Today's Editor:
David S. Bindel
Cornell University
bindel@cornell.edu
Today's Topics:
AIM, explained. Open problems and human understanding
Announcing the release of the MOLE 1.3.0 Library
FORUM Multiphysics: inspect PDE discretizations in a browser
New Book, Investment, Consumption, and Pricing in Constrained and Unbounded Markets
Call for submissions, Joint Annual Meeting of GAMM & DMV, Mar 2027
Mathematics and Image Analysis (MIA 2027), Berlin, 10-12 February 2027
Call for Applications: 2027 Gene Golub SIAM Summer School (June 14-25, 2027)
PhD position in Computer Science at NYU Shanghai
Postdoc: SciML and Numerical Weather Prediction, SFU, Canada
Postdoc positions in Computational Modeling at Morgan State University
Postdoc Position, John von Neumann Fellow, Sandia National Labs
Tenure Track Position at Southern Methodist University
Tenure-track Lerheden Assistant Professor position in Applied Mathematics at KTH
Contents, AIMS New Volume: AMMC Vol. 9
Contents, AIMS New Volume: EECT Vol. 26
Contents, AIMS New Volume: FMF Vol. 10
Call for papers, ACOM special issue, fast/integral eqns, Greengard 70th
See this issue of NA Digest on the web at:
https://na-digest.coecis.cornell.edu/na-digest-html/26/v26n40.html
Submissions, FAQs, and archives:
https://na-digest.coecis.cornell.edu/
-------------------------------------------------------
From: Matthew Colbrook mjc249@cam.ac.uk
Date: October 01, 2026
Subject: AIM, explained. Open problems and human understanding
We invite the numerical analysis community to explore AIM, a
public collection of open problems in applied mathematics, and
AIM, explained, a website devoted to explaining their mathematics.
The aim is to deepen human understanding: what is the question,
why does it matter, and which ideas, examples or known results
help us understand it? A new theorem or proof is not required.
An explanation of how mathematics clarifies an application can
be a complete contribution; applications are optional.
We welcome readable papers and videos of at most ten minutes.
Papers: Zenodo, arXiv or ResearchGate. Videos: YouTube or Vimeo.
Include a plain-text overview and, for videos, a transcript.
Different perspectives on the same problem are encouraged;
topics are not reserved, and being first brings no priority.
Contributions with or without AI assistance are equally welcome.
Please identify the source problem and credit the work you use.
The library is open to everyone. An optional
prize competition closes on 1 January 2027.
New open problems, corrections and partial results are also
welcome in the repository. See the website for full guidance.
Problem repository: https://github.com/MColbrook/AIM
Website: https://mathematics-explained.com
Steven L. Brunton, Matthew J. Colbrook, Maarten V. de Hoop,
George Stepaniants, Alex Townsend, and Rachel Ward
-------------------------------------------------------
From: Jose E Castillo jcastillo@sdsu.edu
Date: September 25, 2026
Subject: Announcing the release of the MOLE 1.3.0 Library
We are thrilled to announce a new release of the MOLE 1.3.0 library. The
MOLE Open-source Ecosystem implements high-order mimetic
operators in different programming languages. MOLE provides discrete
analogs of the most common vector calculus operators: Divergence,
Gradient, Curl, and Laplacian. These operators act on functions
discretized over staggered grids (uniform, nonuniform, and curvilinear),
and they satisfy local and global conservation laws. MOLE's operators
can be used to develop computationally efficient programs for solving
linear and nonlinear partial differential equations (PDEs) with higher
orders of accuracy than other methods.
MOLE v1.3.0 has been implemented in four different programming
languages; C++, Python, Julia and GNU Octave (100% compatible with
MATLAB).
Visit the MOLE website for more news and MOLE related events at: mole-
ose.org
For MOLE library documentation visit: mole-docs.readthedocs.io
To report any issues, please create a GitHub Issue on the MOLE library
repository https://urldefense.com/v3/__https://github.com/csrc-
sdsu/mole__;!!H7yp__TR!YDJLp04W3SVrgsPMsnL8qTtRhRcC_h3HgpMcnXj5K
IBbA6AcCZDxqvpiYCxx8Z1-Ah6SFw6gU9I8X2zAIpWyKtdKmBI$
-------------------------------------------------------
From: James james.c.din@gmail.com
Date: September 28, 2026
Subject: FORUM Multiphysics: inspect PDE discretizations in a browser
FORUM Multiphysics connects PDE models with their discretizations
in a browser. Learners can inspect node equations, boundary
formulas and sparse-matrix information alongside computed fields.
The browser edition needs no account or numerical server.
The workflow supports finite-difference and finite-element meshes
and examples such as heat conduction. It may help numerical-methods
instructors demonstrate the connection between a PDE, boundary
conditions and the assembled algebraic system.
Advanced coupled examples include reduced teaching models; this
announcement does not claim industrial validation or open-source
licensing. Product details and browser access:
https://www.multiphysics.us/forum/
Submitted by James on behalf of the FORUM Multiphysics team.
-------------------------------------------------------
From: Mitch Graham mgraham@siam.org
Date: September 29, 2026
Subject: New Book, Investment, Consumption, and Pricing in Constrained and Unbounded Markets
Investment, Consumption, and Pricing in Constrained and Unbounded Markets
by Ying Hu, Gechun Liang, Shanjian Tang
The monograph addresses three fundamental issues in a financial market:
investment, consumption, and pricing using the cutting-edge quadratic backward
stochastic differential equation (BSDE). The book provides an unprecedented
systematic application of the theory of quadratic BSDEs to general utility
maximization problems in constrained and unbounded financial markets. It also
includes the first treatment of general Epstein-Zin utility maximization problems
with portfolio constraints in a non-Markovian framework, marking significant
progress in the dynamic investment-consumption problems. This monograph
serves as an excellent entry point for research students and early-career
researchers in mathematical finance by offering a clear pathway into the field
with practical examples.
2026 / vi + 123 pages / Softcover / 978-1-61197-912-1 / List $59.00 / SIAM
Member $41.30 / FM03
Bookstore link:
https://epubs.siam.org/doi/book/10.1137/1.9781611979114
-------------------------------------------------------
From: Matthias Beckmann matthias.beckmann@uni-hamburg.de
Date: October 02, 2026
Subject: Call for submissions, Joint Annual Meeting of GAMM & DMV, Mar 2027
The upcoming joint annual meeting of GAMM (Gesellschaft für
Angewandte Mathematik und Mechanik) and DMV (Deutsche Mathematiker-
Vereinigung) will be held at Ulm University and Ulm University of
Applied Science (THU), Ulm, Germany, March 8-12, 2027. We are happy
to invite you to submit an abstract for section S21 'Mathematical
Signal and Image Processing.'
Over the last decades mathematics has become the cornerstone in
signal and image processing ranging from various methods for signal
reconstruction to modelling of imaging modalities over its
classical disciplines compression, denoising, segmentation, and
registration to feature extraction. The used methodologies include
such diverse fields as harmonic analysis, inverse problems,
variational analysis, mathematical statistics, partial differential
equations, optimization, approximation theory, sampling theory and
machine learning.
The aim of this section is to gather scientists working on the
theory and applications of mathematical signal and image processing
in order to present their research, exchange ideas, and start new
collaborations.
Important Dates:
* Deadline of abstract submission: December 1, 2026
* Closure of early online registration (Early fee): January 19,
2027
* Closure of online registration: March 5, 2027
Further information about the conference are available at https://
jahrestagung.gamm-ev.de.
We are looking forward to welcoming you in Ulm.
-------------------------------------------------------
From: Kostas Papafitsoros k.papafitsoros@qmul.ac.uk
Date: September 28, 2026
Subject: Mathematics and Image Analysis (MIA 2027), Berlin, 10-12 February 2027
The next edition of the Mathematics and Image Analysis (MIA 2027) conference
will be held in Berlin, 10-12 February 2027, continuing a successful and well-
established series of conferences held in previous years.
https://sites.google.com/view/mia2027
The conference will address a wide range of topics such as:
- Mathematics of novel imaging methods
- Inverse problems in imaging
- Mathematics of visualisation
- Motion analysis
- Video processing
- Statistical and data science aspects in image processing
- PDEs and variational methods in image processing
- Deep and other machine learning methods in imaging
The conference consists of 18 invited talks and a poster session.
Registration is free but mandatory (deadline: 18 December 2026)
https://sites.google.com/view/mia2027/registration
Looking forward to seeing you in Berlin!
The organising committee:
Bruno Galerne
Michael Hintermüller
Arthur Leclaire
Serena Morigi
Kostas Papafitsoros
Gabriele Steidl
Samuel Vaiter
-------------------------------------------------------
From: Yunhui He yhe43@central.uh.edu
Date: September 30, 2026
Subject: Call for Applications: 2027 Gene Golub SIAM Summer School (June 14-25, 2027)
Dear Graduate Students,
We are pleased to invite you to apply to the Gene Golub SIAM Summer School
2027 (G2S3) on Nonlinear Solvers and Preconditioning Techniques for
Multiphysics PDEs. The summer school will be held from June 14 to June 25,
2027, on the campus of Texas A&M University-Corpus Christi, USA. The two-
week school is designed for about 55 advanced international graduate
students. The Gene Golub SIAM Summer School is funded by a bequest of
Gene Golub to SIAM. We are pleased to provide travel and accommodation
support for all selected participants.
The summer school will feature lecture series by Professors Eric de Sturler
(Virginia Tech, USA), Chen Greif (The University of British Columbia, Canada),
Xiaozhe Hu (Tufts University, USA), and Scott MacLachlan (Memory University
of Newfoundland, Canada); see
https://sites.google.com/view/2027g2s3/lecturers
The program addresses a growing need for advanced training in nonlinear
solvers and preconditioning techniques for multiphysics partial differential
equations (PDEs), exposing participants to modern computational methods and
software tools that are essential for large-scale scientific computing. These
topics are often underrepresented in standard graduate curricula. The
internationally recognized instructional team will provide a curriculum
grounded in cutting-edge theory, algorithms, and software development.
Through the integration of Firedrake, participants will gain hands-on
experience implementing and analyzing state-of-the-art numerical methods,
strengthening their theoretical understanding and computational skills.
In addition to the lecture series, the program will include talks by special guests
(Dr. Robert Kirby, Baylor University, Dr. Xiaoye Sherry Li, Lawrence Berkeley
National Laboratory, and Dr. Jie Chen, MIT-IBM Watson AI Lab, IBM Research),
which connect the core material to high-performance computing, current
research challenges, and real-world applications. A special session dedicated to
Gene Golub's legacy will highlight his profound contributions to numerical
linear algebra, his lasting influence on the field, and his unwavering support of
young scientists.
The summer school is committed to showcasing and supporting graduate
students. We will host career panels and a Three-Minute Thesis-style
presentation session, providing students with opportunities to present their
research, develop communication skills, and engage with faculty and peers.
The call for applications will open on October 1, 2026, and close on January 8,
2027. Registration information and application details can be found on the
summer school website:
https://sites.google.com/view/2027g2s3/home
If you have any questions, please email G2S3SIAM2027@gmail.com.
We encourage you to apply and look forward to welcoming you to Texas A&M
University-Corpus Christi in June 2027.
Warm regards,
Yunhui He, Department of Mathematics, University of Houston
Alexey Sadovski, Department of Mathematics and Statistics, Texas A&M
University - Corpus Christi
Maria Vasilyeva, Department of Mathematics and Statistics, Texas A&M
University - Corpus Christi
Min Wang, Department of Mathematics, University of Houston
-------------------------------------------------------
From: Tyler Chen tyler.chen@nyu.edu
Date: September 26, 2026
Subject: PhD position in Computer Science at NYU Shanghai
I have an opening for a PhD student. The position isn't tied to a
particular project, but possible directions include:
- block Krylov methods/randomized numerical linear algebra
- applications of computing to the social sciences, humanities, and
arts
- students' own great idea
The CS PhD program is shared across NYU campuses, and students will
spend time in NYC and Shanghai: https://shanghai.nyu.edu/page/
computer-science-phd-program.
Questions can be directed to: tyler.chen@nyu.edu
-------------------------------------------------------
From: Steve Ruuth sruuth@sfu.ca
Date: September 30, 2026
Subject: Postdoc: SciML and Numerical Weather Prediction, SFU, Canada
Simon Fraser University's Department of Mathematics (Metro Vancouver)
invites applications for a postdoctoral position in hybrid scientific machine
learning and numerical weather prediction, focusing on the Canadian Arctic and
other regions with sparse observations. The fellow will work with Ben Adcock
and Steven Ruuth, collaborating with Environment and Climate Change Canada
through WxAlliance, funded by NSERC Alliance Society. Research may include
operator learning, active learning and numerical methods combining physical
equations with learned components. Topics will reflect your interests.
Applicants must hold a PhD by the start date in mathematics, applied
mathematics, computer science, atmospheric science, physics or a related
field. Strong research potential and scientific computing skills are essential;
weather prediction experience is not required. Candidates of all nationalities,
including those in Canada, may apply.
Salary: CAD $62,500 per year plus mandatory benefits. The initial 12-month
appointment is renewable for a second year, subject to satisfactory progress
and funding. Start: January 1-September 1, 2027, by agreement. Optional
teaching, up to one undergraduate course per year, is paid in addition to the
fellowship salary.
Apply through MathJobs: https://www.mathjobs.org/jobs/list/29084
Applications received by November 15, 2026 receive full consideration. See
MathJobs for required application materials and reference letters. Enquiries:
Ben Adcock (ben_adcock@sfu.ca) or Steven Ruuth (steven_ruuth@sfu.ca).
SFU is an equity employer and encourages applications from all qualified
candidates.
-------------------------------------------------------
From: Pilhwa Lee pilhwa.lee@morgan.edu
Date: September 30, 2026
Subject: Postdoc positions in Computational Modeling at Morgan State University
Postdoctoral Fellow #1) Computational Neuronal Circuitry & Endocrine
Modeling
Institution: Morgan State University, Baltimore, MD, USA
Project: Digital twins for the therapeutics of gestational diabetes (NIH-
funded: OTA-26-004)
Position Summary: We are seeking a highly motivated Postdoctoral Fellow to
contribute to the computational modeling of hypothalamic neuronal
excitability and metabolic adaptation as part of an NIH-funded digital twin
project. This research focuses on the complex neuronal networks modulated
by metabolic and placental hormones during pregnancy. The successful
candidate will drive a crucial phase of our multi-aim workflow, constructing
mechanistic models that capture how circulating hormones alter the
excitability of feeding circuitry to regulate glucose control and energy
balance across healthy, obese, and diabetic maternal cohorts.
Required Qualifications
* Ph.D. in Applied Mathematics, Mathematical Biology, Computational
Neuroscience, or a closely related discipline.
* Proven expertise in building mechanistic mathematical models of neuronal
excitability (e.g., Hodgkin-Huxley or network conductance models).
* Advanced proficiency in MATLAB/Python programming for computational
model development.
* Strong track record of independent research and peer-reviewed scientific
publications.
Preferred Qualifications
* Background in neuroendocrinology, hypothalamic circuitry, or metabolic
regulation (e.g., glucose homeostasis).
* Experience aligning complex computational models with variable clinical
datasets, such as blood titration data or hormone profiles.
* Ability to work in a collaborative, multi-disciplinary team setting
encompassing systems biology, genetics, and clinical data collection.
Postdoctoral Fellow #2) Computational Systems Biology
Institution: Morgan State University, Baltimore, MD, USA
Project: Digital twins for the therapeutics of gestational diabetes (NIH-
funded: OTA-26-004)
Position Summary: We are seeking a Postdoctoral Fellow to lead the
computational modeling of 1) metabolic systems and 2) fluid balance related
to hypertension. As part of an innovative NIH-funded grant, this project
focuses on constructing patient-specific digital twins to advance glycemic
management and therapeutic strategies across diverse pregnant cohorts.
Required Qualifications
* Ph.D. in Applied Mathematics, Mathematical Biology, Systems Biology, or a
related discipline.
* Strong background in mechanistic mathematical modeling of biological,
endocrine, or physiological systems.
* Advanced proficiency in MATLAB/Python programming.
* Demonstrated record of scientific publication and strong writing skills.
Preferred Qualifications
* Prior experience with metabolic signaling, glucose-insulin models, or
gastrointestinal dynamics.
* Familiarity with Python/PyTorch or cross-disciplinary clinical research
environments.
Postdoctoral Fellow #3) Computational and statistical analysis of spatial
biology
Institution: Morgan State University, Baltimore, MD, USA
Position Overview
We are seeking a highly motivated and innovative Postdoctoral Fellow to lead
the computational and statistical analysis of high-dimensional multi-modal
spatial data. The successful candidate will develop and apply advanced
statistical models to integrate spatial transcriptomics, clinical neuroimaging,
and multiplexed tissue imaging datasets. You will play a critical role in
bridging the gap between macro-scale brain imaging and cellular-level
spatial omics.
Key Responsibilities
* Data Analysis & Pipeline Development: Lead the statistical analysis of
spatial transcriptomics data (e.g., 10x Visium, Xenium, or MERFISH) and
highly multiplexed imaging data (e.g., CODEX).
* Multi-Modal Brain Mapping: Process and analyze neuroimaging datasets
(e.g., structural MRI, fMRI, or PET) and integrate these macro-scale clinical
images with micro-scale spatial multi-omics to build multiscale models of
brain tissue.
* Algorithm & Method Development: Design and implement novel statistical
and machine learning methods for spatial domain identification, image
segmentation, and cross-modality data alignment.
* Collaboration: Work closely with experimentalists and radiologists to guide
experimental design, ensure data quality, and iterate on analytical
approaches.
* Scientific Communication: Prepare high-impact manuscripts, present
findings at national/international conferences, and assist in drafting
computational sections for grant proposals.
Required Qualifications
* Education: Ph.D. in Applied Mathematics, Mathematical Biology,
Biostatistics, Bioinformatics, Neuroinformatics, Data Science, or a related
quantitative field.
* Statistical Expertise: Strong foundation in statistical modeling, hypothesis
testing, and spatial statistics.
* Domain Experience: Proven hands-on experience analyzing spatial
transcriptomics datasets, quantitative imaging sciences, and/or
neuroimaging data.
* Programming Skills: High proficiency in R and/or Python. Experience with
relevant computational libraries (e.g., Seurat, Squidpy, SpatialExperiment).
* Version Control & Compute: Experience with Git/GitHub and working in
high-performance computing (HPC) or cloud environments.
* Communication: Excellent written and oral communication skills, with a
track record of peer-reviewed publications.
Preferred Qualifications (Optional)
* Proficiency with standard neuroimaging analysis software and pipelines
(e.g., FSL, FreeSurfer, AFNI, SPM, or ANTs).
* Experience with deep learning and computer vision techniques applied to
biological or medical images (e.g., medical image registration, cell
segmentation).
* Strong background in neuroanatomy, neurobiology, or cognitive
neuroscience.
Contact
Send me your CV to Pilhwa Lee, Pilhwa.lee@morgan.edu
-------------------------------------------------------
From: Raymond Tuminaro rstumin@sandia.gov
Date: September 29, 2026
Subject: Postdoc Position, John von Neumann Fellow, Sandia National Labs
The Center for Computing Research and the Computer Sciences and
Information Systems Center at Sandia National Laboratories invite
outstanding candidates to apply for the 2027 John von Neumann
Postdoctoral Research Fellowship in Computational Science. This
prestigious fellowship is supported by the Applied Mathematics
Research Program in the U.S. Department of Energy's Office
of Advanced Scientific Computing Research. The fellowship provides
an
exceptional opportunity for innovative research in computational
mathematics and scientific computing on advanced computing
architectures with application to a broad range of science and
engineering problems of national importance. Applicants must have
or
soon receive a Ph.D. in applied/computational mathematics or
related
computational science and engineering disciplines. Applicants must
have less than three years of postdoctoral experience. This
appointment is for one year, with a possible renewal for a second
year, and includes a highly competitive salary, moving expenses and
a
generous professional travel allowance.
Applications will be accepted through November 18, 2026.
For more information, including application instructions, please
see
https://www.sandia.gov/careers/careers/students-and-postdocs/
fellowships/john-von-neumann-fellowship/
-------------------------------------------------------
From: Tom Hagstrom thagstrom@smu.edu
Date: September 28, 2026
Subject: Tenure Track Position at Southern Methodist University
The Department of Mathematics at Southern Methodist University
invites applications for a tenure track assistant professorship
starting August 1, 2027. Preference will be given to candidates
whose research program involves optimization, quantum computing,
and/or machine learning for scientific computation. The department
has nineteen tenure-stream faculty with active research efforts in
numerical analysis, scientific computing, machine learning, data
science, imaging, biology, nonlinear optics, and fluid mechanics.
https://www.smu.edu/dedman/academics/departments/math.
Candidates must have a PhD in applied mathematics, mathematics, or
a closely related field. Postdoctoral experience is preferred.Â
A cover letter, CV, research statement, teaching statement
(including a description of teaching experience), and three letters
of recommendation should be submitted to Interfolio at https://
apply.interfolio.com/193867. To ensure full consideration for the
position, the application must be received by November 30, 2026,
but the committee will continue to accept applications until the
position is filled. The committee will notify applicants of the
employment decision after the position is filled. Hiring is
contingent upon the satisfactory completion of a background check.
SMU is an equal opportunity employer. All qualified applicants will
receive consideration for employment without regard to race, color,
religion, national origin, sex, age, disability, genetic
information, veteran status, sexual orientation, or gender identity
and expression.
-------------------------------------------------------
From: Jennifer Ryan jryan©kth.se
Date: October 01, 2026
Subject: Tenure-track Lerheden Assistant Professor position in Applied Mathematics at KTH
The Math department at KTH has an opening for a tenure-track Lerheden
faculty position in Applied Mathematics at KTH. The position is in foundational
mathematical research motivated by applications in one or several of the areas:
Stochastic control, Optimization under uncertainty, Inverse problems, and
numerical methods within these areas. The position includes a starting package
for hiring one PhD student.
Application deadline: October 15, 2026.
https://www.kth.se/lediga-jobb/936948?l=en
Candidates who received PhD during the last 7 years (not including time for
parental leave etc.) are prioritized. Applications require the KTH CV template:
https://www.kth.se/en/om/jobba-pa-kth/cv-mall-for-anstallning-och-befordran-
av-larare-kth-1.471907
-------------------------------------------------------
From: Charley Denton cdenton@aimsciences.org
Date: September 29, 2026
Subject: Contents, AIMS New Volume: AMMC Vol. 9
Applied Mathematics for Modern Challenges
Volume: 9
September 2026
https://www.aimsciences.org/AMMC/article/2026/9/0
Multifidelity sensor placement in Bayesian state estimation problems
Gabriela Ramon, Geena Sarnoski, Vasishta Tumuluri, Hugo DÃaz and Arvind K.
Saibaba
Multi-layer parametrized Bayesian CT reconstruction for subsea pipe inspection
Silja L. Christensen, Nicolai A. B. Riis and Jakob S. Jørgensen
Reconstructions of single pixel X-ray transforms with applications in nuclear-
disarmament verification
Christopher Fichtlscherer, R. Scott Kemp and Christina Brandt
-------------------------------------------------------
From: Charley Denton cdenton@aimsciences.org
Date: September 29, 2026
Subject: Contents, AIMS New Volume: EECT Vol. 26
Evolution Equations and Control Theory
Volume: 26
December 2026
https://www.aimsciences.org/eect/article/2026/26/0
Optimal control of a class of nonlinear heat conduction models
Denilson Menezes and Juan LÃmaco
Pointwise boundary observation in geometric optimization problems associated
to variational inequalities Special Issue
Livia Betz, Cornel Marius Murea and Dan Tiba
Turnpike control and static finite-parameter shape design for linear
elastodynamics: a conditional analytical framework Special Issue
Martin Gugat and Jan Sokołowski
Local in time solvability for fractional semilinear parabolic systems with rapidly
growing nonlinear terms
Masamitsu Suzuki
Approximating technique for the solution to the H∞-optimal control problem
Special Issue
Gabriela Marinoschi
Weak solutions and inertial limits for quasi-static filtrations Special Issue
Peter Lavagnino, Arum Lee and Justin T. Webster
Read more articles here:
https://www.aimsciences.org/eect/article/2026/26/0
-------------------------------------------------------
From: Charley Denton cdenton@aimsciences.org
Date: September 29, 2026
Subject: Contents, AIMS New Volume: FMF Vol. 10
Frontiers of Mathematical Finance
Volume: 10
September 2026
https://www.aimsciences.org/FMF/article/2026/10/0
Is there an AI bubble? Robust date-stamping for periods of exuberance
Abir Sarkar and Martin T. Wells
Correction to: Exploiting arbitrage requires short selling
Eckhard Platen and Stefan Tappe
Portfolio optimisation with European options
Jonathan Raimana Chan, Thomas Huckle, Antoine Jacquier and Aitor Muguruza
A martingale representation for a european-style option under a semi-Markov-
switching diffusion model
Tak Kuen Siu and Robert J. Elliott
Rapid Communications
Asset pricing, measure changes, and a new Lévy model
Dilip B. Madan and King Wang
-------------------------------------------------------
From: Alex Barnett abarnett@flatironinstitute.org
Date: October 01, 2026
Subject: Call for papers, ACOM special issue, fast/integral eqns, Greengard 70th
Dear Colleagues,
The journal Adv. Comput. Math. (ACOM) is soliciting submissions for a
topical collection (special issue) on "Advances in Fast Algorithms and
Integral Equation Methods. In honor of Leslie Greengard’s 70th
Birthday".
Submission deadline: April 30, 2027
Editorial Board for the collection, chaired by Charles L. Epstein and
Shidong Jiang:
Travis Askham (New Jersey Inst. of Technology, USA)
Alex Barnett (Flatiron Institute, USA)
Charles L. Epstein (Flatiron Institute, USA)
Thomas Hagstrom (Southern Methodist University, USA)
Lise-Marie Imbert-Gérard (U. Arizona, USA)
Shidong Jiang (Flatiron Institute, USA)
Jun Lai (Zhejiang University, China)
Michael O'Neil (Courant Institute, NYU, USA)
Manas Rachh (IIT Bombay, India)
Karsten Urban (Ulm University, Germany)
For full details, including topic areas, see:
https://link.springer.com/journal/10444/updates/53761972
Happy paper-writing, and we look forward to your submissions.
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End of Digest
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