International Journal of Data Science in the Mathematical Sciences (IJDTMS)

The aim of this new, highly inter-disciplinary journal is to establish a much-needed platform for experimental mathematicians, both pure and applied, physicists and other experts in theoretical STEM fields, as well as data scientists and computer scientists specializing in machine-learning and artificial intelligence. This platform will publish and promote discussion in the following areas: Data in pure mathematics, especially those already freely available online: LMFdB, GrDB, GAP, KnotsDB, etc. and in particular in line with MathSage; Data in applied mathematics, ranging from mathematical biology to theoretical physics; Data Science & Theoretical Physics: especially in relation to the string landscape; Machine-Learning & Mathematical Structures: in parallel with XenaProject, Coq and LEAN projects in automated theorem proving; Machine-Learning applications to Applied Mathematical sciences; New techniques in machine-learning inspired from theoretical physics, especially from quantum field theory and statistical mechanics; Interpretability Methods in Machine Learning; Conjecturing Formulation

International Journal of Data Science in the Mathematical Sciences (IJDTMS) is :-

• International, Peer-Reviewed, Open Access, Refereed, mathematics, biology, physics, Machine-Learning, Mathematical Structures , Online or Print , Half-Yearly Journal

• UGC Approved, ISSN Approved: P-ISSN P-ISSN: 2810-9392, E-ISSN: 2810-9406, Established: 2023, Impact Factor: 1
• Does Not Provide Crossref DOI

• Not indexed in Scopus, WoS, DOAJ, PubMed, UGC CARE