Shijie Zhao | Applied Mathematics | Best Researcher Award

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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 

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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

 

Mojtaba Lashgari | Geometry | Best Researcher Award

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Dr. Mojtaba Lashgari | Geometry | Best Researcher Award

Research fellow at University of Oxford, United Kingdom

Dr. Mojtaba Lashgari is an accomplished researcher in biomedical engineering and computer science, currently serving as a postdoctoral researcher at the University of Oxford. With a PhD from the University of Leeds and a Marie Curie Early-Stage Research Scholarship, his work bridges artificial intelligence, medical image analysis, and computational modeling. Dr. Lashgari has published extensively in top-tier journals such as Medical Image Analysis and IEEE Transactions on Image Processing, focusing on virtual imaging trials, cardiac MRI, and coronary vessel segmentation. He has presented his research at international conferences and played active roles in scientific committees and conference organization. His interdisciplinary expertise, from MRI physics to deep learning, underpins innovative solutions in healthcare technology. Through academic service, teaching, and high-impact collaborations, Dr. Lashgari exemplifies scientific excellence and leadership. His work is contributing to the future of personalized medicine and diagnostic imaging, making him a highly deserving candidate for the Best Researcher Award.

Professional Profile 

Google Scholar
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Education

Dr. Mojtaba Lashgari’s educational background reflects a strong interdisciplinary foundation in engineering, biomedical sciences, and computational research. He earned his PhD in Computer Science from the University of Leeds in 2023, where he specialized in advanced medical image analysis and virtual imaging trials. Prior to this, he completed a Master of Science in Biomedical Engineering from Isfahan University of Medical Sciences in 2016, graduating as the top-ranked student in his cohort. His academic journey began with a Bachelor of Science in Electrical Engineering from Malek-Ashtar University of Technology in 2013, where he developed a solid base in electronics and signal processing. This unique blend of electrical, biomedical, and computer science education has equipped Dr. Lashgari with the analytical, technical, and problem-solving skills required for high-level research in medical technology and artificial intelligence. His academic achievements have been consistently marked by excellence, innovation, and a clear focus on impactful, real-world applications.

Professional Experience

Dr. Mojtaba Lashgari has accumulated rich and diverse professional experience across leading academic institutions and interdisciplinary research domains. Currently, he serves as a Postdoctoral Researcher in the Department of Engineering Science at the University of Oxford (2023–2026), where he is engaged in pioneering research in medical imaging and AI-driven healthcare solutions. Prior to this, he worked as a part-time Technical Engineer at the Institute of Transport Studies, University of Leeds, contributing to computational modeling projects. His research journey also includes a tenure as a Graduate Researcher at the Medical Image and Signal Processing Research Centre in Isfahan, Iran, where he deepened his expertise in biomedical image analysis. Throughout his career, Dr. Lashgari has been actively involved in teaching, academic service, and organizing scientific events. His roles have consistently demonstrated his capabilities in bridging engineering, medicine, and computational sciences, establishing him as a well-rounded researcher with both technical depth and collaborative breadth.

Research Interest

Dr. Mojtaba Lashgari’s research interests lie at the dynamic intersection of medical imaging, computational modeling, and artificial intelligence. He is particularly passionate about developing innovative solutions for medical image analysis, with a focus on MRI physics, diffusion-weighted imaging, and virtual imaging trials. His work encompasses both model-based and image-based methodologies, integrating techniques such as finite element analysis, inverse problems, and machine and deep learning algorithms to simulate and interpret complex biological systems. A key area of his research involves the creation of patient-specific in-silico models to improve diagnostic accuracy and procedural planning in cardiovascular medicine. Dr. Lashgari is also deeply involved in advancing domain generalization methods for coronary vessel segmentation, aiming to enhance clinical applicability and robustness across diverse imaging environments. His interdisciplinary approach strives to bridge engineering, biomedical science, and data science, contributing significantly to the future of precision medicine and computational healthcare.

Award and Honor

Dr. Mojtaba Lashgari has been recognized with several prestigious awards and honors that underscore his academic excellence and impactful research contributions. He was awarded the esteemed Marie Sklodowska-Curie Early-Stage Research Doctoral Scholarship in 2018, a testament to his potential in cutting-edge scientific innovation at the European level. In 2024, he received a partial scholarship to attend the Virtual Imaging Trial in Medicine (VITM) Summit at Duke University, USA, further highlighting his growing international recognition. His academic brilliance was also evident early in his career when he ranked first in his M.Sc. Biomedical Engineering class at Isfahan University of Medical Sciences in 2016. These honors reflect Dr. Lashgari’s dedication to advancing medical imaging technologies and his leadership within the global research community. His active involvement in scientific committees and organization of high-impact academic events also reinforces his role as an emerging thought leader in biomedical engineering and computational imaging science.

Conclusion

Dr. Mojtaba Lashgari stands out as a highly accomplished and forward-thinking researcher at the intersection of biomedical engineering, computer science, and medical image analysis. With a PhD from the University of Leeds and a current postdoctoral position at the University of Oxford, his academic journey reflects a deep commitment to scientific excellence. His contributions span advanced MRI simulations, deep learning for image segmentation, and virtual imaging trials, underscoring his role in shaping the future of computational medical diagnostics. Recognized with prestigious awards such as the Marie Curie Fellowship and actively engaged in academic leadership, Dr. Lashgari has proven himself a driving force in interdisciplinary research. His impactful publications, teaching roles, and organizational contributions further highlight his versatility and dedication. With a visionary approach to science and a growing international presence, Dr. Lashgari is well-positioned to make lasting contributions to healthcare technology and deserves strong consideration for the Best Researcher Award.

Publications Top Notes

  1. Title: A comparative study of new and current methods for dental micro-CT image denoising
    Authors: M Shahmoradi, M Lashgari, H Rabbani, J Qin, M Swain
    Year: 2016
    Citations: 29
    Source: Dentomaxillofacial Radiology, 45(3), 20150302

  2. Title: Missing surface estimation based on modified Tikhonov regularization: Application for destructed dental tissue
    Authors: M Lashgari, M Shahmoradi, H Rabbani, M Swain
    Year: 2018
    Citations: 16
    Source: IEEE Transactions on Image Processing, 27(5), 2433–2446

  3. Title: A fast and accurate dental micro-CT image denoising based on total variation modeling
    Authors: M Lashgari, H Rabbani, M Shahmorad, M Swain
    Year: 2015
    Citations: 7
    Source: 2015 IEEE Workshop on Signal Processing Systems (SiPS), pp. 1–5

  4. Title: Three-dimensional micro-structurally informed in silico myocardium—Towards virtual imaging trials in cardiac diffusion weighted MRI
    Authors: M Lashgari, N Ravikumar, I Teh, JR Li, DL Buckley, JE Schneider, …
    Year: 2022
    Citations: 4
    Source: Medical Image Analysis, 82, 102592

  5. Title: Patient-specific in silico 3D coronary model in cardiac catheterisation laboratories
    Authors: M Lashgari, RP Choudhury, A Banerjee
    Year: 2024
    Citations: 2
    Source: Frontiers in Cardiovascular Medicine, 11, 1398290

  6. Title: SpinDoctor-IVIM: A virtual imaging framework for intravoxel incoherent motion MRI
    Authors: M Lashgari, Z Yang, MO Bernabeu, JR Li, AF Frangi
    Year: 2025
    Citations: 1
    Source: Medical Image Analysis, 99, 103369

  7. Title: Reconstruction of Connected Digital Lines Based on Constrained Regularization
    Authors: M Lashgari, H Rabbani, G Plonka, I Selesnick
    Year: 2022
    Citations: 1
    Source: IEEE Transactions on Image Processing, 31, 5613–5628

  8. Title: Splitting and Merging for Active Contours: Plug-and-Play
    Authors: M Lashgari, A Banerjee, H Rabbani
    Year: 2025
    Source: Mathematics, 13(6), 991

  9. Title: Virtual Imaging Trial can Unveil the Relationship Between Intravascular Diffusivity and Intravoxel Incoherent Motion in MRI
    Authors: M Lashgari, Z Yang, MO Bernabeu, JR Li, AF Frangi
    Year: 2024
    Source: Proceedings Virtual Imaging Trials in Medicine 2024, 1, 146

  10. Title: An in silico imaging framework for microstructure-sensitive myocardial diffusion-weighted MRI
    Author: M Lashgari
    Year: 2023
    Source: PhD Thesis, University of Leeds

  11. Title: Myocardium numerical phantom at micro-scale: application in MRI simulation
    Authors: M Lashgari, N Ravikumar, I Teh, J Schneider, A Frangi
    Year: 2021
    Source: Book of Abstracts, ESMRMB 2021 Online, 38th Annual Scientific Meeting

 

Mohammed Hussein | Applied Mathematics | Best Researcher Award

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Prof. Mohammed Hussein | Applied Mathematics | Best Researcher Award

Academia at University of Baghdad, Iran

Dr. Mohammed Sabah Hussein is a distinguished Professor of Applied Mathematics at the University of Baghdad, College of Science, with a Ph.D. from the University of Leeds. With 18 years of teaching and research experience, his expertise spans inverse problems for heat equations, numerical analysis, fluid dynamics, and mathematical modeling. He has made significant contributions to academia, mentoring postgraduate students and serving in leadership roles, including Head of the Mathematics Department. Dr. Hussein has an impressive publication record in high-impact journals and actively participates in international research collaborations. His academic reputation is reflected in his H-index rankings across Google Scholar, Scopus, and Clarivate. As a member of several professional societies and editorial boards, he is dedicated to advancing applied mathematics. His technical proficiency in MATLAB, Mathematica, and LaTeX, coupled with his extensive research on solving complex mathematical problems, makes him a leading figure in his field.

Professional Profile 

Google Scholar
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ORCID Profile

Education

Dr. Mohammed Sabah Hussein earned his Ph.D. in Applied Mathematics from the University of Leeds, where he specialized in inverse problems for heat equations and numerical analysis. Prior to that, he obtained his Master’s and Bachelor’s degrees in Mathematics from the University of Baghdad, demonstrating early excellence in mathematical modeling and computational techniques. His academic journey has been marked by a strong foundation in mathematical theories, which he later expanded through advanced research in applied mathematics and fluid dynamics. Throughout his education, Dr. Hussein actively engaged in research projects that enhanced his expertise in solving complex mathematical problems, particularly in heat transfer and differential equations. His exposure to international academic environments enriched his analytical skills and deepened his understanding of mathematical applications in real-world scenarios. His educational background continues to influence his teaching and research, enabling him to contribute significantly to mathematical sciences and mentor future scholars in applied mathematics.

Professional Experience

Dr. Mohammed Sabah Hussein is a Professor of Applied Mathematics at the University of Baghdad, College of Science, with 18 years of experience in teaching and research. He has held several academic leadership roles, including serving as Head of the Mathematics Department, where he played a crucial role in curriculum development and faculty mentoring. Over the years, he has supervised numerous postgraduate students, guiding them in advanced mathematical research. Dr. Hussein has collaborated with international institutions on cutting-edge research projects in applied mathematics, enhancing interdisciplinary studies. He has also served as a reviewer and editorial board member for prestigious mathematical journals, contributing to the peer-review process. His expertise in numerical methods, fluid dynamics, and inverse problems has led him to participate in global awards and workshops, where he shares his insights with the academic community. His commitment to research and education solidifies his standing as a leading mathematician.

Research Interest

Dr. Mohammed Sabah Hussein’s research focuses on inverse problems for heat equations, numerical analysis, fluid dynamics, and mathematical modeling. He specializes in solving complex differential equations that arise in real-world applications, particularly in heat transfer and fluid mechanics. His work extends to computational techniques using MATLAB and Mathematica, where he develops algorithms for accurate numerical solutions. Dr. Hussein is also interested in optimization methods and their applications in engineering and physical sciences. His research has contributed to advancements in thermal analysis and industrial processes, demonstrating the practical impact of applied mathematics. Additionally, he collaborates on interdisciplinary projects that integrate mathematics with physics and engineering, broadening the scope of mathematical applications. His publications in high-impact journals reflect his dedication to innovative mathematical research, and his continued exploration of numerical simulations and mathematical modeling ensures his contributions remain at the forefront of applied mathematics advancements.

Awards and Honors

Dr. Mohammed Sabah Hussein has received several prestigious awards and honors for his outstanding contributions to applied mathematics. His research excellence has been recognized with accolades from national and international academic institutions. He has been honored for his high-impact publications and has received grants for his work in mathematical modeling and numerical analysis. Dr. Hussein’s influence in academia is further demonstrated by his strong citation record and H-index rankings in Google Scholar, Scopus, and Clarivate. He has been invited as a keynote speaker at global awards and has received recognition for his mentorship of postgraduate students. His role in advancing mathematical sciences has been acknowledged through memberships in esteemed mathematical societies and editorial boards of reputed journals. These honors reflect his dedication to academic excellence and his influence on the broader mathematical research community.

Conclusion

Dr. Mohammed Sabah Hussein is a highly respected mathematician whose expertise in applied mathematics has significantly impacted academia and research. With a strong educational background and extensive professional experience, he has contributed to solving complex mathematical problems through advanced numerical analysis and modeling. His dedication to mentoring students, publishing high-impact research, and collaborating internationally highlights his commitment to the mathematical sciences. His awards and honors reflect his scholarly influence and contributions to mathematical research. As a professor, researcher, and mentor, Dr. Hussein continues to advance applied mathematics, ensuring its relevance in solving real-world challenges. His work in inverse problems, fluid dynamics, and computational methods cements his reputation as a leader in the field. Through his academic and research endeavors, he remains dedicated to pushing the boundaries of mathematical knowledge and inspiring future generations of mathematicians.

Publications Top Noted

1. Simultaneous determination of time-dependent coefficients in the heat equation

Authors: M. S. Hussein, D. Lesnic, M. I. Ivanchov
Year: 2014
Citations: 61
Source: Computers & Mathematics with Applications, 67(5), 1065-1091

2. An inverse problem of finding the time‐dependent diffusion coefficient from an integral condition

Authors: M. S. Hussein, D. Lesnic, M. I. Ismailov
Year: 2016
Citations: 49
Source: Mathematical Methods in the Applied Sciences, 39(5), 963-980

3. Reconstruction of time-dependent coefficients from heat moments

Authors: M. J. Huntul, D. Lesnic, M. S. Hussein
Year: 2017
Citations: 45
Source: Applied Mathematics and Computation, 301, 233-253

4. Simultaneous determination of time and space-dependent coefficients in a parabolic equation

Authors: M. S. Hussein, D. Lesnic
Year: 2016
Citations: 38
Source: Communications in Nonlinear Science and Numerical Simulation, 33, 194-217

5. Multiple time-dependent coefficient identification thermal problems with a free boundary

Authors: M. S. Hussein, D. Lesnic, M. I. Ivanchov, H. A. Snitko
Year: 2016
Citations: 37
Source: Applied Numerical Mathematics, 99, 24-50

6. Direct and inverse source problems for degenerate parabolic equations

Authors: M. S. Hussein, D. Lesnic, V. L. Kamynin, A. B. Kostin
Year: 2020
Citations: 35
Source: Journal of Inverse and Ill-Posed Problems, 28(3), 425-448

7. Simultaneous determination of time-dependent coefficients and heat source

Authors: M. S. Hussein, D. Lesnic
Year: 2016
Citations: 24
Source: International Journal for Computational Methods in Engineering Science and Mechanics

8. Identification of the time-dependent conductivity of an inhomogeneous diffusive material

Authors: M. S. Hussein, D. Lesnic
Year: 2015
Citations: 24
Source: Applied Mathematics and Computation, 269, 35-58

9. Determination of a time-dependent thermal diffusivity and free boundary in heat conduction

Authors: M. S. Hussein, D. Lesnic
Year: 2014
Citations: 23
Source: International Communications in Heat and Mass Transfer, 53, 154-163

10. Simultaneous Identification of Thermal Conductivity and Heat Source in the Heat Equation

Authors: M. J. Huntul, M. S. Hussein
Year: 2021
Citations: 20
Source: Iraqi Journal of Science, 1968-1978

11. A wavelet-based collocation technique to find the discontinuous heat source in inverse heat conduction problems

Authors: M. Ahsan, W. Lei, M. Ahmad, M. S. Hussein, Z. Uddin
Year: 2022
Citations: 16
Source: Physica Scripta, 97(12), 125208

12. Identification of a multi-dimensional space-dependent heat source from boundary data

Authors: M. S. Hussein, D. Lesnic, B. T. Johansson, A. Hazanee
Year: 2018
Citations: 16
Source: Applied Mathematical Modelling, 54, 202-220

13. Free boundary determination in nonlinear diffusion

Authors: M. S. Hussein, D. Lesnic, M. Ivanchov
Year: 2013
Citations: 16
Source: East Asian Journal on Applied Mathematics, 3(4), 295-310

14. Retrieval of Timewise Coefficients in the Heat Equation from Nonlocal Overdetermination Conditions

Authors: F. Anwer, M. S. Hussein
Year: 2022
Citations: 15
Source: Iraqi Journal of Science, 1184-1199

15. Numerical Solution to Recover Time-dependent Coefficient and Free Boundary from Nonlocal and Stefan Type Overdetermination Conditions in Heat Equation

Authors: M. Qassim, M. S. Hussein
Year: 2021
Citations: 15
Source: Iraqi Journal of Science, 62(3), 950-960

16. Determination of time-dependent coefficient in time fractional heat equation

Authors: Q. W. Ibraheem, M. S. Hussein
Year: 2023
Citations: 14
Source: Partial Differential Equations in Applied Mathematics, 7, 100492

17. Splitting the One-Dimensional Wave Equation, Part II: Additional Data are Given by an End Displacement Measurement

Authors: S. O. Hussein, M. S. Hussein
Year: 2021
Citations: 13
Source: Iraqi Journal of Science, 62(1), 233-239

18. Numerical Solution for Two-Sided Stefan Problem

Authors: M. S. Hussein, Z. Adil
Year: 2020
Citations: 12
Source: Iraqi Journal of Science, 61(2), 444-452