From: Alex Townsend Date: Fri, 2 Oct 2026 08:20:23 -0400 Subject: NA Digest, V. 26, # 40 To: na-digest-l@lists.cornell.edu NA Digest Friday, October 02, 2026 Volume 26 : Issue 40 Today's Editor: Alex Townsend Cornell University townsend@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. 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 Díaz 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 Límaco 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 SokoÅ‚owski 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. ------------------------------------------------------- End of Digest **************************