Today's Editor:
Alex Townsend
Cornell University
townsend@cornell.edu
Today's Topics:
Howard Elman 1954 - 2025
SIAM Activity Group on Imaging Science Best Paper and Early Career Prizes
New release of OptimalControl.jl
Call for submissions - Section S17 at GAMM Annual Meeting 2026 in Stuttgart
ICCHA 2026 (May 18–22, Vanderbilt): CHA, OT, ML — CFP & Posters
SIAM Conference on Optimization, Edinburgh, June 2026
Postdoctoral Appointments, Scripps Institution of Oceanography, UCSD
Postdoc positions in Scientific Machine Learning, MOX - Politecnico di Milano
Postdoc Position at The Brazilian Synchrotron Light Laboratory
Lectureship In Applied Mathematics at Witwatersrand in Johannesburg
Faculty Positions in Scientific Machine Learning and AI for Science, UT Austin
University of Toronto - Assistant Professor, Teaching Stream
Faculty Positions, Mathematics, UC, Chile
Assistant Professor position in Data Science at the University of New Mexico
Contents, AIMS New Volume: CAC Vol. 5
Contents, AIMS New Issue: PUQR 10-3
Contents, AIMS New Volume: ACSE Vol. 5
Contents, AIMS New Article: ACSE Vol. 5, Art. 4
Contents, AIMS New Issue: FoDS 7-4
Contents & call, Adv. Comput. Math. (ACOM), Vol. 51, Issue 4, 2025
Call for papers “Computational Methods in Structural Optimization”
See this issue of NA Digest on the web at:
https://na-digest.coecis.cornell.edu/na-digest-html/25/v25n40.html
Submissions, FAQs, and archives:
https://na-digest.coecis.cornell.edu/
-------------------------------------------------------
From: Alison Ramage A.Ramage@strath.ac.uk
Date: September 29, 2025
Subject: Howard Elman 1954 - 2025
Howard Elman passed away on 18th September 2025 in Philadelphia. He was
71.
Howard was born in Queens, New York. He attended Stuyvesant High School
and Columbia University where he studied (mostly pure) mathematics. His PhD
in computer science at Yale was supervised by Martin Schultz. In his highly
cited thesis, Howard proved the still widely-used convergence bound for
GMRES that bears his name ("the Elman bound"). The Yale group was a hotbed
of analysis of iterative methods at that time, influenced in part by interests and
developments in the oil industry. After three further years as a research
associate at Yale, he took up a faculty position in the Computer Science
Department at the University of Maryland, College Park in 1985. This was to be
his academic home for the rest of his long career.
Early on he had fruitful collaborations with colleagues in the Mathematics
Department, in particular with the finite element pioneer, Ivo Babuska as well
as with his departmental colleague Dianne O'Leary; Gene Golub from Stanford
was also a big influence and strong supporter. His first sabbatical in 1992/3
was spent at Stanford and at Manchester in the UK. His collaborations with the
three of us led in time to the Oxford University Press monograph "Finite
Elements and Fast Iterative Solvers" and to the widely used Incompressible
Flow and Iterative Solver Software (IFISS). He had ongoing collaborations with
the National Labs, in particular with the group of John Shadid at Sandia in New
Mexico and with Ray Tuminaro at Livermore. Building on his background in
PDEs and linear algebra, Howard was also a pioneering figure in the nascent
field of uncertainty quantification.
For many years, Howard was the co-organiser of the biennial Copper Mountain
conferences on Iterative Methods in Colorado. He had 21 doctoral students
and supported SIAM in many positions, playing a leading role in finance and
science policy as well as serving as Editor in Chief for the SIAM Journal on
Scientific Computing and as Vice-President for Publications, a position he held
until shortly before his death.
Howard was a valued colleague, collaborator, mentor and friend to many and
will be sorely missed.
Alison Ramage, David Silvester and Andy Wathen
-------------------------------------------------------
From: Kui Ren kr2002@columbia.edu
Date: September 27, 2025
Subject: SIAM Activity Group on Imaging Science Best Paper and Early Career Prizes
Dear Colleagues,
SIAM Activity Group on Imaging Science invites nominations for its best paper
prize and early career prize, to be presented at the 2026 SIAM Conference on
Imaging Science. The nomination deadline is October 15, 2025. The details of the
nomination procedure can be found at:
https://www.siam.org/programs-initiatives/prizes-awards/activity-group-
prizes/siam-activity-group-on-imaging-science-best-paper-prize/
and
https://www.siam.org/programs-initiatives/prizes-awards/activity-group-
prizes/siam-activity-group-on-imaging-science-early-career-prize/
We appreciate your help in spreading the information and nominating the best
candidates for the prizes.
Thank you.
Best regards,
Gabriele Steidl, Kui Ren, Yifei Lou, Fatma Terzioglu
-------------------------------------------------------
From: Caillau, Jean-Baptiste jean-baptiste.caillau@univ-cotedazur.fr
Date: September 30, 2025
Subject: New release of OptimalControl.jl
It is a pleasure to announce the new release of OptimalControl.jl (v1.1).
Intended to solve optimal control problems on ODEs, the package features:
- a friendly DSL
- both direct (optimisation) and indirect (aka. shooting) methods
- solving on GPU
- a bunch of examples: tutorials, applications and collection of problems
More details here: https://discourse.julialang.org/t/ann-new-release-of-
optimalcontrol-jl/132764
-------------------------------------------------------
From: Marcel Schweitzer marcel@uni-wuppertal.de
Date: September 30, 2025
Subject: Call for submissions - Section S17 at GAMM Annual Meeting 2026 in Stuttgart
Dear Colleagues,
The 96th Annual Meeting of the International Association of Applied
Mathematics and Mechanics (GAMM) will be hosted at the University of
Stuttgart March 16 - 20, 2026 in Stuttgart, Germany.
On behalf of the organizing committee, we would like to invite you, your
colleagues, postdocs, and graduate students to join
Section S17: APPLIED AND NUMERICAL LINEAR ALGEBRA
The topical speakers of the session are Maike Meier (University of Groningen)
and Patrick Kürschner (HTWK Leipzig).
Contributed talks in this session will have a length of 15 minutes plus 5 minutes
for discussion. Once the abstracts have been received, depending on the
number of submissions and allowed time slots, we may have to select an
appropriate number of abstracts for presentations.
For more detailed information concerning the submission of abstracts as well
as registration and accommodation, please visit the conference website at
https://jahrestagung.gamm.org/annual-meeting-2026/96th-annual-meeting-2/
Deadline for abstract submission is December 8, 2025.
Deadline for early online registration is January 22, 2026.
Online registration will close on March 1, 2026.
Please note that we cannot provide any financial support or exceptions from
the registration fee for participants.
We are looking forward to welcoming you in Stuttgart. Please let us know if you
have any questions regarding the organization of the Section.
Jemima Tabeart, TU Eindhoven, NL (j.m.tabeart@tue.nl)
Marcel Schweitzer, Bergische Universität Wuppertal (marcel@uni-wuppertal.de)
(Section Organizers S17)
-------------------------------------------------------
From: Akram Aldroubi akram.aldroubi@vanderbilt.edu
Date: September 30, 2025
Subject: ICCHA 2026 (May 18–22, Vanderbilt): CHA, OT, ML — CFP & Posters
ICCHA 2026 — Computational Harmonic Analysis & Applications (May 18–22,
2026, Vanderbilt University, Nashville). Together with the 38th Annual Shanks
Lecture by Yann LeCun (NYU & Meta AI). Plenaries (50 min): Joan Bruna,
Robert McCann, Felix Kramer, Kasso Okoudjou, Dongbin Xu, Ozgur Yilmaz.
Main talks (40 min): Alex Cloninger, Sui Tang, Azita Mayeli, Caroline
Moosmüller. Topics include wavelets/scattering, frames, sampling & dynamical
sampling, optimal transport/Wasserstein geometry, and analysis-informed deep
models (CNNs/GNNs/diffusion). Invited (30 min), contributed, and posters.
Details: https://my.vanderbilt.edu/iccha2026/
-------------------------------------------------------
From: John Pearson j.pearson@ed.ac.uk
Date: October 03, 2025
Subject: SIAM Conference on Optimization, Edinburgh, June 2026
The call for participation for the SIAM Conference on Optimization (OP26)
(https://www.siam.org/conferences-events/siam-conferences/op26/) in
Edinburgh is now open!
**June 2-5 2026, University of Edinburgh, UK**
Submission Deadlines:
Minisymposium Proposal Submissions: October 16, 2025 (11:59 p.m. Eastern
Time)
Contributed Lecture and Minisymposium Presentation Abstracts: November
13, 2025 (11:59 p.m. Eastern Time)
SIAM Student Travel Award and Early Career Travel Award:
Travel Fund Application Deadline: March 2, 2026
For detailed submission information, see https://www.siam.org/conferences-
events/siam-conferences/op26/submissions/.
The SIAM Conference on Optimization is the conference of the SIAM Activity
Group on Optimization (https://siagoptimization.github.io/). The SIAM
Conference on Optimization showcases the latest research in the theory,
algorithms, software, and applications of optimization. It brings together
mathematicians, operations researchers, computer scientists, engineers,
software developers, and practitioners, fostering an ideal environment for
exchanging new ideas and addressing significant challenges.
**Invited presentations**
Radu Ioan Bot, University of Vienna, Austria
Andrea Lodi, Cornell Tech University, U.S.
Ruth Misener, Imperial College London, UK
Laura Sanità, Bocconi University, Italy
Ruoyu Sun, Chinese University of Hong Kong, China
Stefan M. Wild, Lawrence Berkeley National Laboratory, U.S.
**Minitutorials**
**Performance and computer-added analyses of optimization methods**
François Glineur, UCLouvain, Belgium
Adrien B. Taylor, INRIA, France
**Fair and interpretable resource allocation and machine learning**
Phebe Vayanos, University of Southern California, U.S.
**Organizing committee co-chairs**
Miguel Anjos, University of Edinburgh, UK
Gabriele Eichfelder, Technische Universität Ilmenau, Germany
Luis Nunes Vicente, Lehigh University, U.S.
**Local Organizing committee co-chairs**
Lars Schewe, University of Edinburgh, UK
Miguel Anjos, University of Edinburgh, UK
-------------------------------------------------------
From: Matthias Morzfeld mmorzfeld@ucsd.edu
Date: October 01, 2025
Subject: Postdoctoral Appointments, Scripps Institution of Oceanography, UCSD
Green Foundation Postdoctoral Appointments in Geophysics
The Institute of Geophysics and Planetary Physics (IGPP) at the Scripps
Institution of Oceanography, University of California San Diego, has openings
starting in 2026 for up to two postdoctoral Green Scholars and one Miles
Postdoctoral Fellow.
Application Deadline: Sunday, Nov 9, 2025 at 11:59pm (Pacific Time)
Further Details: https://igpp.ucsd.edu/about/green-foundation/postdoctoral-
scholarships
Apply here: https://apol-recruit.ucsd.edu/JPF04363
Green Scholar positions are 50% supported by funding from the Green
Foundation for Earth Sciences, matched with extramural funds for specific
research projects. Miles Fellows are 100% supported by the Green
Foundation for Earth Sciences.
Before submitting an application, applicants should contact potential IGPP
mentors to find out if they have a suitable project. Scholars are encouraged
to broaden their experience through interaction with other researchers at
IGPP; individual research goals may be pursued if project progress can be
maintained. Information on recent IGPP research is available at
https://igpp.ucsd.edu/about.
The positions are for one year, renewable for a second year subject to
satisfactory performance and availability of funds. Starting salary is
$75,000/yr plus benefits, along with $3,000/yr of discretionary research
funds.
Please address questions to greenfound@ucsd.edu.
The University of California is an Equal Opportunity Employer. All qualified
applicants will receive consideration for employment without regard to race,
color, religion, sex, sexual orientation, gender identity, national origin,
disability, age, protected veteran status, or other protected status under
state or federal law.
-------------------------------------------------------
From: Francesco Regazzoni francesco.regazzoni@polimi.it
Date: October 01, 2025
Subject: Postdoc positions in Scientific Machine Learning, MOX - Politecnico di Milano
Postdoctoral positions at MOX Laboratory, Department of Mathematics,
Politecnico di Milano (Italy), funded by the FIS (Italian Science Fund) Starting
Grant (1.3 M€, P.I. Francesco Regazzoni) “SYNERGIZE: Synergizing Numerical
Methods and Machine Learning for a new generation of computational models.”
The successful candidates will contribute to the development of novel
methodologies at the intersection of Numerical Analysis and Machine Learning.
The research aims to:
- Bridge Numerical Methods and Machine Learning to create reliable methods
integrating physics with data while maintaining theoretical soundness.
- Design Machine Learning based solvers for differential problems, significantly
reducing computational costs and environmental impact.
- Enhance the reliability, interpretability, and applicability of Machine Learning in
Scientific Computing.
A strong background in Computational Sciences or Scientific Machine Learning is
required. Candidates should have a Ph.D. in Applied Mathematics or a related
field. Duration: 24-36 months
Contact: Francesco Regazzoni (francesco.regazzoni@polimi.it) for more
information.
-------------------------------------------------------
From: Elias Salomão Helou Neto elias@icmc.usp.br
Date: October 01, 2025
Subject: Postdoc Position at The Brazilian Synchrotron Light Laboratory
The Brazilian Synchrotron Light Laboratory (LNLS/CNPEM), in collaboration
with the Institute of Mathematics and Computer Sciences (ICMC-USP, São
Carlos), invites applications for a postdoctoral fellowship in the project:
“Tomogram restoration without reconstruction”: Tomographic reconstruction
from projections is a central problem in computational imaging, with critical
applications at the SIRIUS and ORION facilities of CNPEM (Brazilian Center
for Research in Energy and Materials). In these experimental environments,
data are often acquired under limited-angle configurations and are affected
by micrometer-scale drifts between successive projections. These drifts
introduce inconsistencies in the measured sinogram, making it unsuitable for
conventional reconstruction methods without a prior alignment step.
However, existing alignment techniques typically rely on interpolation, which
degrades resolution and compromises quantitative analyses. This work
proposes a mathematical framework for sinogram alignment based on
consistency conditions derived from the Radon transform. By modeling the
measured tomogram as a geometrically perturbed version of an ideal one, we
formulate an inverse problem that seeks the optimal alignment parameters
minimizing the violation of generalized moment constraints. These
constraints are combined with a constrained optimization formulation that
admits analytical and efficient solutions. Our method enables resolution-
preserving alignment of tomographic data and is particularly well-suited for
limited-angle configurations and high-resolution imaging techniques such as
Tomo-Ptychography. The proposed approach readily applies to SIRIUS
beamlines, supporting a more standardized and accurate tomographic
workflow across experimental stations.
Fellowship Details
Stipend: 12,000 BRL per month
Duration: 12 months
Possible extension: up to 12 additional months
Starting date: as soon as possible (November or December 2025)
Location: LNLS/CNPEM (Campinas, Brazil), in collaboration with ICMC-USP
(São Carlos, Brazil)
Candidate Profile
PhD in Applied Mathematics, Computational Physics, Data Science,
Electrical Engineering, Computer Science, or related fields.
Background in signal and image processing, inverse problems, and/or
regularization methods.
Strong programming skills (Python, C/C++, or similar).
Previous experience with tomography or machine learning will be
considered an asset.
-------------------------------------------------------
From: Montaz Ali montaz.ali@wits.ac.za
Date: September 30, 2025
Subject: Lectureship In Applied Mathematics at Witwatersrand in Johannesburg
The School of Computer Science and Applied Mathematics is a vibrant teaching
and research-intensive department, home to several South African National
Research Foundation (NRF)-rated scientists. We are seeking to appoint two
dynamic and innovative Lecturers in Applied Mathematics to contribute to
our high-quality research and teaching mission, with a commitment to
achieving a synergistic balance between research and teaching excellence.
Our School is deeply committed to excellence in teaching and learning. We
deliver core, large-class Applied Mathematics courses to a diverse body of
students from the Faculties of Science, Engineering,
and Commerce. This role is central to providing these students with a rigorous,
engaging, and supportive foundation for their academic careers.
Our Applied Mathematics research strengths include symmetry methods of
differential equations, mathematical modelling, mathematical biology, control
theory, optimisation, numerical methods and analysis, scientific computing, and
continuum and fluid mechanics. We are particularly interested in candidates
whose research will complement and strengthen these existing areas.
Responsibilities - The successful candidate will be expected to:
• Develop and teach undergraduate and Honours courses in Applied
Mathematics. The ability to teach in core areas such as Numerical Methods,
Scientific Computing, and Mathematical Methods and Modelling is essential.
• Supervise and/or co-supervise postgraduate students at Honours, Masters,
and PhD level.
• Develop and maintain a productive and active research profile.
• Contribute to the academic administration and collective life of the School,
Faculty, and University.
Minimum Requirements
• A PhD in Applied Mathematics or a closely related field. New PhD graduates
are encouraged to apply.
• Some tertiary teaching experience in Applied Mathematics, with a strong
interest in pedagogical
development and a commitment to teaching innovation.
• A developing research record, evidenced by publications in accredited
journals and a clear future research plan.
• The ability to teach a range of courses at undergraduate and Honours levels.
Desirable Criteria - We are particularly interested in candidates who can
demonstrate:
• Excellence in teaching, evidenced by effective practice and a passion for
pedagogical innovation, particularly in the context of large-class settings.
• A strong aptitude for curriculum development, digital pedagogy, and other
transformative learning strategies that directly enhance student learning
outcomes. The successful candidate will also have the exciting opportunity to
contribute to the newly established Wits Academy for Mathematical Pedagogy,
Learning and Innovation for First-Year (AMPLIFY). This pioneering unit is central
to the Faculty’s commitment to transforming learning and teaching in large first
year courses in Mathematics and Applied Mathematics and enhancing
foundational student support.
How to Apply - Please submit the following documents:
• A detailed cover letter.
• A comprehensive and updated academic curriculum vitae (max. 3 pages).
• A teaching portfolio (max. 5 pages), articulating a teaching philosophy,
evidence of practice
through examples, and a description of specific teaching innovations
implemented and their
impact on student learning.
• A statement of research interests (max. 5 pages), comprising a critical review
of past work, a
future research plan with consideration for funding opportunities, and a
discussion of alignment
with the School’s research profile.
• Certified copies of all educational qualifications and ID document or passport.
• The names and email contact details of three referees
Closing Date: 13th October, 2025
-------------------------------------------------------
From: Omar Ghattas omar@oden.utexas.edu
Date: September 27, 2025
Subject: Faculty Positions in Scientific Machine Learning and AI for Science, UT Austin
The Oden Institute for Computational Engineering and Sciences and the
College of Natural Sciences at The University of Texas at Austin invite
applications for two tenured or tenure-track faculty positions beginning Fall
2026 in the area of Scientific Machine Learning and AI for Science.
One of the faculty positions is joint between the Oden Institute and either the
Department of Computer Science or the Department of Mathematics, with split
teaching responsibilities between Oden and the appropriate department. For
more information and to apply for this position, see
https://apply.interfolio.com/174445.
The other position is joint between the Oden Institute and the Department of
Statistics and Data Sciences, with split teaching responsibilities. For more
information and to apply for this position, see
https://apply.interfolio.com/174449.
-------------------------------------------------------
From: Ken Jackson krj@cs.toronto.edu
Date: September 26, 2025
Subject: University of Toronto - Assistant Professor, Teaching Stream
We're excited to announce that the University of Toronto's Department of
Computer Science has two faculty openings for Assistant Professor, Teaching
Stream. This is a unique opportunity to join a vibrant group of 21 teaching-
stream faculty and be part of a world-class computer science department. The
position is full-time with pathways to promotion to Associate Professor,
Teaching Stream and Full Professor, Teaching Stream.
Please encourage excellent candidates who are excited about a career in
teaching to apply by October 27, 2025. Details at:
https://academicjobsonline.org/ajo/jobs/30410
If you have questions about the position, feel free to contact Steve Engels
(sengels@cs.toronto.edu).
-------------------------------------------------------
From: Thomas Fuehrer thfuhrer@uc.cl
Date: September 26, 2025
Subject: Faculty Positions, Mathematics, UC, Chile
The Department of Mathematics of the Catholic University of Chile invites
applications for two full-time positions at the Assistant (tenure track) or
Associate Professor level, starting in March or August 2026.
Applications are accepted until November 14th, 2025. Details on
https://www.mathjobs.org/jobs/list/27012
-------------------------------------------------------
From: Monika Nitsche nitsche@unm.edu
Date: October 01, 2025
Subject: Assistant Professor position in Data Science at the University of New Mexico
The Department of Mathematics and Statistics at the University of New Mexico
invites applications for a full-time, tenure-track Assistant Professor position in
Data Science, with a start date of August 2026. Applicants must have a Ph.D. in
Mathematics, Statistics, Computer Science, or a closely related field by the
appointment start date.
The successful candidate will develop a strong independent research program
in one or more areas central to modern Data Science, such as: Optimization,
Machine Learning, Statistical Learning, Applied Probability, Graph Theory and
Network Science, or Computational Statistics, with opportunities for cross-
disciplinary collaboration across UNM and with national laboratories such as
Sandia National Laboratories.
The new faculty member will play a key role in developing and delivering core
courses in the concentration, such as:
- Introduction to Data Science
- Probability and Statistics for Data Science
- Optimization and Algorithms
- Data Mining and Machine Learning
- Capstone in Data Science
This hire will also support course needs in Applied or Pure Mathematics and
Statistics, strengthening the department’s capacity to serve diverse student
populations and client departments (e.g., Sociology, Psychology, Biology,
Economics, Political Science). By expanding our ability to deliver rigorous and
modern mathematical training, this position will enhance job placement for our
students and deepen interdepartmental and external partnerships.
This strategic hire is a cornerstone of our newly approved Data Science
Concentration, which integrates departmental strengths across Statistics (e.g.,
applied and Bayesian methods), Pure Mathematics (e.g., topological data
analysis), and Applied Mathematics (e.g., machine learning, scientific
computing, uncertainty quantification). The hire will support this high-impact,
interdisciplinary initiative, which positions our department as a campus leader
in modern data-driven education and research.
A complete application consists of:
• Cover letter (Applicants are encouraged to include 2–3 sentences on how
their teaching, research, or service may contribute to UNM’s mission to serve
diverse local and global communities.)
• Curriculum vitae
• Research statement
• Teaching statement
• A minimum of four letters of recommendation, including at least one
addressing teaching experience
For more about the department, visit http://www.math.unm.edu.
Letters of recommendation may be sent to Amy Hathaway at
ahathawa@unm.edu, or by mail to:
Search Committee – Data Science Position
Department of Mathematics and Statistics
MSC01 1115, 1 University of New Mexico
Albuquerque, NM 87131
-------------------------------------------------------
From: Charley Denton cdenton@aimsciences.org
Date: September 30, 2025
Subject: Contents, AIMS New Volume: CAC Vol. 5
Communications on Analysis and Computation
Volume: 5
September 2025
https://www.aimsciences.org/CAC/article/2025/5/0
Preface
Hongyu Liu and Dinh-Liem Nguyen
A monotonicity-based globalization of the level-set method for inclusion
detection
Bastian Harrach and Houcine Meftahi
Simultaneous estimation of piecewise constant coefficients in elliptic PDEs via
Bayesian level-set methods
Anuj Abhishek, Thilo Strauss and Taufiquar Khan
Using the Newton-Raphson method with Automatic Differentiation to
numerically solve the implied volatility of stock options via the Binomial model
Wanchaloem Wunkaew, Yuqing Liu and Kirill V. Golubnichiy
Recent progress in Carleman estimates for mean field games
Jingzhi Li and Tian Niu
Some new results on an inverse medium scattering problem
Nguyen Trung Thành and Gianluca Barone
Read more articles here:
https://www.aimsciences.org/CAC/article/2025/5/0
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From: Charley Denton cdenton@aimsciences.org
Date: September 30, 2025
Subject: Contents, AIMS New Issue: PUQR 10-3
Probability, Uncertainty and Quantitative Risk
Volume: 10 Issue: 3
2025
https://www.aimsciences.org/PUQR/article/2025/10/3
A maximum principle for robust optimal control problems of quadratic BSDEs
Tao Hao, Jiaqiang Wen and Qi Zhang
Optimal investment and consumption under logarithmic utility and uncertainty
model
Wahid Faidi
On limit theorems under the Shilkret integral
Pedro Terán
Asymptotic smiles for an affine jump-diffusion model
Nian Yao, Junfeng Lin and Zhiqiu Li
A class of quadratic reflected BSDEs with singular coefficients
Shiqiu Zheng, Lidong Zhang and Xiangbo Meng
Optimal stopping under model uncertainty in a general setting
Ihsan Arharas, Siham Bouhadou, Astrid Hilbert and Youssef Ouknine
-------------------------------------------------------
From: Charley Denton cdenton@aimsciences.org
Date: September 30, 2025
Subject: Contents, AIMS New Volume: ACSE Vol. 5
Advances in Computational Science and Engineering
Volume: 5
September 2025
https://www.aimsciences.org/ACSE/article/2025/5/0
Challenges in realizing 3rd generation multidisciplinary design optimization
Ihar Antonau, Suneth Warnakulasuriya, Susanna Baars, Ildar Baimuratov, Tim
Wittenborg, Lasse Kreuzeberg, Achyuth Attravanam and Roland Wüchner
Reduced order models for fluid flows at various Mach number solved using
discontinuous Galerkin method
Andrea Lario and Gianluigi Rozza
Enhanced low-dose CT image reconstruction by domain and task shifting
gaussian denoisers
Tim Selig, Thomas März, Martin Storath and Andreas Weinmann
A parameter-driven physics-informed neural network framework for solving two-
parameter singular perturbation problems involving boundary layers
Pradanya Boro, Aayushman Raina and Srinivasan Natesan
Solving implicit inverse problems with homotopy-based regularization path
Davide Parodi, Federico Benvenuto, Sara Garbarino and Michele Piana
-------------------------------------------------------
From: Charley Denton cdenton@aimsciences.org
Date: September 29, 2025
Subject: Contents, AIMS New Article: ACSE Vol. 5, Art. 4
Advances in Computational Science and Engineering
Volume: 5, Article: 4
2025
https://www.aimsciences.org/ACSE/article/2025/5/0
A parameter-driven physics-informed neural network framework for solving two-
parameter singular perturbation problems involving boundary layers
Pradanya Boro, Aayushman Raina and Srinivasan Natesan
-------------------------------------------------------
From: Charley Denton cdenton@aimsciences.org
Date: September 29, 2025
Subject: Contents, AIMS New Issue: FoDS 7-4
Foundations of Data Science
Volume: 7, Article: 4
December 2025
https://www.aimsciences.org/FoDS/article/2025/7/4
Preface
Arnaud Doucet, Víctor Elvira, Fredrik Lindsten and Joaquín Miguez
Noise calibration for SPDEs: A case study for the rotating shallow water model
Dan Crisan, Oana Lang, Alexander Lobbe, Peter-Jan van Leeuwen and Roland
Potthast
An overview of differentiable particle filters for data-adaptive sequential Bayesian
inference
Xiongjie Chen and Yunpeng Li
Global convergence of optimized adaptive importance samplers
Omer Deniz Akyildiz
Sequential Monte Carlo bandits
Iñigo Urteaga and Chris H. Wiggins
Scalable Bayesian bi-level variable selection in generalized linear models
Younès Youssfi and Nicolas Chopin
An adaptive mixture view of particle filters
Nicola Branchini and Víctor Elvira
Read more articles here:
https://www.aimsciences.org/FoDS/article/2025/7/4
-------------------------------------------------------
From: Alex Barnett abarnett@flatironinstitute.org
Date: September 26, 2025
Subject: Contents & call, Adv. Comput. Math. (ACOM), Vol. 51, Issue 4, 2025
Call for papers in open collection:
Research Frontiers and Development Trends in Numerical Algebra
and Scientific Computing (NASC Conference 2025).
Editors: Zhong-Zhi Bai, Raymond H. Chan & Yu-Hong Ran
In Vol. 51, Issue 4:
An adaptive finite element DtN method for the acoustic-elastic
interaction problem in periodic structures
Lei Lin, Junliang Lv
Two-level discretization of the 3D stationary Navier–Stokes equations
with damping based on a difference finite element method
Qi Zhang, Pengzhan Huang
Exponential decay and numerical treatment for mixture problem with
Fourier law and frictional damping
Mauro L. Santos, Anderson J. A. Ramos, Anderson D. S. Campelo
Uniform error bounds of a nested Picard iterative integrator for the
Klein-Gordon-Zakharov system in the subsonic limit regime
Jiyong Li

Galerkin neural network-POD for acoustic and electromagnetic wave
propagation in parametric domains
Philipp Weder, Mariella Kast, Fernando Henríquez, Jan S. Hesthaven
Energy-stable and efficient finite element schemes for the Shliomis
model of ferrofluid flows
Guo-Dong Zhang, Kejia Pan, Xiaoming He, Xiaofeng Yang

On the injectivity of mean value mappings between quadrilaterals
Michael S. Floater, Georg Muntingh
A SUPG-stabilized virtual element method for the Navier–Stokes
equation: approximations of branches of non-singular solutions
Sudheer Mishra, E. Natarajan, Sundararajan Natarajan
Nonconforming virtual element method for general second-order
elliptic problems on curved domain
Yi Liu, Alessandro Russo
An orthonormal gradient flow for computing ground state solution of
two-dimensional dipolar fermion gas
Xuelin Zhang, Hanquan Wang
Solving elliptic optimal control problems via neural networks and
optimality system
Yongcheng Dai, Bangti Jin, Ramesh Chandra Sau, Zhi Zhou
A nonconforming P3+B4 and discontinuous P2 mixed finite element
on tetrahedral grids
Xuejun Xu, Shangyou Zhang
Decoupled weak Galerkin finite element method for Maxwell’s
equations
Wenya Qi, Kaifang Liu
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From: Molly Fu molly.fu@mdpi.com
Date: September 28, 2025
Subject: Call for papers “Computational Methods in Structural Optimization”
Dear Colleagues,
Advances in computational methods are increasingly shaping structural
optimization, driving innovations across civil and architectural engineering, as
well as in aerospace, mechanics, energy, offshore, manufacturing, robotics,
biomechanics, and cultural heritage. The demand for sustainable, resilient, and
high-performance systems requires advanced strategies that combine modern
computing with engineering design.
This Special Issue invites the submission of contributions that emphasize both
methodological progress and significant computing innovations. Alongside
case studies from engineering practice, we particularly welcome work that
introduces new algorithms, scalable numerical methods, surrogate modelling
strategies, AI-driven approaches, or advances in software and workflows,
including implementations of high-performance computing platforms such as
GPUs, cloud-based environments, open-source tools, and protocols that
ensure the reproducibility of results.
https://www.mdpi.com/journal/computation/special_issues/4464231K69
This Special Issue’s scope includes multi-objective, multidisciplinary, and
uncertainty-aware optimization; topology, shape, and material optimization
across scales; surrogate models, metamodeling, and data-driven approaches;
evolutionary, reinforcement learning and bio-inspired algorithms; digital twins;
real-time optimization and human-in-the-loop design; and multiscale and
multiphysics modelling. Application fields range from civil and bridge
engineering to aerospace and offshore structures, energy systems, robotics,
biomechanics, additive manufacturing, and the preservation and strengthening
of heritage constructions.
By emphasizing computational advances together with engineering
applications, this Special Issue aims to foster dialogue between researchers in
computing and engineering and to promote reproducible and scalable
approaches for the next generation of engineering design.
Dr. Laura Sardone
Prof. Dr. Giuseppe Carlo Marano
Prof. Dr. Rucheng Xiao
Dr. Beibei Xiong
Guest Editors
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End of Digest
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