John Paulo Serwelas | Applied Mathematics | Mathematical Engineering Excellence Award

Published on by Math Scientist

Prof. John Paulo Serwelas | Applied Mathematics | Mathematical Engineering Excellence Award

Author at Mapua University | Philippines

Prof. John Paulo Serwelas is a faculty member at Mapúa University, Philippines, whose research focuses on structural and materials engineering, particularly the performance of reinforced concrete structures under corrosion effects. His work integrates experimental investigation and analytical modeling to evaluate bonding strength and durability in corroded reinforced concrete using electrochemical measurement techniques such as half-cell potential analysis. Through his research, he contributes to improving structural safety, durability assessment, and sustainable infrastructure design in civil engineering.

Featured Publication

Mustapha Bouallala | Numerical Analysis | Numerical Analysis Research Award

Published on by Math Scientist

Prof. Mustapha Bouallala | Numerical Analysis | Numerical Analysis Research Award

Mustapha Bouallala | Cadi Ayyad University | Morocco

Prof. Mustapha Bouallala, from the Polydisciplinary Faculty at Cadi Ayyad University in Safi, Morocco, specializes in applied mathematics with a focus on variational and hemivariational inequalities, contact mechanics, thermo-viscoelasticity, and fractional‐order differential models. His work emphasizes the mathematical analysis, modeling, and numerical simulation of complex physical systems governed by non-smooth dynamics, memory effects, and time-fractional derivatives. He contributes to the development of analytical frameworks for contact problems involving viscoelastic materials, locking materials, and thermo-mechanical interactions. Through rigorous mathematical modeling and approximation techniques, his research advances the understanding of nonlinear evolutionary problems and supports applications in engineering mechanics, material behavior, and thermal–structural interaction systems.

Profiles: Scopus | Orcid 

Featured Publications

Bouallala, M., Essoufi, E.-H., & Ouafik, Y. (2026). Modeling and simulation of time-fractional derivative contact problem in thermo-viscoelasticity. Rendiconti del Circolo Matematico di Palermo Series 2. https://doi.org/10.1007/s12215-025-01318-1
Year: 2026

Ouaanabi, A., Alaoui, M., Bouallala, M., & Essoufi, E.-H. (2025). Continuous dependence result for a class of evolutionary variational-hemivariational inequalities with application to a dynamic thermo-viscoelastic contact problem. Acta Applicandae Mathematicae. https://doi.org/10.1007/s10440-025-00707-z
Year: 2025

Bouallala, M., Bourichi, S., Essoufi, E. H., & Rahnaoui, H. (2025). Approximation of solution for unilateral contact problem with locking materials. Mathematical Methods in the Applied Sciences. https://doi.org/10.1002/mma.70131
Year: 2025

Bouallala, M., Ouafik, Y., & Bendarag, A. (2025). Analysis of a thermo-viscoelastic contact problem with normal damped response, unilateral constraint and memory term. SeMA Journal. https://doi.org/10.1007/s40324-025-00418-3
Year: 2025

Aharrouch, B., & Bouallala, M. (2025). Convergence analysis of Kantorovich-type operators in variable exponent Sobolev spaces. Georgian Mathematical Journal. https://doi.org/10.1515/gmj-2025-2089
Year: 2025

Hind Hallabia | Data Science | Excellence in Research Award

Published on by Math Scientist

Dr. Hind Hallabia | Data Science | Excellence in Research Award

Teaching and Researcher Assistant | University Institute of Technology of Saint Etienne Jean Monnet University | France

Dr. Hind Hallabia, affiliated with the University Institute of Technology of Saint-Étienne at Jean Monnet University, France, specializes in remote sensing, pansharpening, and advanced image processing techniques for satellite data analysis. Her research focuses on developing graph-based segmentation methods, superpixel modeling, and data fusion frameworks to enhance multispectral and panchromatic imagery. Dr. Hallabia investigates latent low-rank decomposition, detail-injection mechanisms, and texture-based segmentation models to improve image quality, spatial–spectral fidelity, and analytic accuracy in Earth observation applications. Her work contributes to advances in hazardous-area monitoring, environmental assessment, and optical remote sensing technologies through methodological innovation, algorithm design, and computational enhancements.

Profiles: Scopus | Orcid

Featured Publications

  • Hallabia, H. (2025). A graph-based superpixel segmentation approach applied to pansharpening. Sensors, 25(16), Article 4992. https://doi.org/10.3390/s25164992
    Year: 2025

  • Hallabia, H. (2025). Land and aquatic spectral signatures analysis over a spatio-temporal hazardous area acquired by Worldview satellite. Annual International Congress on Electrical Engineering 2025.
    Year: 2025

  • Hallabia, H. (2025). Advanced trends in optical remotely sensed data fusion: Pansharpening case study. Iris Journal of Astronomy and Satellite Communications.
    Year: 2025

  • Hallabia, H., Hamam, H., & Ben Hamida, A. (2023). A novel detail injection framework using latent low-rank decomposition for multispectral pan-sharpening. Multimedia Tools and Applications, 82, 11971–11995. https://doi.org/10.1007/s11042-022-12770-x
    Year: 2023

  • Hallabia, H., & Hamam, H. (2021). A graph-based textural superpixel segmentation method for pansharpening application. Proceedings of IGARSS 2021. https://doi.org/10.1109/igarss47720.2021.9553304
    Year: 2021

Xichang Wang | Mathematical Engineering | Research Excellence Award

Published on by Math Scientist

Prof. Xichang Wang | Mathematical Engineering | Research Excellence Award

Director | China Aeronautical Manufacturing Technology Institute | China

Prof. Xichang Wang specializes in welding engineering, metal material standards, and aerospace manufacturing processes. His research focuses on structural modeling of welding process specifications, thermal bonding behavior of titanium alloys, and the development of metal material standards within China’s evolving military–civilian integration framework. He has contributed to key studies on electron beam welding (EBW), thermal self-compressing bonding mechanisms, and material property characterization for aviation and submersible applications. His work integrates materials science, welding technology, and standards engineering, supporting the advancement of high-performance manufacturing in aerospace and defense industries.

Profiles: Scopus | Orcid

Featured Publications

  • Wang, X., Li, G., Zeng, Y., Wang, X., Lyu, X., & Cao, Y. (2025). Research on the structural model of welding process specifications for aviation products based on trade-off design standards. Standards, 5(4), Article 0031. https://doi.org/10.3390/standards5040031
    Year: 2025

  • Wang, X.-C., Wu, Q.-Y., Xu, M., Qi, D.-X., Lu, J., & Teng, C.-Y. (2019). A brief analysis on the development of metal material standards in China under the background of military-civilian integration. Metallurgical Analysis, (Yejin Fenxi), Article 010558. https://doi.org/10.13228/j.boyuan.issn1000-7571.010558
    Year: 2019

  • Deng, Y., Guan, Q., Tao, J., Wu, B., & Wang, X. (2017). Effect of heating time on rigid restraint thermal self-compressing bonding of TC4 alloy. Rare Metal Materials and Engineering.
    Year: 2017

  • Fu, P., Mao, Z., Tang, Z., Li, K., Wang, X., & Zuo, C. (2017). Microstructures and properties of TC4 ELI alloy with horizontal electron beam welding for submersible manned cabin. Applied Ocean Research. https://doi.org/10.1016/j.apor.2017.09.004
    Year: 2017

yanan Camaraza-Medina | Integracion Numerica | Editorial Board Member

Published on by Math Scientist

Dr. yanan Camaraza-Medina | Integracion Numerica | Editorial Board Member

Postdoctoral Research | University of Guanajuato | Mexico

Yanan Camaraza Medina is a mechanical engineer with 15 years of experience in thermal and energy systems, specializing in convective heat transfer, thermal radiation, and industrial heat-transfer equipment. His work integrates experimental, analytical, and numerical methods to improve the performance, safety, and efficiency of thermal systems used in energy generation and industrial applications. With academic and industrial expertise, he has served as a department head in thermal engineering, university professor, and researcher, contributing to advancements in thermophysical property modeling, phase-change processes, and multiphysics simulations. His research includes the development of predictive correlations, heat-transfer models, and computational strategies applied to real-world engineering problems.

Profiles: Scopus | Orcid 

Featured Publications

Camaraza Medina, Y. (2025). Proximate and ultimate analysis, higher heating value and inorganic chemical composition of woods from central region of Cuba. Sustainable Chemistry One World.

Camaraza Medina, Y., et al. (2025). Heat transfer modeling during condensation inside tubes with arbitrary geometrical orientations. Heat Transfer.

Camaraza Medina, Y. (2025). Experimental correlation of the steel’s thermophysical properties for thermal engineering applications. Heat Transfer.

Camaraza Medina, Y., et al. (2025). Multiphysics analysis of electric arc extinction in low voltage switchgear: Electromagnetic, thermal, and fluid dynamics interactions. Thermal Science and Engineering Progress.

Camaraza Medina, Y., et al. (2025). Analysis of transient heat conduction in tubes under convective boundary conditions. Heat Transfer.

Ilhem Kadri | Applied Mathematics | Best Researcher Award

Published on by Math Scientist

Assoc. Prof. Dr. Ilhem Kadri | Applied Mathematics | Best Researcher Award

Associate Professor | University of Oran 1 – Ahmed Ben Bella | Algeria

Dr. Ilhem Kadri is an Associate Professor of Applied Mathematics at the University of Oran 1, Algeria, specializing in fractional calculus, nonlinear partial differential equations, and computational mathematics. She earned her Ph.D. in Applied Mathematics from the University of Jordan, following her master’s and bachelor’s degrees in mathematics from the University of Oran 1 Ahmed Ben Bella. Dr. Kadri’s academic and research trajectory reflects a deep commitment to advancing the analytical and numerical treatment of fractional and conformable differential equations, as well as exploring chaotic and nonlinear dynamical systems. Her scholarly contributions include numerous research articles in internationally recognized journals, such as the European Journal of Pure and Applied Mathematics, Mathematics, and Results in Nonlinear Analysis, where she has developed novel analytical and numerical frameworks including the Laplace Transform Decomposition Method, the Conformable Fractional Laplace Transform Method, and applications of fractional Fourier series and tensor product techniques. She has presented her work at several prestigious international conferences and symposia across Europe, Asia, and Africa, contributing to global dialogues on applied and computational mathematics. Dr. Kadri is also actively engaged in academic collaboration, scientific workshops, and professional development activities focused on enhancing research impact and innovation in mathematical sciences. Her expertise and scholarly output reflect a strong foundation in both theoretical and applied aspects of mathematics, positioning her as an influential contributor to the field of fractional calculus and nonlinear analysis.10 Citations, 4 Documents, 2 h-index.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Kadri, I.*, Al-Horani, M., & Khalil, R. (2022). Solution of non-linear fractional Burger’s type equations using the Laplace transform decomposition method. Results in Nonlinear Analysis, 5(2), 131–150. Citations: 12.

2. Kadri, I.*, Al Horani, M., & Khalil, R. (2023). Solution of fractional Laplace type equation in conformable sense using fractional Fourier series with separation of variables technique. Results in Nonlinear Analysis, 6(2), 53–59. Citations: 10.

3. Kadri, I.*, Horani, M., & Khalil, R. (2020). Tensor product technique and fractional differential equations. Journal of Semigroup Theory and Applications, Article ID 6. Citations: 5.

4. Ahmed, A. I., Elbadri, M., Alotaibi, A. M., Ashmaig, M. A. M., Dafaalla, M. E., & Kadri, I.* (2025). Chaos and dynamic behavior of the 4D hyperchaotic Chen system via variable-order fractional derivatives. Mathematics, 13(20), 3240.

5. Kadri, I.*, Saadeh, R. S., AlMutairi, D. M., Dafaalla, M. E., Berir, M., & Abdoon, M. A. (2025). Analytical and numerical investigation of a fractional order 4D chaotic system via Caputo fractional derivative. European Journal of Pure and Applied Mathematics, 18(3).

Yajuan Sun | Computational Mathematics | Best Researcher Award

Published on by Math Scientist

Prof. Yajuan Sun | Computational Mathematics | Best Researcher Award

Researcher at Academy of Mathematics and Systems Science, CAS, China

Professor Yajuan Sun is a distinguished mathematician at the Academy of Mathematics and Systems Science, Chinese Academy of Sciences (CAS), specializing in geometric numerical methods for differential equations with applications in plasma physics, molecular dynamics, and soliton theory. With a Ph.D. from CAS and over two decades of academic excellence, she has led 14 major research projects, including national and international collaborations such as the ITER fusion project. Her 49+ peer-reviewed publications in top-tier journals, mentorship of numerous graduate students, and global academic engagements—spanning the UK, USA, Singapore, and Australia—reflect her influential contributions to both theory and applied science. Her innovative algorithms have been used in major fusion reactor simulations and were shortlisted for the ACM Gordon Bell Prize. Prof. Sun exemplifies leadership, innovation, and global impact in computational mathematics.

Professional Profile

Scopus Profile | ORCID Profile 

Education

Professor Yajuan Sun holds a Ph.D. in Mathematics from the Academy of Mathematics and Systems Science, Chinese Academy of Sciences (CAS), where she developed variational integrators under the guidance of Prof. Mengzhao Qin. Prior to that, she earned her M.S. in Mathematics from Inner Mongolia University, where she focused on nonlinear parabolic equations. Her academic journey began with a B.S. in Mathematics from Inner Mongolia Normal University. Her early research laid the foundation for a lifelong specialization in numerical methods and geometric integrators. These academic credentials from top Chinese institutions shaped her deep understanding of both theoretical and computational mathematics, enabling her to build a globally recognized career in numerical analysis, with a focus on preserving geometric structures in the solutions of differential equations.

Experience

Professor Sun’s academic career spans over two decades at the Chinese Academy of Sciences, where she currently serves as a Professor at the Academy of Mathematics and Systems Science. She began as a Postdoctoral Researcher and has steadily advanced through roles as Assistant and Associate Professor. Internationally, she has been a Visiting Scholar at prestigious institutions including the Isaac Newton Institute (UK), UCSD (USA), and the National University of Singapore. Her collaborations span Europe, Oceania, and Asia, reflecting a robust international presence. She has supervised numerous graduate and visiting students, served as a referee for reputed journals, and contributed to a range of scientific platforms. Her sustained dedication and interdisciplinary work have made her a key contributor to applied and theoretical research within global scientific communities.

Research Interest

Professor Yajuan Sun’s research lies in geometric numerical integration, focusing on the development of algorithms that preserve intrinsic structures in differential equations—such as symplectic, volume-preserving, and energy-conserving properties. She explores advanced numerical techniques for both ODEs and PDEs, using variational principles, Hamiltonian systems, and generating functions. Her work applies to complex systems such as plasma dynamics, molecular simulations, and electromagnetic field modeling. She integrates finite element methods with geometric approaches to solve large-scale, stiff problems arising from science and engineering. Her ongoing interests include adaptive schemes, multisymplectic theory, and numerical stability. The elegance of preserving physical laws in simulations is at the heart of her research, contributing both to theoretical advancement and real-world scientific modeling in fusion energy and particle dynamics.

Award and Honor

Professor Sun has received notable honors, including the Excellent Achievement Award in Natural Science and funding from the K.C. Wong Education Foundation for Excellent Female Scientists. She has led or participated in prestigious projects funded by the National Natural Science Foundation of China, the ITER Project, and international programs like the Royal Society’s cost-share exchange. Her work was integral to a simulation shortlisted for the ACM Gordon Bell Prize, one of the highest recognitions in high-performance computing. These accolades reflect her pioneering role in computational mathematics, the global relevance of her research, and her impact as a female leader in STEM. Her sustained excellence across theory, application, and mentorship has earned her respect in both Chinese and international scientific circles.

Research Skill

Professor Yajuan Sun excels in designing structure-preserving numerical algorithms for large-scale systems modeled by differential equations. She is proficient in symplectic and multisymplectic integrators, generating function techniques, Runge–Kutta methods, and volume-preserving schemes. Her computational expertise extends to adaptive time-stepping, Hamiltonian splitting, and hybrid solvers used in plasma and electromagnetic field modeling. She integrates theoretical rigor with practical algorithm design, validated through real-world simulations such as those of fusion reactors (EAST, CFETR). Her collaborative work across mathematics and physics showcases her ability to bridge domains using high-level programming, numerical modeling, and mathematical physics. She also reviews and edits scientific publications, mentors graduate research, and contributes to algorithmic theory in cutting-edge computational science.

Publication Top Notes

  • Title: Contact-PIC Numerical Methods for Simulating Vlasov–Poisson–Fokker–Planck Problem
    Authors: Yajuan Sun
    Year: 2022

  • Title: Numerical Analysis for a Class of Variational Integrators
    Authors: Yajuan Sun, et al.
    Year: 2025

  • Title: Geometric Integration for the Linear-Gradient System
    Authors: Yajuan Sun, et al.
    Year: 2025

  • Title: Hamiltonian Particle-in-Cell Methods for Vlasov–Poisson Equations
    Authors: Yajuan Sun, et al.
    Year: 2022
    Citations: 7

Conclusion

Professor Yajuan Sun stands out as a leading mathematician whose research bridges theoretical innovation and practical scientific impact. With an outstanding academic record, influential publications, and significant research grants, she has made enduring contributions to geometric numerical methods and their application in plasma physics and beyond. Her ability to integrate structure-preserving algorithms into simulations of complex physical systems has driven advancements in computational modeling. Through global collaborations, student mentorship, and editorial service, she contributes actively to the scientific community. With ongoing research in adaptive and energy-conserving numerical methods, Professor Sun is poised to further influence the future of scientific computing, making her an exemplary candidate for the Best Researcher Award and a role model in the mathematical sciences.

Olaf Dössel | Mathematical Engineering | Best Researcher Award

Published on by Math Scientist

Prof. Dr. Olaf Dössel | Mathematical Engineering | Best Researcher Award

Professor at Karlsruhe Institute of Technology KIT, Germany

Prof. Dr. Olaf Dössel 🎓, an esteemed biomedical engineering expert, served as Director of the Institute of Biomedical Engineering at Karlsruhe Institute of Technology (KIT) 🇩🇪 for over 25 years. With a PhD in Physics and over 700 publications 📚, his pioneering research spans ECG imaging 🫀, bioelectric field modeling, and AI-powered biosignal analysis 🤖. A Fellow of IAMBE, IUPESM, and EAMBES 🌐, he has shaped global scientific policy through leadership in EU, German, and international advisory boards. As Editor-in-Chief of Biomedical Engineering (2010–2022) and President of global conferences 🌍, he has advanced the field significantly. His work bridges research, education, and innovation, mentoring generations of engineers 👨‍🏫. A recipient of the Ragnar Granit Prize 🏅 and KIT’s Verdienstnadel, he remains a guiding force in biomedical science and technology.

Professional Profile 

Google Scholar
Scopus Profile
ORCID Profile

🎓 Education

Prof. Dr. Olaf Dössel began his academic journey in Physics at Universität Kiel, earning his Diploma in 1979 and PhD in 1982 🎓. His foundational education combined analytical rigor with scientific curiosity, setting the stage for his lifelong commitment to biomedical innovation 🧠. His PhD, supported by the Studienstiftung des deutschen Volkes, laid the groundwork for pioneering work in bioelectricity, signal processing, and cardiac imaging. The early exposure to quantitative and experimental physics 📐⚛️ helped develop a deep understanding of electromagnetics and biological systems, forming the basis of his interdisciplinary expertise. This robust educational path enabled him to integrate physics, engineering, and medicine into a visionary academic and research career that would shape the future of biomedical engineering worldwide 🌍.

🧪 Professional Experience

Prof. Dössel’s professional career spans both industrial research and academia. From 1982 to 1996, he held senior roles at Philips Research Laboratories Hamburg ⚙️, leading the “Measuring Techniques” group and contributing to applied medical technologies. In 1996, he became Full Professor and Director of the Institute of Biomedical Engineering at KIT 🏛️, where he served until retirement in 2022. As Dean and academic advisor, he influenced thousands of students and researchers 👨‍🏫. He led several national and EU-funded evaluations, contributed to medical technology strategy development, and presided over major conferences including the World Congress on Biomedical Engineering. His balanced blend of research, leadership, and mentorship reflects a career dedicated to advancing healthcare through engineering 🔬❤️.

🔬 Research Interests

Prof. Dössel’s research spans electrocardiology, cardiac modeling, medical imaging, and AI-based signal analysis 💓🖥️. He has advanced the understanding of atrial arrhythmias, ECG-imaging, and the inverse problem of electrocardiography. His work in computer-assisted heart modeling and impedance tomography has been internationally recognized, offering new insights into heart rhythms and diagnostic imaging. Using advanced algorithms and simulations, his research bridges clinical cardiology and engineering innovation ⚡📊. A pioneer in applying artificial intelligence to bioelectric signals, he enhances non-invasive diagnostics and patient-specific treatments. Prof. Dössel continues to shape the future of digital medicine, contributing to more accurate, personalized, and safer diagnostic tools worldwide 🌍🧬.

🏆 Awards and Honors

Prof. Dössel’s excellence has been widely recognized through prestigious awards 🥇. He received the Ragnar Granit Prize in 2003 for outstanding achievements in biomedical signal analysis and KIT’s Verdienstnadel in 2024 for exceptional service. His academic stature is underscored by multiple Fellowships, including with IAMBE, IUPESM, EAMBES, and DGBMT 🌐. He’s also a member of elite academies such as acatech, the Berlin-Brandenburg Academy of Sciences, and the North Rhine-Westphalian Academy 🏛️. His leadership in global scientific evaluation panels, advisory boards, and journal editorships—including Biomedical Engineering—further validates his impact on the international research landscape. These honors reflect a career defined by innovation, vision, and global collaboration 🌟.

🧠 Research Skills

Prof. Dössel exhibits mastery across computational modeling, biosignal processing, cardiac simulation, and medical imaging 📊💡. He possesses advanced skills in numerical methods, ECG data interpretation, inverse problem-solving, and AI applications in medicine. His expertise extends to interdisciplinary integration, bringing physics, engineering, and life sciences together to solve complex health problems 🔄🔍. As an editor and evaluator, he demonstrates critical analysis, peer review excellence, and strategic foresight in emerging biomedical trends. Equally important is his mentorship and ability to translate research into teaching, conference leadership, and policy impact. Prof. Dössel’s technical breadth, from theory to clinical translation, makes him a gold standard in biomedical engineering education and innovation 🧬🛠️.

Publications Top Note 📝

  • Title: Estimating Cardiac Active Tension from Wall Motion—An Inverse Problem of Cardiac Biomechanics
    Authors: Olaf Dössel et al.
    Year: 2021
    Citations: 6
    Source: Conference Proceedings (Open Access)

  • Title: Development of a Human Body Model for Numerical Calculation of Electrical Fields
    Authors: FB Sachse, CD Werner, K Meyer-Waarden, O Dössel
    Year: 2000
    Citations: 61
    Source: Computerized Medical Imaging and Graphics, Volume 24, Issue 3, Pages 165–171
    DOI / Link: ScienceDirect – CMIG Journal

  • Title: CVAR‑Seg: An Automated Signal Segmentation Pipeline for Conduction Velocity and Amplitude Restitution
    Authors: Olaf Dössel et al.
    Year: 2021
    Citations: 7
    Source: Frontiers in Physiology

  • Title: A Bi-atrial Statistical Shape Model for Large-scale In Silico Studies of Human Atria: Model Development and Application to ECG Simulations
    Authors: C Nagel, S Schuler, O Dössel, A Loewe
    Year: 2021
    Citations: 57
    Source: Medical Image Analysis, Volume 74, Article 102210
    DOI / Link: Medical Image Analysis – Elsevier

  • Title: A Reproducible Protocol to Assess Arrhythmia Vulnerability In Silico
    Authors: Olaf Dössel et al.
    Year: 2021
    Citations: 24
    Source: Frontiers in Physiology

  • Title: Machine Learning Enables Noninvasive Prediction of Atrial Fibrillation Driver Location and Acute Pulmonary Vein Ablation Success Using the 12-lead ECG
    Authors: G Luongo, L Azzolin, S Schuler, MW Rivolta, TP Almeida, JP Martínez, … O Dössel
    Year: 2021
    Citations: 47
    Source: Cardiovascular Digital Health Journal, Volume 2, Issue 2, Pages 126–136
    DOI / Link: Cardiovascular Digital Health Journal

  • Title: Cycle Length Statistics During Human Atrial Fibrillation
    Authors: Olaf Dössel et al.
    Year: 2021
    Citations: 10
    Source: Europace

  • Title: Parameter Estimation of Ion Current Formulations Requires Hybrid Optimization Approach to Be Both Accurate and Reliable
    Authors: A Loewe, M Wilhelms, J Schmid, MJ Krause, F Fischer, D Thomas, … O Dössel
    Year: 2016
    Citations: 31
    Source: Frontiers in Bioengineering and Biotechnology, Volume 3, Article 209
    DOI / Link: Frontiers – Bioengineering and Biotechnology

  • Title: Non‑Invasive Characterization of Atrial Flutter Using Recurrence Quantification on ECG
    Authors: Olaf Dössel et al.
    Year: 2021
    Citations: 18
    Source: IEEE Transactions on Biomedical Engineering

  • Title: Selective Brain Hypothermia for MCA-M1 Stroke: A 3D Brain Temperature Model
    Authors: Olaf Dössel et al.
    Year: 2021
    Citations: 8
    Source: IEEE Transactions on Biomedical Engineering

  • Title: Regional Lung Perfusion in ARDS by Impedance and CT
    Authors: Olaf Dössel et al.
    Year: 2021
    Citations: 50
    Source: IEEE Transactions on Medical Imaging

  • Title: ECGdeli: An Open Source ECG Delineation Toolbox for MATLAB
    Authors: Olaf Dössel et al.
    Year: 2021
    Citations: 52
    Source: SoftwareX

  • Title: Quantification of Potassium and Calcium Disorders via ECG
    Authors: Olaf Dössel et al.
    Year: 2021
    Citations: 13
    Source: Review Article (Journal)

  • Title: Electrogram Characteristics of Extra‑Pulmonary Vein AF Sources
    Authors: Olaf Dössel et al.
    Year: 2020
    Citations: 35
    Source: Scientific Reports

📌 Conclusion

Prof. Dr. Olaf Dössel is a luminary in biomedical engineering, whose work has transformed cardiovascular diagnostics, research methodologies, and interdisciplinary science 🌟. With a career spanning 40+ years, over 700 publications 📚, and leadership roles in global conferences, advisory panels, and academic societies, he has shaped generations of engineers and physicians. His holistic approach—combining education, innovation, and evaluation—continues to influence medical technology worldwide 🌍❤️. Post-retirement, he remains an active mentor, evaluator, and thought leader, championing responsible research and forward-thinking solutions. Prof. Dössel’s legacy is not just academic excellence but also the creation of a robust, ethical, and innovative biomedical engineering ecosystem 🚀🔬.

Raquel Lacuesta Gilaberte | Artificial Intelligence in Mathematics | Women Researcher Award

Published on by Math Scientist

Prof. Dr. Raquel Lacuesta Gilaberte | Artificial Intelligence in Mathematics | Women Researcher Award

Researcher and Lecturer at Universidad de Zaragoza , Spain

Prof. Dr. Raquel Lacuesta Gilaberte 🎓, a distinguished academic from the Universidad de Zaragoza 🇪🇸, is a seasoned expert in Computer Science and Human-Computer Interaction 💻🧠. With a Ph.D. Cum Laude from the Universidad Politécnica de Valencia 🎖️, she brings over two decades of dedication to teaching, mentoring, and interdisciplinary research. Her work spans digital interaction design, intelligent systems 🤖, and healthcare technologies 🏥💡, making significant contributions to both education and applied science. As a full-time professor, she has spearheaded numerous courses in engineering, health innovation, and digital systems, inspiring future technologists and innovators. Fluent in English 🌍, she’s well-positioned for global collaboration. Her academic journey reflects a blend of visionary thinking, pedagogical depth, and technological curiosity, marking her as a dynamic force in the engineering and research ecosystem 🚀📘.

Professional Profile 

Google Scholar
Scopus Profile
ORCID Profile

🎓 Education

Prof. Dr. Raquel Lacuesta Gilaberte holds a prestigious academic lineage rooted in technical excellence. She earned her degree in Computer Engineering from the Universidad Politécnica de Valencia 🏛️ in 1999 and went on to complete her Ph.D. in Computer Science in 2008 with the esteemed Cum Laude distinction 🏅. Her doctoral studies deepened her expertise in informatics, laying a strong foundation for a career at the nexus of innovation and systems architecture. This elite academic path reflects her unwavering commitment to scholarly rigor and intellectual development. Her comprehensive training in both theoretical and applied computing equips her to seamlessly bridge academia and real-world technology 🌐💡.

🧑‍🏫 Professional Experience

With over 15 years of academic service, Prof. Dr. Lacuesta currently serves as a Professor Titular at the Universidad de Zaragoza 👩‍🏫. Since 2018, she has dedicated herself full-time to the Department of Computer Science and Systems Engineering, shaping the minds of future engineers. Her teaching portfolio is both broad and impactful—spanning information systems, human-computer interaction, digital design, and cybersecurity 🔐. Beyond instruction, she plays a pivotal role in curriculum development for undergraduate and master’s programs. Her long-term affiliation with various innovative teaching initiatives reflects a career devoted not just to knowledge dissemination but to shaping evolving educational ecosystems 🏫🚀.

🔬 Research Interests

Prof. Dr. Lacuesta’s research navigates the confluence of technology and human experience. Her primary interests include Human-Computer Interaction (HCI) 🖥️🤝, user-centered digital design 🎨, multi-agent systems 🤖, and health-focused technology applications 🩺📲. She actively explores how emerging interfaces can enhance user accessibility and well-being, especially within medical and wellness contexts. Her work in intelligent systems and decision-support architectures positions her at the forefront of digital innovation. The interdisciplinary nature of her research enables her to address complex challenges through holistic, systems-oriented solutions. Driven by curiosity and social impact, her research continuously adapts to the dynamic needs of the digital age 🌍⚙️.

🏆 Awards and Honors

While her formal accolades were not detailed in the provided records, Prof. Dr. Lacuesta’s academic career reflects honors embedded in her roles and responsibilities. Attaining a Ph.D. with Cum Laude honors 🎖️ signals excellence at the doctoral level. Her continuous presence in postgraduate and interdisciplinary programs is itself a recognition of her expertise and reliability. Trusted to lead innovation-focused subjects in health tech and interactive systems, she enjoys peer respect and institutional recognition 🌟. Her appointment to key academic roles and her involvement in diverse teaching environments speak volumes of the esteem she commands in academic circles. Future awards will likely follow as her research visibility grows.

🔚 Conclusion

Prof. Dr. Raquel Lacuesta Gilaberte exemplifies the modern academic—technically astute, pedagogically impactful, and research-driven 💼🧠. Her journey from a top-tier engineering graduate to a full-time professor reflects perseverance, scholarly excellence, and a forward-looking mindset. With deep roots in computing and branches extending into healthcare innovation and interactive design, she stands as a beacon of interdisciplinary progress 🌱🔍. Though understated in accolades, her real reward lies in shaping students, pushing boundaries in tech-for-good, and mentoring in future-centric domains. She is unquestionably a standout candidate for recognition such as the Best Researcher Award 🏅🌟.

Publications Top Notes

Redesign and New Evaluation of a Pervasive Game for Older Adults
👥 Jesús Gallardo, Raquel Lacuesta, Silvia Ramis
📅 2024 | 📈 0 citations
📄 Conference Paper | DOI: Not provided

Exploring the Use of Voice Assistants in Nursing Homes
👥 Eva Cerezo, Raquel Lacuesta, Jesús Gallardo, Antonio Aguelo
📅 2025 | 📈 1 citation
📄 International Journal of Human–Computer Interaction
🔗 DOI: 10.1080/10447318.2025.2470282

Cooking Game: A Serious Game Using a Social Robot
👥 Joan Josep Ordoñez, Silvia Ramis, Francisco J. Perales, Jose M. Buades, Raquel Lacuesta
📅 2024 | 📈 1 citation
📄 Conference Paper
🔗 DOI: 10.1145/3657242.3658604

A New Online Tool to Evaluate Transferable Skills in the European Framework
👥 Raquel Lacuesta, G. Palacios-Navarro
📅 2024 | 📈 0 citations
📄 International Journal of Engineering Pedagogy | DOI not listed

Wearable Low-Cost and Low-Energy Consumption Gas Sensor with Machine Learning to Recognize Outdoor Areas
👥 Jianchen Wang, Lorena Parra, Raquel Lacuesta, Jaime Lloret, Pascal Lorenz
📅 2024 | 📈 0 citations
📄 IEEE Sensors Journal
🔗 DOI: 10.1109/JSEN.2024.3442874

Ubiquitous Monitoring of Liver Transplantation Patients
👥 Javier Navarro-Alamán, Raquel Lacuesta, Jose M. Jimenez, Iván García-Magariño, Trinidad Serrano
📅 2024 | 📈 1 citation
📄 International Journal of Ad Hoc and Ubiquitous Computing | DOI not listed

Evaluation of Suitability of Low-Cost Gas Sensors for Monitoring Indoor and Outdoor Urban Areas
👥 Jianchen Wang, Sandra Viciano-Tudela, Lorena Parra, Raquel Lacuesta, Jaime Lloret
📅 2023 | 📈 16 citations
📄 IEEE Sensors Journal
🔗 DOI: 10.1109/JSEN.2023.3301651

Cybersecure XAI Algorithm for Generating Recommendations Based on Financial Fundamentals Using DeepSeek
👥 Iván García-Magariño, Javier Bravo-Agapito, Raquel Lacuesta
📅 2025 | 📈 N/A
📄 AI (Open Access Journal)
🔗 DOI: 10.3390/ai6050095

Designing Pervasive Games Oriented Towards the Elderly: A Case Study
👥 Raquel Lacuesta, Jesús Gallardo, Silvia Hernández, Álvaro Pérez
📅 2023 | 📈 N/A
📄 Book Chapter
🔗 DOI: 10.1007/978-3-031-37496-8_13

Early Detection of Abandonment Signs in Interactive Novels with a Randomized Forest Classifier
👥 Javier Navarro, Iván García-Magariño, Jorge J. Gómez Sanz, Raquel Lacuesta, Rubén Fuentes, Juan Pavón
📅 2022 | 📈 N/A
📄 Book Chapter
🔗 DOI: 10.1007/978-3-031-22419-5_18

 

 

 

Shijie Zhao | Applied Mathematics | Best Researcher Award

Published on by Math Scientist

Assoc. Prof. Dr. Shijie Zhao | Applied Mathematics | Best Researcher Award

Associate Professor at Liaoning Technical University, China

Assoc. Prof. Dr. Shijie Zhao is a distinguished researcher and academic at the Institute of Intelligence Science and Optimization, Liaoning Technical University, China. With a Ph.D. in Optimization and Management Decisions, his expertise lies in metaheuristic optimization, multi-objective optimization, and underwater navigation and positioning. He has made significant contributions through innovative algorithm designs and novel mathematical models, particularly in high-dimensional feature selection and robust navigation techniques. Dr. Zhao has published 9 SCI-indexed journal articles and participated in over 10 nationally and provincially funded research projects. He serves as a reviewer for leading journals including those by Elsevier, Springer, and IEEE, and holds memberships in 13 professional bodies. With strong programming skills, rigorous analytical thinking, and a commitment to scientific innovation, Dr. Zhao has also earned four research awards. His work bridges theoretical mathematics and practical applications, making him a valuable contributor to the global research community in intelligent systems and optimization.

Professional Profile 

Scopus Profile
ORCID Profile

Education

Assoc. Prof. Dr. Shijie Zhao has a robust academic foundation anchored at Liaoning Technical University, China. He earned his B.S. degree in Science of Information & Computation in 2012, followed by a successive postgraduate and doctoral program in Mathematics and Applied Mathematics from 2012 to 2014. He went on to complete his Ph.D. in Optimization and Management Decisions in 2018. His educational trajectory highlights a deep commitment to the field of mathematical optimization and intelligent systems. Dr. Zhao’s academic excellence is also reflected in his ability to integrate theoretical knowledge with practical problem-solving, laying a strong foundation for his future research. His interdisciplinary approach blends pure mathematics with applied optimization techniques, making him uniquely positioned to contribute to emerging challenges in computational intelligence, machine learning, and navigation systems. His comprehensive training has equipped him with skills in advanced mathematical modeling, algorithm design, and statistical analysis—all crucial for his research trajectory.

Professional Experience

Dr. Shijie Zhao began his professional journey as a faculty member at Liaoning Technical University, where he is now serving as an Associate Professor and Director of the Institute of Intelligence Science and Optimization. Since 2012, he has progressed through a series of academic roles, including a postdoctoral tenure beginning in 2020. He has successfully led and participated in a range of scientific research projects sponsored by institutions such as the China Postdoctoral Science Foundation and the Department of Science & Technology of Liaoning Province. In addition to his teaching responsibilities, he has been actively involved in administrative, academic, and research leadership roles. Dr. Zhao has served as a reviewer for numerous high-impact international journals and conferences and has editorial roles in reputed scientific publications. His contributions to collaborative and interdisciplinary projects underscore his ability to bridge research and real-world applications, enhancing his standing as a key contributor in intelligent systems research.

Research Interest

Assoc. Prof. Dr. Shijie Zhao’s research interests lie at the intersection of intelligent optimization, computational mathematics, and advanced data analytics. He specializes in the development and enhancement of metaheuristic and multi-objective optimization algorithms, addressing both theoretical and application-driven challenges. His work has pioneered novel strategies for high-dimensional feature selection and optimization in machine learning contexts. Another key area of his focus is underwater navigation and positioning, where he has introduced innovative models for enhancing gravity navigation accuracy. With a strong foundation in mathematics, Dr. Zhao combines theoretical rigor with practical applicability, ensuring that his research contributes both to academic knowledge and technological development. His recent work explores how optimization strategies can be integrated into real-time systems, with implications in robotics, autonomous navigation, and engineering design. By addressing complex computational problems, Dr. Zhao’s research plays a vital role in driving forward the capabilities of intelligent systems and adaptive algorithms.

Award and Honor

Dr. Shijie Zhao has earned multiple accolades in recognition of his impactful contributions to scientific research and innovation. He has received four prestigious research awards for his work in intelligent systems, mathematical optimization, and applied computational modeling. His leadership in various national and provincial research initiatives has further cemented his reputation as a top-tier researcher in his domain. In addition to these honors, he has held editorial and reviewer positions for over ten internationally recognized journals, including publications by IEEE, Springer, and Elsevier—an acknowledgment of his expertise and academic integrity. Dr. Zhao is also an active member of 13 professional bodies, reflecting his global engagement and scholarly influence. His participation in high-impact collaborative projects and his growing citation index underscore the recognition and respect he commands in the research community. These honors validate his innovative spirit and unwavering dedication to advancing knowledge in mathematics and intelligent computing.

Conclusion

In conclusion, Assoc. Prof. Dr. Shijie Zhao exemplifies excellence in mathematical research, optimization theory, and intelligent system applications. His educational background, combined with over a decade of professional experience, positions him as a thought leader in his field. Through pioneering contributions to metaheuristic algorithms, multi-objective optimization, and underwater navigation, he bridges the gap between theoretical frameworks and practical technologies. His commitment to research integrity, academic service, and innovation has earned him widespread recognition and professional accolades. As an educator, leader, and scientist, Dr. Zhao’s multifaceted contributions reflect a deep dedication to advancing scientific knowledge and solving complex global challenges. His future endeavors are poised to have even greater impacts on the fields of artificial intelligence, data-driven decision-making, and intelligent navigation. With a strong publication record, a solid foundation in mathematics, and an expanding research network, Dr. Zhao continues to be a prominent and influential figure in the global academic landscape.

Publications Top Notes

  • Title: ID2TM: A Novel Iterative Double-Cross Domain-Center Transfer-Matching Method for Underwater Gravity-Aided Navigation
    Authors: Shijie Zhao, Zhiyuan Dou, Huizhong Zhu, Wei Zheng, Yifan Shen
    Year: 2025
    Source: IEEE Internet of Things Journal

  • Title: OS-BiTP: Objective sorting-informed bidomain-information transfer prediction for dynamic multiobjective optimization
    Authors: Shijie Zhao, Tianran Zhang, Lei Zhang, Jinling Song
    Year: 2025
    Source: Swarm and Evolutionary Computation

  • Title: Mirage search optimization: Application to path planning and engineering design problems
    Authors: Jiahao He, Shijie Zhao, Jiayi Ding, Yiming Wang
    Year: 2025
    Source: Advances in Engineering Software

  • Title: Twin-population Multiple Knowledge-guided Transfer Prediction Framework for Evolutionary Dynamic Multi-Objective Optimization
    Authors: Shijie Zhao, Tianran Zhang, Miao Chen, Lei Zhang
    Year: 2025
    Source: Applied Soft Computing

  • Title: VC-TpMO: V-dominance and staged dynamic collaboration mechanism based on two-population for multi- and many-objective optimization algorithm
    Authors: Shijie Zhao, Shilin Ma, Tianran Zhang, Miao Chen
    Year: 2025
    Source: Expert Systems with Applications

  • Title: A Novel Cross-Line Adaptive Domain Matching Algorithm for Underwater Gravity Aided Navigation
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2024
    Source: IEEE Geoscience and Remote Sensing Letters

  • Title: Triangulation topology aggregation optimizer: A novel mathematics-based meta-heuristic algorithm for continuous optimization and engineering applications
    Authors: Shijie Zhao, Tianran Zhang, Liang Cai, Ronghua Yang
    Year: 2024
    Source: Expert Systems with Applications

  • Title: Improving Matching Efficiency and Out-of-Domain Positioning Reliability of Underwater Gravity Matching Navigation Based on a Novel Domain-Center Adaptive-Transfer Matching Method
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2023
    Source: IEEE Transactions on Instrumentation and Measurement

  • Title: A dynamic support ratio of selected feature-based information for feature selection
    Authors: Shijie Zhao, Mengchen Wang, Shilin Ma, Qianqian Cui
    Year: 2023
    Source: Engineering Applications of Artificial Intelligence

  • Title: Sea-horse optimizer: a novel nature-inspired meta-heuristic for global optimization problems
    Authors: Shijie Zhao, Tianran Zhang, Shilin Ma, Mengchen Wang
    Year: 2023
    Source: Applied Intelligence

  • Title: Improving the Out-of-Domain Matching Reliability and Positioning Accuracy of Underwater Gravity Matching Navigation Based on a Novel Cyclic Boundary Semisquare-Domain Researching Method
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2023
    Source: IEEE Sensors Journal

  • Title: A feature selection method via relevant-redundant weight
    Authors: Shijie Zhao, Mengchen Wang, Shilin Ma, Qianqian Cui
    Year: 2022
    Source: Expert Systems with Applications

  • Title: Dandelion Optimizer: A nature-inspired metaheuristic algorithm for engineering applications
    Authors: Shijie Zhao, Tianran Zhang, Shilin Ma, Miao Chen
    Year: 2022
    Source: Engineering Applications of Artificial Intelligence

  • Title: Improving Matching Efficiency and Out-of-domain Reliability of Underwater Gravity Matching Navigation Based on a Novel Soft-margin Local Semicircular-domain Re-searching Model
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2022
    Source: Remote Sensing

  • Title: Improving Matching Accuracy of Underwater Gravity Matching Navigation Based on Iterative Optimal Annulus Point Method with a Novel Grid Topology
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Aigong Xu, Huizhong Zhu
    Year: 2021
    Source: Remote Sensing

  • Title: A Novel Quantum Entanglement‐Inspired Meta‐heuristic Framework for Solving Multimodal Optimization Problems
    Authors: Shijie Zhao
    Year: 2021
    Source: Chinese Journal of Electronics

  • Title: A Novel Modified Tree‐Seed Algorithm for High‐Dimensional Optimization Problems
    Authors: Shijie Zhao
    Year: 2020
    Source: Chinese Journal of Electronics