From hetmaniu at uw.edu Mon Jan 4 21:04:36 2016
From: hetmaniu at uw.edu (Ulrich Hetmaniuk)
Date: Tue Jun 12 13:43:55 2018
Subject: [Amath-seminars] Fwd: Jan. 5 - Special AMATH Seminar - Tom Trogdon
(NYU)
In-Reply-To:
References:
Message-ID:
Here is a kind reminder about Tom Trogdon's talk on Tuesday Jan. 5th at
16h00 (HUB 334).
---------- Forwarded message ----------
From: Ulrich Hetmaniuk
Date: Tue, Dec 29, 2015 at 4:19 PM
Subject: Jan. 5 - Special AMATH Seminar - Tom Trogdon (NYU)
To: amath-local@amath.washington.edu, affiliate@amath.washington.edu,
amath-seminars@u.washington.edu
Dear All,
We hope you can join us for our special AMATH seminar on Tuesday January
5th.
Speaker: Tom Trogdon, Courant Institute of Mathematics, NYU
Time: January 5, 16h00
Location: HUB 334
Title: Universality in numerical computations with random data
Abstract
-----------
This talk will concern recent progress on the statistical analysis of
numerical algorithms with random initial data. In particular, with
appropriate randomness, the fluctuations of the iteration count (halting
time) of numerous numerical algorithms have been demonstrated to be
universal, i.e., independent of the distribution on the initial data. This
phenomenon has given new insights into random matrix theory. Furthermore,
estimates from random matrix theory allow for fluctuation limit theorems
for simple algorithms and halting time estimates for others. The
universality in the halting time is directly related to the experimental
work of Bakhtin and Correll on neural computation and human decision-making
times.
Speaker webpage
------------------------
http://www.cims.nyu.edu/~trogdon/
-------------- next part --------------
An HTML attachment was scrubbed...
URL:
From hetmaniu at uw.edu Tue Jan 5 22:33:31 2016
From: hetmaniu at uw.edu (Ulrich Hetmaniuk)
Date: Tue Jun 12 13:43:55 2018
Subject: [Amath-seminars] Jan. 12 - Special AMATH Seminar - Mary Wootters
(CMU)
Message-ID:
Dear All,
We hope you can join us for our special AMATH seminar on Tuesday January
12th.
Speaker: Mary Wootters, Carnegie Mellon University
Time: January 12th, 16h00
Location: HUB 250
Title: From compressed sensing to coding theory
Abstract
-----------
I'll discuss two problems, which on the surface seem quite different. The
first, which comes up in signal processing and in algorithm design, is the
problem of coming up with linear, geometry-preserving maps which are
efficient to store and manipulate. The second, which comes up in coding
theory and theoretical computer science, is the problem of establishing the
list-decodability -- a combinatorial property -- of error correcting
codes. I'll establish a connection between these two problems, and discuss
how techniques from high-dimensional probability can be used to handle
both. Punchlines include improved fast Johnson-Lindenstrauss transforms
and structured RIP matrices, and the answer to some longstanding open
combinatorial questions in coding theory.
Speaker webpage
------------------------
https://sites.google.com/site/marywootters/
-------------- next part --------------
An HTML attachment was scrubbed...
URL:
From hetmaniu at uw.edu Tue Jan 12 06:00:27 2016
From: hetmaniu at uw.edu (Ulrich Hetmaniuk)
Date: Tue Jun 12 13:43:55 2018
Subject: [Amath-seminars] Jan. 12 - Special AMATH Seminar - Mary
Wootters (CMU)
In-Reply-To:
References:
Message-ID:
Here is a kind reminder about Mary Wootters' talk today, Tuesday Jan. 12th
at 16h00 (HUB 250).
-----------------
Dear All,
>
> We hope you can join us for our special AMATH seminar on Tuesday January
> 12th.
>
> Speaker: Mary Wootters, Carnegie Mellon University
> Time: January 12th, 16h00
> Location: HUB 250
>
> Title: From compressed sensing to coding theory
>
> Abstract
> -----------
> I'll discuss two problems, which on the surface seem quite different. The
> first, which comes up in signal processing and in algorithm design, is the
> problem of coming up with linear, geometry-preserving maps which are
> efficient to store and manipulate. The second, which comes up in coding
> theory and theoretical computer science, is the problem of establishing the
> list-decodability -- a combinatorial property -- of error correcting
> codes. I'll establish a connection between these two problems, and discuss
> how techniques from high-dimensional probability can be used to handle
> both. Punchlines include improved fast Johnson-Lindenstrauss transforms
> and structured RIP matrices, and the answer to some longstanding open
> combinatorial questions in coding theory.
>
>
> Speaker webpage
> ------------------------
> https://sites.google.com/site/marywootters/
>
>
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL:
From hetmaniu at uw.edu Thu Jan 14 07:57:18 2016
From: hetmaniu at uw.edu (Ulrich Hetmaniuk)
Date: Tue Jun 12 13:43:55 2018
Subject: [Amath-seminars] Jan. 19 - Special AMATH Seminar - Jay Newby (UNC)
Message-ID:
Dear All,
We hope you can join us for our special AMATH seminar on Tuesday January
19th.
Speaker: Jay Newby, University of North Carolina
Time: January 19th, 16h00
Location: DEM 004
Title: How first passage time problems can help us understand transport of
biomolecules in crowded environments
Abstract
-----------
My talk will explore how first passage time problems are used to model
molecular transport in biology. Cellular environments are typically crowded
and highly heterogeneous. Even if large molecular species are not directly
involved in a given reaction, they can influence it through steric
interactions. By modeling the random motion of individual molecules in
heterogeneous environments, first passage time statistics can be used to
understand the dynamics of complex physiological processes. I will discuss
two examples.
(i) First, I will show how antibodies are dynamically tuned to anchor large
nanoparticles, such as viruses, to constitutive elements of a mucin polymer
gel. Mucus is a vital component of our immune system and provides a first
line of defense against infection. Large nanoparticles such as bacteria are
trapped within the tangled polymer network, preventing contact with the
mucus membrane and subsequent infection. However, some nanoparticles, such
as certain viruses, are small enough that they can freely diffuse through
the polymer matrix. One hypothesis for how smaller nanoparticles could be
trapped is that they are crosslinked to the mucin network by antibodies.
Indeed, antibodies are present in large quantities within mucus. However,
the hypothesis was previously discounted because antibodies typically have
very weak affinity for mucin. Counter to the prevailing theory that
antibodies are only effective if they have strong affinity to mucin, I will
show how weak affinity and rapid binding kinetics substantially improves
their ability to trap large nanoparticles.
(ii) In the second half of my talk I will present theoretical support for a
hypothesis about cell-cell contact, which plays a critical role in immune
function. A fundamental question for all cell-cell interfaces is how
receptors and ligands come into contact, despite being separated by large
molecules, the extracellular fluid, and other structures in the glycocalyx.
The cell membrane is a crowded domain filled with large glycoproteins that
impair interactions between smaller pairs of molecules, such as the T cell
receptor and its ligand, which is a key step in immunological information
processing and decision-making. A first passage time problem allows us to
gauge whether a reaction zone can be cleared of large molecules through
passive diffusion on biologically relevant timescales. I combine numerical
and asymptotic approaches to obtain a complete picture of the first passage
time, which shows that passive diffusion alone would take far too long to
account for experimentally observed cell-cell contact formation times. The
result suggests that cell-cell contact formation may involve previously
unknown active mechanical processes.
Speaker webpage
------------------------
http://www.math.utah.edu/~newby/
-------------- next part --------------
An HTML attachment was scrubbed...
URL:
From hetmaniu at uw.edu Mon Jan 18 20:10:26 2016
From: hetmaniu at uw.edu (Ulrich Hetmaniuk)
Date: Tue Jun 12 13:43:55 2018
Subject: [Amath-seminars] Jan. 19 - Special AMATH Seminar - Jay Newby
(UNC)
In-Reply-To:
References:
Message-ID:
Here is a kind reminder about Jay Newby's talk, Tuesday Jan. 19th at 16h00
(DEM 004).
----------------
Dear All,
>
> We hope you can join us for our special AMATH seminar on Tuesday January
> 19th.
>
> Speaker: Jay Newby, University of North Carolina
> Time: January 19th, 16h00
> Location: DEM 004
>
> Title: How first passage time problems can help us understand transport of
> biomolecules in crowded environments
>
> Abstract
> -----------
>
> My talk will explore how first passage time problems are used to model
> molecular transport in biology. Cellular environments are typically crowded
> and highly heterogeneous. Even if large molecular species are not directly
> involved in a given reaction, they can influence it through steric
> interactions. By modeling the random motion of individual molecules in
> heterogeneous environments, first passage time statistics can be used to
> understand the dynamics of complex physiological processes. I will discuss
> two examples.
>
> (i) First, I will show how antibodies are dynamically tuned to anchor
> large nanoparticles, such as viruses, to constitutive elements of a mucin
> polymer gel. Mucus is a vital component of our immune system and provides a
> first line of defense against infection. Large nanoparticles such as
> bacteria are trapped within the tangled polymer network, preventing contact
> with the mucus membrane and subsequent infection. However, some
> nanoparticles, such as certain viruses, are small enough that they can
> freely diffuse through the polymer matrix. One hypothesis for how smaller
> nanoparticles could be trapped is that they are crosslinked to the mucin
> network by antibodies. Indeed, antibodies are present in large quantities
> within mucus. However, the hypothesis was previously discounted because
> antibodies typically have very weak affinity for mucin. Counter to the
> prevailing theory that antibodies are only effective if they have strong
> affinity to mucin, I will show how weak affinity and rapid binding kinetics
> substantially improves their ability to trap large nanoparticles.
>
> (ii) In the second half of my talk I will present theoretical support for
> a hypothesis about cell-cell contact, which plays a critical role in immune
> function. A fundamental question for all cell-cell interfaces is how
> receptors and ligands come into contact, despite being separated by large
> molecules, the extracellular fluid, and other structures in the glycocalyx.
> The cell membrane is a crowded domain filled with large glycoproteins that
> impair interactions between smaller pairs of molecules, such as the T cell
> receptor and its ligand, which is a key step in immunological information
> processing and decision-making. A first passage time problem allows us to
> gauge whether a reaction zone can be cleared of large molecules through
> passive diffusion on biologically relevant timescales. I combine numerical
> and asymptotic approaches to obtain a complete picture of the first passage
> time, which shows that passive diffusion alone would take far too long to
> account for experimentally observed cell-cell contact formation times. The
> result suggests that cell-cell contact formation may involve previously
> unknown active mechanical processes.
>
>
> Speaker webpage
> ------------------------
> http://www.math.utah.edu/~newby/
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL:
From hetmaniu at uw.edu Wed Jan 20 11:24:41 2016
From: hetmaniu at uw.edu (Ulrich Hetmaniuk)
Date: Tue Jun 12 13:43:55 2018
Subject: [Amath-seminars] Jan. 26 - Special AMATH Seminar - Dominique Zosso
(UCLA)
Message-ID:
Dear All,
We hope you can join us for our special AMATH seminar on Tuesday January
26th.
Speaker: Dominique Zosso, UCLA
Time: January 26th, 16h00
Location: DEM 004
Title: From Sparsity in Images and Information Science to Efficient PDE
Solvers
Abstract
-----------
There is a strong convergence between problems and methods in imaging, data
science and machine learning. Maybe more unexpectedly, elliptic PDEs
equally bear strong similarities with these imaging and data problems. In
this talk, I will present recent and ongoing research on numerical schemes
associated with optimization problems in imaging/data science, and
naturally related to elliptic PDEs. Recently, the primal-dual hybrid
gradients (PDHG) method has been revived. In our work, we realize that in
the particular yet frequent case of Dirichlet-energy problems, the proximal
update of the dual problem has an immediate, simple solution, and the dual
variable can be eliminated altogether. The resulting scheme is reduced to a
primal update problem that contains a momentum term, which significantly
boosts the convergence over standard gradient descent. Since elliptic PDEs
describe the minimizers of associated convex minimization problems, this
algorithm extends to the explicit, fast solution of elliptic PDE problems
without operator inversion. I will describe our algorithm in detail on a
simple Laplace problem and briefly analyze the dynamics of the resulting
optimization scheme. We then look at more interesting PDE and optimization
problems, ranging from classical image denoising, motion by mean curvature,
the obstacle problem, to nonconvex problems such as eigenfunctions of the
Schr?dinger operator and pagerank on graphs. The proposed algorithms are
derived in a disciplined way, are simple to interpret and implement, and
generally fast.
Speaker webpage
------------------------
http://www.math.ucla.edu/~zosso/
-------------- next part --------------
An HTML attachment was scrubbed...
URL:
From hetmaniu at uw.edu Mon Jan 25 08:33:34 2016
From: hetmaniu at uw.edu (Ulrich Hetmaniuk)
Date: Tue Jun 12 13:43:55 2018
Subject: [Amath-seminars] Jan. 26 - Special AMATH Seminar - Dominique
Zosso (UCLA)
In-Reply-To:
References:
Message-ID:
Dear All,
Here is a kind reminder of Dominique Zosso's upcoming talk
Speaker: Dominique Zosso, UCLA
Time: January 26th, 16h00
Location: DEM 004
> Title: From Sparsity in Images and Information Science to Efficient PDE
Solvers
>
> Abstract
> -----------
> There is a strong convergence between problems and methods in imaging,
data science and machine learning. Maybe more unexpectedly, elliptic PDEs
equally bear strong similarities with these imaging and data problems. In
this talk, I will present recent and ongoing research on numerical schemes
associated with optimization problems in imaging/data science, and
naturally related to elliptic PDEs. Recently, the primal-dual hybrid
gradients (PDHG) method has been revived. In our work, we realize that in
the particular yet frequent case of Dirichlet-energy problems, the proximal
update of the dual problem has an immediate, simple solution, and the dual
variable can be eliminated altogether. The resulting scheme is reduced to a
primal update problem that contains a momentum term, which significantly
boosts the convergence over standard gradient descent. Since elliptic PDEs
describe the minimizers of associated convex minimization problems, this
algorithm extends to the explicit, fast solution of elliptic PDE problems
without operator inversion. I will describe our algorithm in detail on a
simple Laplace problem and briefly analyze the dynamics of the resulting
optimization scheme. We then look at more interesting PDE and optimization
problems, ranging from classical image denoising, motion by mean curvature,
the obstacle problem, to nonconvex problems such as eigenfunctions of the
Schr?dinger operator and pagerank on graphs. The proposed algorithms are
derived in a disciplined way, are simple to interpret and implement, and
generally fast.
>
>
> Speaker webpage
> ------------------------
> http://www.math.ucla.edu/~zosso/
-------------- next part --------------
An HTML attachment was scrubbed...
URL:
From hetmaniu at uw.edu Mon Jan 25 08:36:28 2016
From: hetmaniu at uw.edu (Ulrich Hetmaniuk)
Date: Tue Jun 12 13:43:55 2018
Subject: [Amath-seminars] Jan. 28 - Special AMATH Seminar - Ivana Bozic
(Harvard)
Message-ID:
Dear All,
We hope you can join us for our special AMATH seminar on **Thursday**
January 28th.
Speaker: Ivana Bozic, Harvard
Time: January 28th, 16h00
Location: SMI 102
Title: Stochastic evolutionary modeling of cancer development and
resistance to treatment
Abstract
-----------
Cancer is the result of a stochastic evolutionary process characterized by
the accumulation of mutations that are responsible for tumor growth, immune
escape, and drug resistance, as well as mutations with no effect on the
phenotype. Stochastic modeling can be used to describe the dynamics of
tumor cell populations and obtain insights into the hidden evolutionary
processes leading to cancer. I will present recent approaches that use
branching process models of cancer evolution to quantify intra-tumor
heterogeneity and the development of drug resistance, and their
implications for interpretation of cancer sequencing data and the design of
optimal treatment strategies.
Speaker webpage
------------------------
http://www.ivanabozic.com
-------------- next part --------------
An HTML attachment was scrubbed...
URL:
From hetmaniu at uw.edu Wed Jan 27 14:17:39 2016
From: hetmaniu at uw.edu (Ulrich Hetmaniuk)
Date: Tue Jun 12 13:43:55 2018
Subject: [Amath-seminars] Jan. 28 - Special AMATH Seminar - Ivana Bozic
(Harvard)
In-Reply-To:
References:
Message-ID:
Dear All,
Here is a kind reminder of Ivana Bozic's upcoming talk
Title: Stochastic evolutionary modeling of cancer development and
resistance to treatment
Time: January 28th, 16h00
Location: SMI 102
On Mon, Jan 25, 2016 at 8:36 AM, Ulrich Hetmaniuk wrote:
> Dear All,
>
> We hope you can join us for our special AMATH seminar on **Thursday**
> January 28th.
>
> Speaker: Ivana Bozic, Harvard
> Time: January 28th, 16h00
> Location: SMI 102
>
> Title: Stochastic evolutionary modeling of cancer development and
> resistance to treatment
>
> Abstract
> -----------
> Cancer is the result of a stochastic evolutionary process characterized by
> the accumulation of mutations that are responsible for tumor growth, immune
> escape, and drug resistance, as well as mutations with no effect on the
> phenotype. Stochastic modeling can be used to describe the dynamics of
> tumor cell populations and obtain insights into the hidden evolutionary
> processes leading to cancer. I will present recent approaches that use
> branching process models of cancer evolution to quantify intra-tumor
> heterogeneity and the development of drug resistance, and their
> implications for interpretation of cancer sequencing data and the design of
> optimal treatment strategies.
>
> Speaker webpage
> ------------------------
> http://www.ivanabozic.com
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL:
From hetmaniu at uw.edu Sun Jan 31 15:19:54 2016
From: hetmaniu at uw.edu (Ulrich Hetmaniuk)
Date: Tue Jun 12 13:43:55 2018
Subject: [Amath-seminars] Feb. 4 - Special AMATH Seminar - Benjamin
Peherstorfer (MIT)
Message-ID:
Dear All,
We hope you can join us for our special AMATH seminar on **Thursday**
February 4th.
Speaker: Benjamin Peherstorfer, MIT
Time: February 4th, 16h00
Location: SMI 102
Title: Data-driven multi-fidelity methods for uncertainty quantification
Abstract
-----------
Quantifying uncertainty in systems described by partial differential
equations (PDEs) typically requires solving the PDEs many times for
different realizations of the stochastic parameters. Solving the PDEs for
thousands or even millions of parameter realizations is often intractable.
A common remedy is to replace the high-fidelity model (system of equations)
stemming from the discretization of the PDEs with a reduced model that
provides low-cost approximations of the PDE solutions; however, reduced
models induce an error into the overall result that typically leads to the
loss of accuracy guarantees for the statistics of interest (often the error
cannot even be quantified). We introduce multi-fidelity methods that
combine, instead of replace, the high-fidelity model with reduced
models---to increase the accuracy of the overall result and to ultimately
establish accuracy guarantees. We first present an online adaptive model
reduction approach that uses sparse data of the high-fidelity model to
adapt a reduced model while it is evaluated. Numerical results demonstrate
that our online adaptive reduced models achieve higher accuracies in
approximating nonlinear PDEs than static models. In the second part, we
introduce the multi-fidelity Monte Carlo method that combines the
high-fidelity model with reduced models and data-fit models to efficiently
estimate statistics of outputs of the high-fidelity model. Our
multi-fidelity method is guaranteed to provide unbiased estimates
("accuracy guarantees"). In our numerical experiments with linear and
nonlinear models from aerospace engineering, the multi-fidelity Monte Carlo
method achieves speedups by orders of magnitude compared to methods that
invoke a single high-fidelity or reduced model only.
Speaker webpage
------------------------
http://web.mit.edu/pehersto/www/
-------------- next part --------------
An HTML attachment was scrubbed...
URL:
From hetmaniu at uw.edu Wed Feb 3 13:19:21 2016
From: hetmaniu at uw.edu (Ulrich Hetmaniuk)
Date: Tue Jun 12 13:43:55 2018
Subject: [Amath-seminars] Feb. 4 - Special AMATH Seminar - Benjamin
Peherstorfer (MIT)
In-Reply-To:
References:
Message-ID:
Dear All,
Here is a kind reminder of Benjamin Peherstorfer's upcoming talk
Speaker: Benjamin Peherstorfer, MIT
Time: Thursday February 4th, 16h00
Location: SMI 102
Title: Data-driven multi-fidelity methods for uncertainty quantification
On Sun, Jan 31, 2016 at 3:19 PM, Ulrich Hetmaniuk wrote:
> Dear All,
>
> We hope you can join us for our special AMATH seminar on **Thursday**
> February 4th.
>
> Speaker: Benjamin Peherstorfer, MIT
> Time: February 4th, 16h00
> Location: SMI 102
>
> Title: Data-driven multi-fidelity methods for uncertainty quantification
>
> Abstract
> -----------
> Quantifying uncertainty in systems described by partial differential
> equations (PDEs) typically requires solving the PDEs many times for
> different realizations of the stochastic parameters. Solving the PDEs for
> thousands or even millions of parameter realizations is often intractable.
> A common remedy is to replace the high-fidelity model (system of equations)
> stemming from the discretization of the PDEs with a reduced model that
> provides low-cost approximations of the PDE solutions; however, reduced
> models induce an error into the overall result that typically leads to the
> loss of accuracy guarantees for the statistics of interest (often the error
> cannot even be quantified). We introduce multi-fidelity methods that
> combine, instead of replace, the high-fidelity model with reduced
> models---to increase the accuracy of the overall result and to ultimately
> establish accuracy guarantees. We first present an online adaptive model
> reduction approach that uses sparse data of the high-fidelity model to
> adapt a reduced model while it is evaluated. Numerical results demonstrate
> that our online adaptive reduced models achieve higher accuracies in
> approximating nonlinear PDEs than static models. In the second part, we
> introduce the multi-fidelity Monte Carlo method that combines the
> high-fidelity model with reduced models and data-fit models to efficiently
> estimate statistics of outputs of the high-fidelity model. Our
> multi-fidelity method is guaranteed to provide unbiased estimates
> ("accuracy guarantees"). In our numerical experiments with linear and
> nonlinear models from aerospace engineering, the multi-fidelity Monte Carlo
> method achieves speedups by orders of magnitude compared to methods that
> invoke a single high-fidelity or reduced model only.
>
>
> Speaker webpage
> ------------------------
> http://web.mit.edu/pehersto/www/
>
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL:
From hetmaniu at uw.edu Mon Feb 8 10:37:16 2016
From: hetmaniu at uw.edu (Ulrich Hetmaniuk)
Date: Tue Jun 12 13:43:55 2018
Subject: [Amath-seminars] Feb. 11 - Special AMATH Seminar - Weiwei Hu (IMA)
Message-ID:
Dear All,
We hope you can join us for our special AMATH seminar on **Thursday**
February 11th.
Speaker: Weiwei Hu, IMA
Time: February 11th, 16h00
Location: DEM 004
Title: Controlling a Thermal Fluid: Theoretical and Computational Issues
Abstract
-----------
We first discuss the problem of designing a feedback law which locally
stabilizes a two dimensional thermal fluid modeled by the Boussinesq
equations. The investigation of stability for a fluid flow in the natural
convection problem is important in the theory of hydrodynamical stability.
The challenge of stabilization of the Boussinesq equations arises from the
stabilization of the Navier-Stokes equations and its coupling with the
convection-diffusion equation for temperature. In particular, given a
steady state solution on a bounded and connected domain, we show that a
finite number of controls acting on a part of the boundary through
Neumann/Robin boundary conditions is sufficient to stabilize the full
nonlinear equations in the neighborhood of this steady state solution.
Dirichlet boundary conditions are imposed on the rest of the boundary.
Moreover, we prove that a stabilizing feedback control law can be obtained
based on the state estimators by solving an extended Kalman filter
problem for the linearized Boussinesq equations. A reduced order model is
used to construct a finite dimensional estimator. Numerical results are
provided to illustrate the idea. In the end, we discuss the problem of
well-posedness and control designs for the Boussinesq equations with zero
diffusivity and its application to optimal mixing and stirring.
Speaker webpage
------------------------
http://www.ima.umn.edu/~weiwei/
-------------- next part --------------
An HTML attachment was scrubbed...
URL:
From hetmaniu at uw.edu Wed Feb 10 16:24:46 2016
From: hetmaniu at uw.edu (Ulrich Hetmaniuk)
Date: Tue Jun 12 13:43:55 2018
Subject: [Amath-seminars] Feb. 11 - Special AMATH Seminar - Weiwei Hu
(IMA)
In-Reply-To:
References:
Message-ID:
Dear All,
Here is a kind reminder of Weiwei Hu's upcoming talk
Speaker: Weiwei Hu, IMA
Time: Thursday February 11th, 16h00
Location: DEM 004
Title: Controlling a Thermal Fluid: Theoretical and Computational Issues
>
> Abstract
> -----------
> We first discuss the problem of designing a feedback law which locally
> stabilizes a two dimensional thermal fluid modeled by the Boussinesq
> equations. The investigation of stability for a fluid flow in the natural
> convection problem is important in the theory of hydrodynamical stability.
> The challenge of stabilization of the Boussinesq equations arises from the
> stabilization of the Navier-Stokes equations and its coupling with the
> convection-diffusion equation for temperature. In particular, given a
> steady state solution on a bounded and connected domain, we show that a
> finite number of controls acting on a part of the boundary through
> Neumann/Robin boundary conditions is sufficient to stabilize the full
> nonlinear equations in the neighborhood of this steady state solution.
> Dirichlet boundary conditions are imposed on the rest of the boundary.
> Moreover, we prove that a stabilizing feedback control law can be obtained
> based on the state estimators by solving an extended Kalman filter
> problem for the linearized Boussinesq equations. A reduced order model is
> used to construct a finite dimensional estimator. Numerical results are
> provided to illustrate the idea. In the end, we discuss the problem of
> well-posedness and control designs for the Boussinesq equations with zero
> diffusivity and its application to optimal mixing and stirring.
>
>
> Speaker webpage
> ------------------------
> http://www.ima.umn.edu/~weiwei/
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL:
From hetmaniu at uw.edu Thu Feb 11 15:00:25 2016
From: hetmaniu at uw.edu (Ulrich Hetmaniuk)
Date: Tue Jun 12 13:43:55 2018
Subject: [Amath-seminars] Tuesday Feb. 16 - Special AMATH Seminar - Shishi
Luo (UCB)
Message-ID:
Dear All,
We hope you can join us for our special AMATH seminar on **Tuesday**
February 16th.
Speaker: Shishi Luo, UCB
Time: February 16th, 16h00
Location: DEM 004 (Dempsey Hall)
Title: Mathematical biology in the genomics era
Abstract
-----------
Biology is becoming increasingly quantitative, with large genomic datasets
being curated at a rapid rate. Both theoretical and data-driven approaches
are required to take advantage of these newly available datasets. I will
describe two projects in the field of evolutionary biology that span the
spectrum of these approaches. The first project is the development and
analysis of a Markov chain model of natural selection acting at two scales.
Simulations of the stochastic process as well as analysis of the scaling
limit lead to general properties of this complex evolutionary phenomenon.
The second project is a bioinformatics pipeline that identifies gene copy
number variants, currently a difficult problem in modern genomics. Using
hierarchical clustering to define a reference set of genes, we can
represent inter-individual variation in gene copy number in a tractable
form. This quantification of copy number variation in turn generates new
mathematical modeling questions that require the type of approach described
in the first part of my talk.
Speaker webpage
------------------------
https://szluo.wordpress.com/
-------------- next part --------------
An HTML attachment was scrubbed...
URL:
From hetmaniu at uw.edu Mon Feb 15 15:56:58 2016
From: hetmaniu at uw.edu (Ulrich Hetmaniuk)
Date: Tue Jun 12 13:43:55 2018
Subject: [Amath-seminars] Tuesday Feb. 16 - Special AMATH Seminar -
Shishi Luo (UCB)
In-Reply-To:
References:
Message-ID:
Dear All,
Here is a kind reminder about Shishi Luo's presentation on Tuesday Feb.
16th at 16h00 in Dempsey Hall DEM 004.
Speaker: Shishi Luo, UCB
Time: February 16th, 16h00
Location: DEM 004 (Dempsey Hall)
Title: Mathematical biology in the genomics era
> Abstract
> -----------
> Biology is becoming increasingly quantitative, with large genomic datasets
> being curated at a rapid rate. Both theoretical and data-driven approaches
> are required to take advantage of these newly available datasets. I will
> describe two projects in the field of evolutionary biology that span the
> spectrum of these approaches. The first project is the development and
> analysis of a Markov chain model of natural selection acting at two scales.
> Simulations of the stochastic process as well as analysis of the scaling
> limit lead to general properties of this complex evolutionary phenomenon.
> The second project is a bioinformatics pipeline that identifies gene copy
> number variants, currently a difficult problem in modern genomics. Using
> hierarchical clustering to define a reference set of genes, we can
> represent inter-individual variation in gene copy number in a tractable
> form. This quantification of copy number variation in turn generates new
> mathematical modeling questions that require the type of approach described
> in the first part of my talk.
>
> Speaker webpage
> ------------------------
> https://szluo.wordpress.com/
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL:
From pmaia at u.washington.edu Thu Mar 10 11:37:52 2016
From: pmaia at u.washington.edu (pmaia@u.washington.edu)
Date: Tue Jun 12 13:43:55 2018
Subject: [Amath-seminars] (reminder) Boeing Distinguished Colloquium:
Emmanuel Candes (Stanford), Today, @4pm in SMI 102
Message-ID:
Dear all,
Please join us at our Boeing Distinguished Colloquia today.
________________________________________________________________________________
Boeing Distinguished Colloquia
Emmanuel Candes (Stanford)
Place: Smith 102 at 4:00pm
Title: Beyond Compressed Sensing: The Effectiveness of Convex Programming in the Information and Physical Sciences
This talk discusses three concrete problems characterized by incomplete information about an object of interest. The first is the century-old phase retrieval problem where intensity-only measurements ? phase information is completely missing ? are available about an image as in X-ray crystallography, and we wish to recover the phase. The second is the super-resolution problem where one can only observe the low-frequencies of a signal and/or image due to physical laws, and wish to recover the high-end of its spectrum as to ?beat? the diffraction limit?. The third is a problem in data analysis and computer vision, where we observe only a few entries in a data matrix ? for instance, users? preferences for a collection of items ? which may have been further corrupted, and we wish to infer reliably all the missing and corrupted entries. To retrieve what seems lost, we describe three simple solutions with a common theme, namely, the use of ideas from convex progra!
mming. We present some theory explaining when one can and cannot expect these methods to provide accurate answers, as well as some applications.
________________________________________________________________________________
From amathsys at uw.edu Thu Mar 10 11:51:12 2016
From: amathsys at uw.edu (AMATH Sysadmin)
Date: Tue Jun 12 13:43:55 2018
Subject: [Amath-seminars] Fwd: (reminder) Boeing Distinguished Colloquium:
Emmanuel Candes (Stanford), Today, @4pm in SMI 102
In-Reply-To:
References:
Message-ID:
---------- Forwarded message ----------
From: Pedro Maia
Date: Thu, Mar 10, 2016 at 11:05 AM
Subject: (reminder) Boeing Distinguished Colloquium: Emmanuel Candes
(Stanford), Today, @4pm in SMI 102
To: amath-seminar@u.washington.edu, amath-local@amath.washington.edu,
Donsub Rim , Applied Mathematics Sysadmin <
amathsys@uw.edu>
Dear all,
Please join us at our Boeing Distinguished Colloquia today.
*________________________________________________________________________________*
*Boeing Distinguished Colloquia*
*Emmanuel Candes (Stanford)*
Place: Smith 102 at 4:00pm
Title: Beyond Compressed Sensing: The Effectiveness of Convex Programming
in the Information and Physical Sciences
This talk discusses three concrete problems characterized by incomplete
information about an object of interest. The first is the century-old phase
retrieval problem where intensity-only measurements ? phase information is
completely missing ? are available about an image as in X-ray
crystallography, and we wish to recover the phase. The second is the
super-resolution problem where one can only observe the low-frequencies of
a signal and/or image due to physical laws, and wish to recover the
high-end of its spectrum as to ?beat? the diffraction limit?. The third is
a problem in data analysis and computer vision, where we observe only a few
entries in a data matrix ? for instance, users? preferences for a
collection of items ? which may have been further corrupted, and we wish to
infer reliably all the missing and corrupted entries. To retrieve what
seems lost, we describe three simple solutions with a common theme, namely,
the use of ideas from convex programming. We present some theory explaining
when one can and cannot expect these methods to provide accurate answers,
as well as some applications.
*________________________________________________________________________________*
--
Ben Lansdell and Donsub Rim
Applied Mathematics Systems Administrators
amathsys@uw.edu
-------------- next part --------------
An HTML attachment was scrubbed...
URL: