About this conference
This international conference serves as a forum for data scientists, physicists, applied mathematicians, and computational researchers to explore the intersection of applied data science, physics, and computational mathematics. The conference program covers foundational and applied topics in data science including machine learning, statistical modeling, big data analytics, data visualization, and predictive modeling. In the physics domain, topics include condensed matter physics, quantum physics, statistical mechanics, astrophysics, and biophysics, with an emphasis on computationally intensive approaches. Computational mathematics topics include numerical methods, optimization, partial differential equations, linear algebra, and algorithm development for high-performance computing. Special emphasis is placed on the convergence of these disciplines, including physics-informed machine learning, data-driven modeling of physical systems, and mathematical foundations of machine learning algorithms. Through keynote lectures, technical paper presentations, and interdisciplinary workshops, this conference aims to advance computational approaches to scientific discovery and engineering applications.