Special Sessions

• Prof. Dr. Mehmet Yavuz, Necmettin Erbakan University, Turkiye, mehmetyavuz@erbakan.edu.tr
• Prof. Dr. Ercan Çelik, Kyrgyz-Turkish Manas Universıty, Kyrgyzstan, ercan.celik@manas.edu.kg
• Prof. Dr. Fırat Evirgen, Balikesir University, Türkiye, fevirgen@balikesir.edu.tr

Theme

• Computational Mathematics is a field that focuses on solving mathematical problems using computational techniques and algorithms. It bridges the gap between mathematics, computer science, and applied sciences, emphasizing the development and implementation of numerical methods to analyze and solve complex mathematical problems.

Topics

• Numerical analysis (finite element methods, Monte Carlo simulations)
• High-performance computing (parallel algorithms, GPU computing)
• Scientific computing (PDE solvers, computational fluid dynamics)
• Differential Equations
• Error and Stability Analysis
• Monte Carlo and Stochastic Methods

• Prof. Dr. Necati Özdemir, Balıkesir University, Türkiye, nozdemir@balikesir.edu.tr
• Assoc. Prof. Dr. Markus Mueller, University of Exeter, United Kingdom, m.mueller@exeter.ac.uk
• Assoc. Prof. Dr. Amin Jajarmi, University of Bojnord, Iran, a.jajarmi@ub.ac.ir

Theme

• This session aims to discuss a broad range of topics including current trends of linear, nonlinear, discrete and fractional control systems as well as new developments in robotics and mechatronics, unmanned systems, energy systems with the goal of strengthening cooperation of control and automation scientists with industry.

Topics

• Adaptive control
• Linear and nonlinear control systems
• Optimal control
• Discrete time control systems
• Robust control
• Fractional order systems and control
• Chaotic systems and control
• Evolutionary and heuristic control
• Robotic control
• Energy management and control
• Control of unmanned air and undersea vehicles

• Prof. Dr. Stuart Townley, University of Exeter, United Kingdom, s.b.townley@exeter.ac.uk
• Prof. Dr. Carla M.A. Pinto, Instituto Superior de Engenharia do Porto, Portugal, cap@isep.ipp.pt
• Prof. Dr. Md. Haider Ali Biswas, Khulna University, Bangladesh, mhabiswas@math.ku.ac.bd

Theme

• Mathematical Biology and Ecology is an interdisciplinary field that uses mathematical models and computational techniques to understand biological and ecological systems. It integrates mathematical theories with biological processes to analyze complex phenomena and predict outcomes.

Topics

• Population Dynamics and Models
• Epidemiology and Disease Modeling
• Evolutionary Models
• Physiological and Biochemical Modeling
• Ecosystem and Community Models
• Mathematical Ecology Techniques
• Spatial and Spatiotemporal Models
• Pattern Formation and Morphogenesis
• Genomics and Systems Biology
• Conservation and Resource Management Models

• Prof. Dr. Dumitru Baleanu, Lebanese American University, Lebanon, dumitru.baleanu@lau.edu.lb
• Prof. Dr. Thabet Abdeljawad, Prince Sultan University, Saudi Arabia, tabdeljawad@psu.edu.sa
• Prof. Dr. Jordan Hristov, University of Chemical Technology and Metallurgy, Bulgaria, jyh@uctm.edu

Theme

• In the past few decades, fractional differential equations have played a very important role in various fields. Based on the wide applications in engineering and sciences such as physics, mechanics, chemistry, and biology, research on fractional ordinary or partial differential equations and other relative topics is active and extensive around the world. In the past few years, hundreds of research papers, monographs, and international conferences have witnessed an increase in the number of this subject. The objective of this special session is to highlight the importance of theoretical aspects and numerical methods in fractional calculus and their applications and let the readers of this journal know about the possibilities of this new tool.

Topics

• New methods for solving fractional differential equations
• Controllability of fractional order systems
• Iteration methods for solving partial and ordinary fractional equations
• Numerical methods for solving fractional integro-differential equations
• Numerical functional analysis and applications
• Local and nonlocal boundary value problems for fractional partial differential equations
• Stochastic partial fractional differential equations and applications
• Computational methods in fractional partial differential equations
• Numerical methods for solving variable order differential equations
• Perturbation methods for fractional differential equations

• Prof. Dr. Ralf Korn, University of Kaiserslautern-Landau, Germany, korn@mathematik.uni-kl.de
• Assoc. Prof. Dr. Sascha Desmettre, Johannes Kepler University Linz, Austria, sascha.desmettre@jku.at
• Assoc. Prof. Dr. Bilgi Yılmaz, Kahramanmaraş Sütçü İmam Üniversitesi, Türkiye, bilgiyilmaz@ksu.edu.tr
• Dr. Christian Laudagé, University of Kaiserslautern-Landau, Germany, christian.laudage@rptu.de
• Dr. Laurena Ramadani, University of Kaiserslautern-Landau, Germany, ramadani@mathematik.uni-kl.de

Theme

• Mathematical Finance is a field that applies advanced mathematical models and techniques to analyze financial markets, assess risks, and optimize investment strategies. It focuses on understanding and managing financial risk, valuing assets, and making informed decisions in financial markets. It bridges the gap between mathematics, economics, and finance, emphasizing the use of probability theory, stochastic processes, and numerical methods to model asset prices, evaluate derivatives, and manage financial risk.

Topics

• Financial Economics
• Green and Sustainable Finance (Electricity, Energy,…)
• Insurance (Climate Risk, Cyber Risk, …)
• Statistics for Financial Markets and Large Language Models
• Mean Field Games and Stochastic Control
• New Technologies in Finance and Insurance (Computational Methods and Machine Learning, Cryptocurrencies, Limit Order Book and High Frequency Trading, Algorithmic Trading)
• Optimal Transport (Robust Finance)
• Portfolio Optimisation
• Risk Management (Risk Allocation, Risk Aggregation, Credit Risk and Systemic Risk)
• Rough Analysis in Finance and Insurance (Rough and Stochastic Volatility)
• Stochastic Optimal Control
• Derivative and Option Pricing &Hedging

• Prof. Dr. Yeliz Karaca, University of Massachusetts (UMass) Chan Medical School, USA, yeliz.karaca@ieee.org
• Prof. Dr. Dumitru Baleanu, Lebanese American University, Lebanon, dumitru.baleanu@lau.edu.lb
• Prof. Dr. Yu-Dong Zhang, University of Leicester, United Kingdom, yudongzhang@ieee.org

Theme

• The junction of computational and mathematical neuroscience as well as medicine reflects and demonstrates a transformative dimension for the understanding and treating of various disorders among which neurological ones pose a global burden. It has become possible, via application of advanced mathematical models and computational techniques, to simulate neural activities while exploring the complexities of brain structure and function to unearth the underlying mechanisms across medicinal, clinical and neurological conditions which may also be affected by external factors. Furthermore, the interplay of neuroscience and Artificial Intelligence (AI) can provide us with innovative models benefiting from the computational power of AI to yield more accurate solutions through advanced technologies that reveal complex neural mechanisms to enhance understanding. Consequently, the aim of our special session is to work toward enabling the development of mathematical and predictive models by attempting to bridge the gap between theoretical neuroscience and clinical practices, where computational and mathematical neuroscience hold the potential to transform the way of diagnosis, management as well as curing diseases and health concerns, paving the way for more accurate results and improved patient outcomes.

Topics

• Computational neuroscience and models
• Mathematical modeling
• Disease dynamics and complex attributes
• Artificial Intelligence (AI) applications in medicine, neuroscience, biology and clinical settings
• Computational biology
• Fractional calculus in medicine/biology/neurology
• Fractal applications in medicine/biology/neurology
• Mathematical bioengineering
• Biotechnology and / or bioengineering practices
• Artificial Intelligence (AI) in neuroimaging
• Signal / image processing
• Complex networks and pattern recognition
• Deep learning and neural networks for brain disorder diagnosis, prognosis and prediction
• Advanced neurological data analysis
• Personalized medicine and applications

• Prof. Dr. Gerhard-Wilhelm Weber, Poznan University of Technology, Poland, gerhard.weber@put.poznan.pl
• Prof. Dr. Ibrahim Kucukkoc, Balikesir University, Türkiye, ikucukkoc@balikesir.edu.tr
• Prof. Dr. Osman Taylan, King Abdulaziz University, Saudi Arabia, otaylan@kau.edu.sa

Theme

• The goal of this session is to discuss recent developments in applications of optimization methods by bringing together researchers and practitioners working in the field of optimization theory, methods, software and related areas.

Topics

• Mathematical programming
• Global optimization
• Nondifferential optimization
• Continuous optimization
• Combinatorial optimization
• Multicriteria optimization
• Equilibrium programming
• Game theory
• Data mining
• Population based algorithms
• Applications of optimization in natural sciences
• Applications of optimization in engineering

• Prof. Dr. Hüseyin Merdan, TOBB Economy and Technology University, Türkiye, merdan@etu.edu.tr
• Prof. Dr. Parvaiz Ahmad Naik, Youjiang Medical University for Nationalities, China, naik.parvaiz@ymun.edu.cn
• Prof. Dr. Akif Akgül, Hitit University, Türkiye, akifakgul@hitit.edu.tr

Theme

• Nonlinear Dynamical Systems and Chaos Theory is a branch of mathematics and physics that studies systems governed by nonlinear equations, where small changes in initial conditions can lead to vastly different outcomes. It focuses on understanding complex and chaotic behaviors in deterministic systems.

Topics

• Nonlinear dynamics & bifurcation theory
• Feedback systems
• Chaos and fractals in real-world applications
• Hamiltonian and conservative systems
• Coupled and synchronizing systems
• Quantifying chaos
• Fractals and strange attractors

• Prof. Dr. Bünyamin Aydın, Necmettin Erbakan University, Türkiye, baydin@erbakan.edu.tr
• Prof. Dr. Nihat Akgüneş, Necmettin Erbakan University, Türkiye, nakgunes@erbakan.edu.tr
• Assoc. Prof. Dr. Ahmet Sınak, Akdeniz University, Türkiye, ahmetsinak@akdeniz.edu.tr
• Prof. Dr. Nesip Aktan, Necmettin Erbakan University, Türkiye, naktan@erbakan.edu.tr
• Prof. Dr. Sedat Pak, Karamanoğlu Mehmetbey University, Türkiye, sedatpak@kmu.edu.tr

Theme

• Structures, Symmetries, and Abstractions: Contemporary Explorations in Pure Mathematics. This session highlights current research and theoretical developments in Pure Mathematics. It welcomes contributions from all areas that emphasize deep structural understanding, abstraction, and rigorous proof. The goal is to showcase the elegance, interconnectedness, and foundational power of mathematics in its purest form—spanning both classical theory and modern innovation.

Topics

Analysis

• Real and complex analysis, including function theory
• Harmonic analysis and Fourier theory
• Functional analysis and Banach space theory
• Measure theory and integration

Algebra and Number Theory

• Group theory, ring theory, and field extensions
• Algebraic number theory and Diophantine equations
• Modular forms, elliptic curves, and Galois representations
• Commutative algebra and ideal theory
• Symbolic computation & computer algebra systems
• Parallel & distributed computing
• Linear block codes (e.g., Hamming codes, BCH codes, Reed-Solomon codes)

Geometry and Topology

• Differential geometry and Riemannian manifolds
• Algebraic geometry and schemes
• Low-dimensional topology and knot theory
• Homotopy theory and higher category theory

• Assoc. Prof. Ahmet Pekgör, Necmettin Erbakan University, Türkiye, apekgor@erbakan.edu.tr

Theme

• The objective of this session is to apply numerical methods to statistical problems and probabilistic models. Harnessing advanced statistical methods and probabilistic models to tackle data-driven challenges in science and technology.

Topics

• Core statistical computing for data science
• Scalable algorithms for massive data
• Probability in machine learning & AI
• Data science applications with statistical rigor
• Probabilistic programming (Stan, PyMC, Turing.jl): making advanced models accessible to data scientists
• R/Python for scalable statistical computing: efficient libraries and workflows (e.g., NumPyro, TensorFlow Probability)

• Prof. Dr. Şeref Sağıroğlu, Gazi University, Computer Engineering Department; IEEE Blockchain, Türkiye, ss@gazi.edu.tr
• Prof. Dr. Ali Turab, School of Software, Northwestern Polytechnical University, China, aliturab@nwpu.edu.cn
• Dr. Ozan Evkaya, The University of Edinburgh, Scotland, United Kingdom, Ozan.Evkaya@ed.ac.uk
• Dr. Seda Karateke, Atlas University, Türkiye, seda.karateke@atlas.edu.tr

Theme

• This session delves into the scientific and mathematical foundations and applications of Artificial Intelligence and Machine Learning. It invites contributions that highlight theoretical advances, mathematical modeling, algorithmic innovation, and the application of AI/ML methods to solve complex scientific problems. Emphasis is placed on rigorous approaches, interdisciplinary integration, and real-world scientific discovery powered by intelligent systems.

Topics

• Mathematical foundations of machine learning
• AI in scientific computing
• ML for data-driven scientific discovery
• Geometric and topological methods in AI
• Integration of symbolic mathematics with machine learning
• Control theory, signal processing, and inverse problems solved with ML
• ML applications in educational data science

• Dr. Abdallah Alsammani, Jacksonville University, Florida, USA, aalsamm@ju.edu
• Dr. Eray Çakıcı, IBM Data Science & Al Elite, Germany, eray.cakici1@ibm.com
• Dr. Osman Yardimci, Tuskegee University, Tuskegee, AL 36088, USA, oyardimci@tuskegee.edu
• Dr. Tahir Issa, Data Science, Machine Learning, Deep Learning, Statistics, San José State University, USA, tahirbachar.issa@sjsu.edu

Theme

• The objective of this session is to explore recent advancements in different areas of Data Science. This session also explores the mathematical foundations and methodologies that drive innovations in Data Science. It aims to bring together researchers working on the interface of mathematics and data-intensive applications across various domains. The session welcomes contributions emphasizing rigorous mathematical modeling, algorithmic development, and analytical techniques to uncover insights from complex data. Special attention will be given to interdisciplinary approaches, theoretical advancements, and real-world problem solving through mathematical data science

Topics

• Emerging Trends in Mathematics and Data Science
• Data Science in Healthcare and Medicine
• Emerging Trends in Mathematics and Data Science
• Mathematical Models in Healthcare and Biomedical Data Science
• Financial and Marketing Analytics
• Mathematical Approaches to Energy Data and Management
• Modeling and Analytics for Climate Change
• Applications of Data Science in Education and Natural Sciences
• Big Data Analytics and Mathematical Visualization Techniques
• Econometric Models and Statistical Learning
• Optimization, Inference, and Data-Driven Decision Making

Target Audience

• This session is designed for mathematicians, data scientists, statisticians, computer scientists, and professionals engaged in solving real-world problems through data-driven mathematical methods.