Advanced Mathematical and Statistical Methods for Modern Data Science and Scientific Machine Learning
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D1: Probability and Statistics".
Deadline for manuscript submissions: 31 December 2026 | Viewed by 330
Editors
Interests: multiple testing; watermark in LLM; statistical computing; bioinformatics
Special Issue Information
Dear Colleagues,
The rapid advancement of data acquisition technologies has led to the proliferation of high-dimensional and complex datasets across diverse scientific and engineering disciplines. As the scale and intricacy of data increase, the traditional boundaries between mathematical theory, statistical inference, and computational algorithms are becoming increasingly porous. To effectively model, analyze, and interpret real-world phenomena, it is now essential to bridge the gap between rigorous mathematical foundations and practical computational strategies.
This Special Issue seeks high-quality contributions that address the theoretical and computational challenges inherent in modern data science. We invite authors to submit original research and review articles that advance the development of statistical methodologies, approximation techniques, and probabilistic models. We welcome submissions proposing novel theoretical frameworks or demonstrating significant applications in fields ranging from the life sciences to artificial intelligence.
Dr. Guanxun Li
Dr. Chunyang Liao
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- artificial intelligence
- approximation theory
- bayesian inference
- bioinformatics
- computational inference
- data science
- high-dimensional probability
- large language models
- MCMC
- multiple testing
- probabilistic modeling
- scientific machine learning
- statistical computing
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