this talk, I'm going to briefly introduce this platform and some caveats about data science competitions hosted on Kaggle. The second part of this talk will present a past competition where a variety of data--including fundamental and transactional information-- was used to predict potential customers' repayment abilities.


Thursday, Dec 6

Oscillopathies: From Squid Axons to Infant Apneas

Thursday, Dec 6, 2018 from 3:30PM to 5PM | POB 6.304

  • Additional Information

    Hosted by Karen Willcox

    Sponsor: ICES Seminar

    Speaker: David Paydarfar, MD

    Speaker Affiliation: Professor & Chair, Department of Neurology, Dell Medical School, UT Austin

  • Abstract

    Abnormal neural oscillations are implicated in certain disease states, for example repetitive firing of injured axons evoking painful paresthesia, and rhythmic discharges of cortical neurons in patients with epilepsy. In other clinical conditions, the pathological state manifests as a vulnerability of an oscillator to switch off, for example prolonged pauses in automatic breathing commonly observed in preterm infants. I will present theory and experimental observations on the initiation and termination of neural rhythms at the cellular, tissue and organism levels. The findings suggest how small appropriately tuned noisy inputs could silence a neural oscillator or, conversely, could promote rhythmic activity. Noise-sensitive neurons have intrinsic properties that yield interesting physiological properties on the edge of a bifurcation, affording remarkable adaptive capacities to circuits that require rapid and efficient on-off switching; between multiple modes of activity (e.g., quiescence, repetitive firing, bursting) and between multiple functions (e.g., breathing, swallowing, coughing, and vocalization). I will illustrate the therapeutic potential of stochastic stimulation for promoting stability of breathing and preventing central apnea in preterm infants.

    Bio:
    David Paydarfar is Professor and inaugural Chair of the Department of Neurology at the Dell Medical School at The University of Texas at Austin. He previously served as Professor and Executive Vice Chair of the Department of Neurology at the University of Massachusetts Medical School, and as Associate Faculty of the Wyss Institute for Biologically Inspired Engineering at Harvard University. Paydarfar received his B.S. in Physics (summa cum laude) from Duke University and M.D. from the University of North Carolina at Chapel Hill, and completed his residency training in neurology at the Massachusetts General Hospital and Harvard Medical School. He is a Fellow of the American Neurological Association and an Investigator of the Clayton Foundation for Research.


Friday, Nov 30

The Mathematics of Programming

Friday, Nov 30, 2018 from 10AM to 11AM | POB 6.304

  • Additional Information

    Hosted by Kendrick Shepherd and Max Bremer

    Sponsor: ICES Seminar-Babuska Forum Series

    Speaker: Robert van de Geijn

    Speaker Affiliation: Department of Computer Science, UT Austin

  • Abstract

    Many a computational software scientist starts as a “domain scientist” who discovers that computation can accelerate scientific discovery and ends up contributing to the software infrastructure for scientific exploration. As a domain scientist, he/she is expected to understand the mathematics that underlies the domain (physics, chemistry, etc.). Yet once they become software scientists, few master the fundamental mathematics that underlies programming: the so-called Hoare Calculus that underlies goal-oriented programming. Did you know that you can prove a program correct? That the Principle of Mathematical Induction is fundamental to understanding loops? That you can derive programs hand-in-hand with their proofs of correctness? That the derivation process yields families of algorithms from which the highest performing can be chosen? In this talk, we illustrate how the science of programming matrix operations has allowed us to develop open source software libraries that are exceptionally robust and high performing.

    Bio:
    Robert van de Geijn is professor of computer science and member of the Institute for Computational Engineering and Sciences. He received his Ph.D. in Applied Mathematics from the University of Maryland, College Park.

    His interests are in linear algebra, high-performance computing, parallel computing, and formal derivation of algorithms. He heads the FLAME project, a collaboration between UT Austin, Universidad Jaume I (Spain), and RWTH Aachen University (Germany). This project pursues foundational research in the field of linear algebra libraries and has led to the development of the libflame library, a modern, high-performance dense linear algebra library that targets both sequential and parallel architectures. One of the benefits of this library lies with its impact on the teaching of numerical linear algebra, for which van de Geijn received the UT President’s Associates Teaching Excellence Award. He has published several books and more than 100 refereed publications.


Friday, Nov 30

Tensorflow: A Short Primer

Friday, Nov 30, 2018 from 9AM to 10AM | POB 6.304

  • Additional Information

    Hosted by William Ruys and Max Bremer

    Sponsor: ICES Seminar-Student Forum Series

    Speaker: Sheroze Sheriffdeen

    Speaker Affiliation: ICES, UT Austin

  • Abstract

    TensorFlow is an open-source machine learning library for research and production. This primer will introduce TensorFlow’s high-level interfaces which provide building blocks to create and train deep learning models, pre-made and custom Estimators to write your own models, and low-level interfaces to manipulate the underlying computational graphs.

    This primer will introduce Keras, a high-level API to build and train deep learning models. It is used for fast prototyping, advanced research, and production. It is user friendly, modular, and easy to extend. Keras provides a simple interface optimized for common use cases and its models are made by connecting configurable building building blocks together.

    TensorFlow’s Estimators are high-level representations of complete models. It handles the details of initialization, logging, saving and restoring, and many other features so you can concentrate on your model. This primer will show examples of pre-made Estimators, custom Estimators, and how to define your input functions to feed data into these models.

    Finally, this primer will cover TensorFlow’s low-level interface which focuses on building a dataflow graph. In a dataflow graph, the nodes represent units of computation, and the edges represent the data consumed or produced by a computation. This leads to a low-level programming model in which you first define the graph, then create a TensorFlow session to run parts of the graph across a set of local and remote devices. It is important to understand this model as it aids in debugging and extending high-level deep learning models.


Friday, Nov 30

Understanding the Structure-Properties Relationship of the Eye Wall with Applications to Glaucoma

Friday, Nov 30, 2018 from 12PM to 1PM | POB 4.304

Important Update: NOTE: Different day, location
  • Additional Information

    Hosted by Michael Sacks

    Sponsor: ICES Seminar - WCCMS Series

    Speaker: Vicky Nguyen

    Speaker Affiliation: Associate Professor, Mechanical Engineering, Johns Hopkins University

  • Abstract

    The sclera and optic nerve head, along with the cornea, are connective tissues that form the outer wall of the eye in humans. These stiff and tough tissues serve to mechanically support the delicate retinal and neural tissues of the eye while maintaining an optimal shape for refraction. The mechanical properties of the sclera and optic nerve head tissues arise from the fiber-reinforced microstructure of the extracellular matrix, which is composed mainly of collagen and elastin fibers arranged in a proteoglycan-rich matrix. The extracelullar matrix structure in the human optic nerve head is called the lamina cribrosa for its perforated appearance. Variations in the mechanical properties may contribute to the susceptibility and progression of diseases, such as glaucoma. Mouse models of glaucoma have been used to study the biomechanical effects of glaucomatous axon damage. The mouse sclera has a similar extracellular matrix structure as in human, but the mouse optic nerve head does not have a connective tissue lamina cribrosa. It contains instead a network of astrocytes with long processes organized into structures that are evocative of the collagen beam structure of the human lamina cribrosa. In this presentation, I will describe our efforts to understand the structure-properties relationship of the sclera and optic nerve head tissues of human and mouse eyes using an integrated experimental and computational method. To measure the mechanical behavior of the tissues under physiological conditions, we have developed ex-vivo inflation tests with optical imaging and 3D digital image correlation (3D-DIC) and digital volume correlation. We also developed methods to measure the anisotropy of the fibrous collagen microstructure of the sclera and the beam network microstructure of the lamina tissue of our inflation tested specimens. This has allowed us to develop specimen-specific computational micromechanical models to study the structure-properties relationship of these tissues and extract their anisotropic nonlinear elastic properties using inverse analysis. I will also describe applying these methods on experimental mouse models of glaucoma along with chemical and pharmacological interventions to study the remodeling of the tissues with glaucoma.

    Bio
    Thao (Vicky) Nguyen received her S.B. from MIT in 1998, and M.S. and Ph.D. from Stanford in 2004, all in mechanical engineering. She was a research scientist at Sandia National Laboratories in Livermore from 2004- 2007, before joining the Mechanical Engineering Department at The Johns Hopkins University, where she is currently a tenured Associate Professor and The Marlin U. Zimmerman Faculty Scholar in the departments of Mechanical Engineering and Materials Science. Dr. Nguyen’s research encompasses the biomechanics of soft tissues and the mechanics of active polymers and biomaterials. Dr. Nguyen has received the 2008 Presidential Early Career Award for Scientists and Engineers (PECASE) and the NNSA Office of Defense Programs Early Career Scientists and Engineer Awards for her work on modeling the thermomechanical behavior of shape memory polymers. She received the 2013 NSF CAREER award and 2016 JHU Catalyst Award to study the micromechanisms of growth and remodeling of collagenous tissues. She was also awarded the inaugural Eshelby Mechanics Award for Young Faculty for the creative development and applications of mechanics and the ASME Sia Nemat-Nasser Early Career Award for research excellence in mechanics and materials in 2013, and the T.J.R. Hughes Young Investigator Award from the Applied Mechanics Division in 2015.


Thursday, Nov 29

Four "better'' ways to solve the Navier-Stokes equations

Thursday, Nov 29, 2018 from 3:30PM to 5PM | POB 6.304

  • Additional Information

    Hosted by Leszek Demkowicz and Omar Ghattas

    Sponsor: ICES Seminar

    Speaker: Max Gunzburger

    Speaker Affiliation: Professor, Mathematics, Florida State University

  • Abstract

    Four "better'' ways to solve the Navier-Stokes equations: Ensemble discretization methods, an auxiliary equation approach for UQ, simulation of Richardson pair dispersion

    This facetious and self-serving title refers to four novel approaches for Navier-Stokes simulations. The first involves the analysis, numerical analysis, and an efficient implementation strategy for a recently proposed fractional Laplacian closure model that accounts for Richardson pair dispersion observed in turbulent flows.

    The second is the exploitation of accurate and widely applicable ensemble methods in settings in which multiple inputs need to be processed, as is the case for uncertainty quantification, reduced-order modeling, control and optimization, and other applications. The third addresses the lack of regularity of solutions and the resultant loss of accuracy of approximations in the case of white or weakly correlated additive noise forcing. The fourth involves filtered spectral viscosity and hierarchical finite element methods for the Navier-Stokes equations with hyperviscosity regularization and a regularization due to Ladyzhenskaya for which well posedness is proved for the PDE and its discretizations. The first topic will be talked about but because the three other topics cannot be covered in the time allotted, the talk will be preceded by a polling of the audience to select which topics will be talked about. [One or more of these efforts is joint with Trian Iliescu, Nan Jian, Eunjun Lee, Ju Ming, Yuki Saka, Michael Schneier, Catalin Trenchea, Zhu Wang, Fefei Xu, and Wenju Zhao.]

    Bio
    Max D. Gunzburger, Francis Eppes Distinguished Professor of Mathematics at Florida State University, is an American mathematician and computational scientist affiliated with the Florida State interdisciplinary Department of Scientific Computing. He was the 2008 winner of the SIAM W.T. and Idalia Reid Prize in Mathematics. His seminal research contributions include flow control, finite element analysis, superconductivity and Voronoi tessellations. He has also made contributions in the areas of aerodynamics, materials, acoustics, climate change, groundwater, image processing and risk assessment.


Wednesday, Nov 28

Exploring the Arctic Ocean

Wednesday, Nov 28, 2018 from 12PM to 1PM | Visual Arts Center, 2301 San Jacinto Blvd, Austin TX, 78712

Important Update: PLEASE Note different venue and times
  • Additional Information

    Hosted by Patrick Heimbach and An T. Nguyen

    Sponsor: Joint ICES/Department of Art and Art History (DAAH)

    Speaker: Ulrike Heine

    Speaker Affiliation: UT Austin

  • Abstract

    Curator Ulrike Heine will lead a public tour of the exhibition Exploring the Arctic Ocean (https://sites.utexas.edu/utvac/exploring-the-arctic-ocean/).

    Bio
    Ulrike Heine is a visual studies scholar and curator with a focus on the intersection of visual arts and ecology. She completed her PhD with a thesis on climate change-related imagery. From 2013 to 2016, Heine was on the curatorial staff of the MIT Museum in Cambridge, an institution working at the intersection of science, technology, and the arts.

  • Multimedia

     Event Stream Link: Click Here to Watch


Wednesday, Nov 28

Art and Activism

Wednesday, Nov 28, 2018 from 5PM to 8PM | Fleming Lecture Hall, Belo Center for New Media (BMC 1.202)

  • Additional Information

    Hosted by Patrick Heimbach and An T. Nguyen

    Sponsor: Joint ICES/Department of Art and Art History (DAAH)

    Speaker: John Quigley

    Speaker Affiliation: https://sites.utexas.edu/utvac/exploring-the-arctic-ocean/

  • Abstract

    In 2014, Quigley was commissioned by Greenpeace to create an installation that would highlight the effects of the rapid melting of sea ice in the Arctic. Quigley used copper strips to lay the outlines of Da Vinci’s Vitruvian Man on a large ice floe. In his presentation, Quigley will talk about this and other projects, and discuss the efficacy of activist art production.

    https://sites.utexas.edu/utvac/art-and-activism/
    Presented in conjunction with the exhibition "Exploring the Arctic Ocean", https://sites.utexas.edu/utvac/exploring-the-arctic-ocean/.

  • Multimedia

     Event Stream Link: Click Here to Watch