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.

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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

 

Halima Bensmail | Applied Mathematics | Best Researcher Award

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Prof. Dr. Halima Bensmail | Applied Mathematics | Best Researcher Award

Principal scientist at Qatar Computing Research Institute, Qatar

Dr. Halima Bensmail is a distinguished Principal Scientist at the Qatar Computing Research Institute, specializing in machine learning, bioinformatics, biostatistics, and statistical modeling. With a Ph.D. in Statistics (Summa Cum Laude) from the University Pierre & Marie Curie, she has made significant contributions to Bayesian inference, multivariate analysis, and precision medicine. She has an impressive research record with an H-index of 31, i10-index of 54, and around 140 publications in prestigious journals such as Nature Communications, JASA, and IEEE TNNLS. As the founder of the Statistical Machine Learning and Bioinformatics group at QCRI, she has led groundbreaking projects, including the development of open-source data-driven tools like the PRISQ pre-diabetes screening model and MCLUST clustering algorithm. With extensive academic experience in the USA, France, and the Netherlands, she has mentored numerous postdocs and students, shaping the next generation of researchers. Her expertise and leadership make her a key figure in data science and precision health.

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Education

Dr. Halima Bensmail holds a Ph.D. in Statistical Machine Learning (Summa Cum Laude) from the University Pierre & Marie Curie (Paris 6), where she specialized in Bayesian inference, spectral decomposition, and mixture models. Her thesis focused on deterministic and Bayesian model-based clustering and classification for data science applications. Prior to that, she earned an M.S. in Machine Learning from the same university, with a focus on probability, financial modeling, and stochastic processes. She also holds a Bachelor’s degree in Applied Mathematics and Statistics from the University Mohammed V in Morocco, where she gained expertise in numerical analysis, stochastic processes, topology, and mathematical programming. Throughout her academic journey, she was mentored by esteemed professors and developed a strong foundation in theoretical and applied statistics. Her educational background has laid the groundwork for her pioneering research in machine learning, bioinformatics, and data-driven modeling for real-world applications.

Professional Experience

Dr. Bensmail is currently a Principal Scientist at the Qatar Computing Research Institute (QCRI), where she leads research in bioinformatics, statistical machine learning, and artificial intelligence. She also serves as a Full Professor in the College of Science and Engineering at Hamad Bin Khalifa University and a Visiting Full Professor at Texas A&M University at Qatar. Previously, she held tenured faculty positions at Virginia Medical School and the University of Tennessee, where she contributed significantly to public health and business administration research. She has also worked as a Research Scientist at the University of Leiden, a scientist at the Fred Hutchinson Cancer Research Center, and a postdoctoral researcher at the University of Washington. With decades of experience across academia and research institutions in the U.S., Europe, and the Middle East, she has built expertise in developing statistical and AI-driven solutions for biomedical and computational challenges.

Research Interests

Dr. Bensmail’s research spans statistical machine learning, bioinformatics, and precision medicine. She has developed novel clustering algorithms, such as an advanced Bayesian clustering model implemented in the MCLUST package, and statistical methods for analyzing Next-Generation Sequencing (NGS) data. She is also interested in computational biology, specifically protein-protein interactions, protein solubility, and structural biology. Her work includes dimensionality reduction techniques like nonnegative matrix factorization and discriminative sparse coding for domain adaptation. In the field of precision medicine, she has designed PRISQ, a statistical model for pre-diabetes screening. Her broader interests include Bayesian statistics, functional data analysis, information theory, and high-dimensional data modeling. With a strong focus on developing real-world data-driven tools, she actively contributes to statistical methodologies that enhance decision-making in medicine, genomics, and artificial intelligence applications.

Awards and Honors

Dr. Bensmail has received numerous accolades for her contributions to machine learning, bioinformatics, and statistical modeling. Her work has been widely recognized, with over 140 peer-reviewed publications and an H-index of 31, demonstrating the impact of her research. She has secured research grants and led major projects in AI-driven healthcare solutions. Her contributions to the field have been acknowledged through invitations to serve as a keynote speaker at international awards and as an editorial board member for high-impact journals. She has also been instrumental in mentoring young researchers, postdoctoral fellows, and doctoral students, fostering the next generation of scientists in AI, statistics, and bioinformatics. Additionally, her work on statistical methods for precision medicine and biomedical informatics has gained international recognition, positioning her as a leading expert in the field of data science for healthcare and computational biology.

Conclusion

Dr. Halima Bensmail is a pioneering researcher in machine learning, statistical modeling, and bioinformatics, with a career spanning leading institutions in the U.S., Europe, and the Middle East. Her contributions to clustering algorithms, high-dimensional data analysis, and precision medicine have made a lasting impact on the fields of AI and computational biology. As a mentor and leader, she has shaped numerous young scientists and postdocs, driving innovation in data science applications. With a robust publication record, influential research projects, and a dedication to developing real-world AI-driven solutions, she stands as a leading figure in statistical machine learning. Her expertise and contributions continue to push the boundaries of knowledge in bioinformatics, artificial intelligence, and healthcare analytics, making her a strong candidate for prestigious research awards and recognition in scientific communities worldwide.

Publications Top Noted

 

Teodor Bulboaca | Pure Mathematics | Excellence in Research

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Prof. Dr. Teodor Bulboaca | Pure Mathematics | Excellence in Research

Professor at Babes-Bolyai University, Romania

Prof. Teodor Bulboacă is a distinguished mathematician specializing in Complex Analysis and Geometric Function Theory. A full professor at Babeş-Bolyai University, he holds a Doctor of Science (2015) and a Ph.D. in Mathematics (1991), supervised by Prof. Dr. Petru T. Mocanu. With extensive research contributions in differential subordinations and univalent functions, he has significantly advanced the field. A dedicated educator, he has decades of teaching experience, mentoring undergraduate, master’s, and Ph.D. students. He actively participates in international awards, serving as an organizer and scientific committee member. His expertise is recognized through memberships in AMS, the Romanian Society of Mathematical Sciences, and the Hungarian Academy of Sciences. He has also contributed as an expert evaluator for Romania’s National University Research Council. His ongoing work continues to influence mathematical analysis, though expansion into interdisciplinary applications and high-impact collaborations could further enhance his global research impact.

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Education

Prof. Teodor Bulboacă has an extensive academic background in mathematics, earning his Ph.D. in Mathematical Analysis (1991) from Babeş-Bolyai University, under the supervision of Prof. Dr. Petru T. Mocanu, a member of the Romanian Academy. His doctoral research focused on differential subordinations and applications in the theory of univalent functions. In 2015, he obtained a Doctor of Science degree, further solidifying his contributions to the field. His formal education began with undergraduate studies at the Faculty of Mathematics and Computer Science, Babeş-Bolyai University (1974-1979). Prior to that, he completed his high school education at I. Slavici High School, Arad (1970-1974). With a strong foundation in complex analysis, topology, and geometric function theory, Prof. Bulboacă has built a distinguished academic and research career. His deep expertise in applied mathematical analysis has played a pivotal role in advancing theoretical developments and mathematical problem-solving methodologies.

Professional Experience

Prof. Teodor Bulboacă has had an illustrious academic career spanning over four decades. Since 2000, he has served as a full professor at the Faculty of Mathematics and Computer Science, Babeş-Bolyai University, Cluj-Napoca, Romania. Previously, he was an associate professor (1995-2000) at the same institution and also held a similar position at Aurel Vlaicu University, Arad (1994-1995). His academic journey began as an assistant professor (1990-1994) at Aurel Vlaicu University. Throughout his career, he has taught diverse courses, including Complex Analysis, Geometric Function Theory, Real Functions, and Applications of Complex Numbers in Geometry. Additionally, he has supervised bachelor’s, master’s, and Ph.D. theses, guiding students in mathematical research. As an active contributor to the academic community, he has been a scientific committee member for numerous international awards and an expert evaluator for the Romanian National University Research Council from 2006 to 2009.

Research Interest

Prof. Teodor Bulboacă specializes in Complex Analysis and Geometric Function Theory, with a primary focus on differential subordinations and univalent functions. His research explores fundamental mathematical properties within 30C15 (Geometric function theory) and 30C80 (Special classes of univalent and multivalent functions) in the Mathematics Subject Classification (MSC). He has made substantial contributions to geometric function theory, analytic functions, and mathematical inequalities, influencing theoretical developments and their applications. His research has interdisciplinary implications, with potential extensions into mathematical physics, data science, and computational modeling. He has collaborated with esteemed mathematicians and actively participates in international mathematical awards, where he presents groundbreaking findings. By integrating modern computational techniques with classical analysis, his work continues to shape advancements in mathematical theory and applied problem-solving methodologies. Future directions in his research could include machine learning-based mathematical modeling and complex network theory applications.

Awards and Honors

Prof. Teodor Bulboacă is recognized for his outstanding contributions to mathematics through numerous academic memberships and honors. He has been a member of the American Mathematical Society (AMS) since 2000, the Romanian Society of Mathematical Sciences since 1979, and the Public-Law Association of the Hungarian Academy of Sciences since 2000. His expertise has been acknowledged through his evaluation roles in the Romanian National University Research Council (2006-2009), where he assessed and guided national-level research projects. He has also played a key role in the scientific and organizing committees of major international mathematical awards, further highlighting his global academic influence. While his research impact is widely recognized in mathematical circles, an increased presence in prestigious international awards, fellowships, and interdisciplinary collaborations could further solidify his legacy. His longstanding commitment to education and research makes him a highly respected figure in complex analysis and applied mathematics.

Conclusion

Prof. Teodor Bulboacă is an accomplished mathematician whose research in complex analysis, geometric function theory, and differential subordinations has significantly contributed to the field. With a distinguished academic career spanning over four decades, he has played a pivotal role in teaching, mentoring, and advancing mathematical knowledge. His involvement in national and international research initiatives, professional organizations, and award committees underscores his commitment to the global mathematical community. While his contributions are widely recognized, expanding his research into interdisciplinary areas such as mathematical modeling, data science, and applied machine learning could enhance his impact even further. His dedication to mentoring young researchers ensures that his legacy will continue through the next generation of mathematicians. As he remains an active contributor to mathematical research and education, his work will continue to influence advancements in analytical and geometric function theories for years to come.

Publications Top Noted

 

Ran Zhang | Applied Mathematics | Best Researcher Award

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Dr. Ran Zhang | Applied Mathematics | Best Researcher Award

Researcher at Nanjing University of Posts and Telecommunications, China

Ran Zhang is a dedicated researcher specializing in differential operator spectrum theory and inverse problems, with a strong academic record and impactful contributions to mathematical analysis. He has published extensively in prestigious journals such as Journal of Differential Equations, Applied Mathematics Letters, and Mathematical Methods in Applied Sciences, addressing critical problems in Sturm-Liouville operators, Dirac systems, and inverse spectral analysis. As the host of national research projects, including those funded by the National Natural Science Foundation of China and Jiangsu Provincial Natural Science Foundation of China, he has demonstrated leadership in advancing theoretical mathematics. His work has significant implications for mathematical physics and engineering applications. While already an accomplished researcher, expanding into applied interdisciplinary domains and increasing global collaborations could further enhance his influence. With a strong foundation in theoretical and computational approaches, Ran Zhang continues to push the boundaries of mathematical research, making him a valuable contributor to the field.

Professional Profile

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Education

Ran Zhang has established a strong academic foundation in mathematics, particularly in differential operator spectrum theory and inverse problems. His educational journey has been marked by rigorous training in advanced mathematical techniques, equipping him with the analytical and computational skills necessary for solving complex problems in spectral analysis. Throughout his academic career, he has specialized in inverse problems, Sturm-Liouville operators, and Dirac systems, which are fundamental to mathematical physics and engineering applications. His deep understanding of functional analysis and operator theory has enabled him to contribute innovative solutions to long-standing mathematical challenges. His education has been further enriched through collaborations with esteemed mathematicians and participation in high-level mathematical research projects. This solid academic background has laid the groundwork for his contributions to the field, positioning him as a leading researcher in spectral theory and inverse problems.

Professional Experience

Ran Zhang has built an impressive professional career focused on mathematical research and inverse spectral analysis. As a host of research projects funded by the National Natural Science Foundation of China and the Jiangsu Provincial Natural Science Foundation of China, he has played a pivotal role in advancing theoretical mathematics. His work has been recognized in esteemed mathematical journals, reflecting the high impact of his research in spectral theory, Sturm-Liouville operators, and discontinuous differential equations. He has actively contributed to solving complex mathematical challenges and has worked closely with research teams, collaborating with renowned mathematicians across institutions. His experience extends beyond academia, as his research has potential applications in engineering, quantum mechanics, and applied physics. His ability to bridge theoretical mathematics with practical applications makes him a distinguished figure in the field. As he progresses in his career, expanding into interdisciplinary research and mentoring young mathematicians could further solidify his professional legacy.

Research Interest

Ran Zhang’s primary research interest lies in differential operator spectrum theory and its inverse problems, focusing on Sturm-Liouville operators, Dirac systems, and inverse spectral analysis. His work explores the uniqueness, reconstruction, and solvability of inverse problems, often dealing with differential operators that exhibit discontinuities. He is particularly interested in solving inverse nodal and resonance problems, which have profound implications in mathematical physics, quantum mechanics, and engineering applications. His research also extends to periodic and impulsive differential equations, addressing their spectral properties and reconstruction techniques. By developing new mathematical models and analytical methods, he aims to enhance the theoretical understanding of inverse problems while providing practical solutions for computational mathematics. His contributions to spectral theory play a vital role in advancing numerical methods and mathematical modeling, further strengthening the connection between pure and applied mathematics. His future research aims to expand into multidisciplinary applications, fostering collaborations across physics, engineering, and computational sciences.

Awards and Honors

Ran Zhang’s research excellence has been recognized through several prestigious honors and awards. As the recipient of funding from the National Natural Science Foundation of China and the Jiangsu Provincial Natural Science Foundation of China, he has demonstrated his ability to lead impactful research projects. His published works in top-tier mathematical journals, such as the Journal of Differential Equations, Applied Mathematics Letters, and Mathematical Methods in Applied Sciences, underscore his significant contributions to spectral theory and inverse problems. His research achievements have also been acknowledged through collaborations with internationally renowned mathematicians, highlighting his growing influence in the mathematical community. His ability to solve complex problems in spectral analysis has positioned him as a leading researcher in the field. With an increasing number of citations and recognition from the global mathematics community, Ran Zhang continues to make substantial contributions that are shaping modern mathematical research.

Conclusion

Ran Zhang is a distinguished researcher whose work in differential operator spectrum theory and inverse problems has made a profound impact on mathematical sciences. His strong academic background, extensive research experience, and leadership in national research projects position him as a key figure in mathematical analysis. His research has provided significant advancements in spectral theory, Sturm-Liouville operators, and inverse nodal problems, which are crucial for engineering, quantum mechanics, and mathematical physics. While he has already gained significant recognition, expanding his work into interdisciplinary applications and international collaborations could further elevate his influence. His commitment to mathematical innovation, coupled with his problem-solving skills and dedication to research, ensures that he will continue to contribute valuable insights to the field. As he moves forward, his work will likely shape the future of spectral analysis, making lasting contributions to both theoretical and applied mathematics.

Publications Top Noted

  • Title: Inverse spectral problems for the Dirac operator with complex-valued weight and discontinuity
    Authors: Ran Zhang, Chuan-Fu Yang, Natalia P. Bondarenko
    Year: 2021
    Citation: Journal of Differential Equations, 278: 100-110
    Source: Journal of Differential Equations

  • Title: Uniqueness and reconstruction of the periodic Strum-Liouville operator with a finite number of discontinuities
    Authors: Ran Zhang, Kai Wang, Chuan-Fu Yang
    Year: 2024
    Citation: Applied Mathematics Letters, 147: 108853
    Source: Applied Mathematics Letters

  • Title: Uniqueness theorems for the impulsive Dirac operator with discontinuity
    Authors: Ran Zhang, Chuan-Fu Yang
    Year: 2022
    Citation: Analysis and Mathematical Physics, 12(1): 1-16
    Source: Analysis and Mathematical Physics

  • Title: Determination of the impulsive Sturm-Liouville operator from a set of eigenvalues
    Authors: Ran Zhang, Xiao-Chuan Xu, Chuan-Fu Yang, Natalia P. Bondarenko
    Year: 2020
    Citation: Journal of Inverse and Ill-posed Problems, 28(3): 341-348
    Source: Journal of Inverse and Ill-posed Problems

  • Title: Solving the inverse problems for discontinuous periodic Strum-Liouville operator by the method of rotation
    Authors: Ran Zhang, Kai Wang, Chuan-Fu Yang
    Year: 2024
    Citation: Results in Mathematics, 79(1): 49
    Source: Results in Mathematics

  • Title: Ambarzumyan-type theorem for the impulsive Sturm-Liouville operator
    Authors: Ran Zhang, Chuan-Fu Yang
    Year: 2021
    Citation: Journal of Inverse and Ill-posed Problems, 29(1): 21-25
    Source: Journal of Inverse and Ill-posed Problems

  • Title: Solvability of an inverse problem for discontinuous Sturm-Liouville operators
    Authors: Ran Zhang, Natalia P. Bondarenko, Chuan-Fu Yang
    Year: 2021
    Citation: Mathematical Methods in Applied Sciences, 44(1): 124-139
    Source: Mathematical Methods in Applied Sciences

  • Title: Reconstruction of the Strum-Liouville operator with periodic boundary conditions and discontinuity
    Authors: Ran Zhang, Chuan-Fu Yang
    Year: 2022
    Citation: Mathematical Methods in Applied Sciences, 45(8): 4244-4251
    Source: Mathematical Methods in Applied Sciences

  • Title: Determination of the impulsive Dirac systems from a set of eigenvalues
    Authors: Ran Zhang, Chuan-Fu Yang, Kai Wang
    Year: 2023
    Citation: Mathematics, 11(19): 4086
    Source: Mathematics

  • Title: Inverse nodal problem for the Sturm-Liouville operator with a weight
    Authors: Ran Zhang, Murat Sat, Chuan-Fu Yang
    Year: 2020
    Citation: Applied Mathematics – A Journal of Chinese Universities Series B, 35(2): 193-202
    Source: Applied Mathematics – A Journal of Chinese Universities Series B

 

Maryam Alkandari | Pure Mathematics | Best Researcher Award

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Dr. Maryam Alkandari | Pure Mathematics | Best Researcher Award

 Associate Prof at Kuwait University, Kuwait

Dr. Maryam Mohammad Alkandari is an esteemed Associate Professor in the Department of Mathematics at Kuwait University, specializing in algebraic geometric coding theory, fractional calculus, and applied mathematics. She earned her Ph.D. from Imperial College London in 2003 and has since made significant contributions to mathematical research. With over 18 high-impact publications in renowned journals and a Springer Nature book, her work spans differential equations, operational calculus, and mathematical modeling. She has led seven major research projects, receiving multiple grants and awards. Dr. Alkandari is also dedicated to education, contributing to mathematics pedagogy and autism research. She has presented at international awards and collaborated on interdisciplinary projects. Her research continues to influence pure and applied mathematics, with potential for industrial applications. With a strong academic foundation and impactful contributions, she stands as a leading researcher in her field, making her an excellent candidate for prestigious research awards.

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Education

Dr. Maryam Mohammad Alkandari holds a Ph.D. in Algebraic Geometric Coding Theory from Imperial College London, UK, awarded in 2003. Alongside her doctorate, she earned a Diploma in Algebra from Imperial College the same year. She previously completed her M.S. in Pure Mathematics in 1997 and a B.S. in Mathematics in 1994, both from Kuwait University. Her doctoral research, titled “Decoding Partial Geometric Codes,” focused on advanced algebraic structures and coding theory, demonstrating her expertise in mathematical problem-solving. Over the years, she has expanded her research into applied mathematics, fractional calculus, and mathematical modeling. With a strong foundation in pure and applied mathematics, Dr. Alkandari has significantly contributed to her field through research, teaching, and mentorship. Her academic journey reflects a commitment to innovation, interdisciplinary studies, and advancing mathematical knowledge in both theoretical and practical applications.

Professional Experience

Dr. Maryam Mohammad Alkandari is an accomplished mathematician and Associate Professor at Kuwait University with over two decades of academic and research experience. She specializes in applied mathematics, algebraic geometric coding theory, and fractional calculus. Since earning her Ph.D. from Imperial College London in 2003, she has held key academic positions, contributing significantly to mathematical research and education. As a principal investigator, she has led multiple funded projects, including studies on fractional calculus, operational methods, and mathematical modeling. Dr. Alkandari has published extensively in high-impact journals and authored a book with Springer Nature Switzerland. She actively participates in international awards and collaborates on interdisciplinary research, including mathematics education and autism studies. Her mentorship, leadership in research, and commitment to advancing mathematical sciences have earned her prestigious grants and recognition. Dr. Alkandari continues to push the boundaries of mathematical applications, making significant contributions to both academia and industry.

Research Interest

Dr. Maryam Mohammad Alkandari’s research interests lie in applied mathematics, fractional calculus, algebraic geometric coding theory, and differential equations, with a strong focus on both theoretical advancements and practical applications. Her work extensively explores operational calculus, algebraic structures, and numerical methods for solving complex mathematical problems. She has made significant contributions to fractional differential equations, oscillation theory, and integral transforms, with applications in engineering, physics, and mathematical modeling. Dr. Alkandari is also interested in mathematics education and pedagogical approaches, particularly the integration of technology in learning and teaching methodologies. Her interdisciplinary research extends to mathematical models in autism education, demonstrating the societal impact of her work. Additionally, she is involved in research projects that explore novel mathematical techniques in oil production and refining. Through her prolific publications, funded research projects, and international collaborations, Dr. Alkandari continues to push the boundaries of applied mathematics and its real-world applications.

Award and Honor

Dr. Maryam Mohammad Alkandari has received numerous awards and honors in recognition of her outstanding contributions to applied mathematics, fractional calculus, and algebraic geometric coding theory. She has been the Principal Investigator (PI) on seven major research projects funded by Kuwait University, including groundbreaking studies on operational methods in fractional calculus and mathematical modeling in oil production. Her excellence in research has been acknowledged through multiple grant awards, including the prestigious Project Award for Operational Method in Fractional Calculus (SM01/17, SM01/20). Additionally, she has been honored with unfunded rewarded papers from Kuwait University’s Research Sector, highlighting her influential publications in top-tier journals. Dr. Alkandari has presented her work at international awards in Turkey, Taiwan, and Kuwait, further solidifying her global academic reputation. With her extensive contributions to research, education, and mentorship, she continues to be a leading figure in applied mathematics, earning well-deserved recognition and respect in the field.

Conclusion

Dr. Maryam Mohammad Alkandari is an accomplished researcher and academic in applied mathematics, specializing in algebraic geometric coding theory, fractional calculus, and differential equations. With a Ph.D. from Imperial College London and over two decades of experience at Kuwait University, she has made significant contributions through numerous high-impact publications, funded research projects, and international award presentations. Her work spans theoretical advancements and practical applications, including innovative mathematical methods in education and autism research. Recognized with multiple research grants and awards, she has demonstrated leadership in interdisciplinary studies and academic mentorship. While her research impact is commendable, further international collaborations, industry applications, and editorial leadership could elevate her global influence. Dr. Alkandari’s dedication to advancing mathematical sciences and her contributions to education make her a strong candidate for prestigious research awards, positioning her as a leading figure in applied mathematics with the potential to make lasting global contributions.

Publications Top Noted

  • Operational Calculus for the General Fractional Derivatives of Arbitrary Order
    • Authors: M. Al-Kandari, L.A.M. Hanna, Y. Luchko
    • Year: 2022
    • Citations: 18
  • Operational Method for Solving Fractional Differential Equations with the Left-and Right-Hand Sided Erdélyi-Kober Fractional Derivatives
    • Authors: L.A.M. Hanna, M. Al-Kandari, Y. Luchko
    • Year: 2020
    • Citations: 16
  • A Fuzzy-Statistical Tolerance Interval from Residuals of Crisp Linear Regression Models
    • Authors: M. Al-Kandari, K. Adjenughwure, K. Papadopoulos
    • Year: 2020
    • Citations: 13
  • Half-Linear Differential Equations of Fourth Order: Oscillation Criteria of Solutions
    • Authors: O. Bazighifan, K.S. Al-Ghafri, M. Al-Kandari, F. Ghanim, F. Mofarreh
    • Year: 2022
    • Citations: 7
  • Delay Differential Equations of Fourth-Order: Oscillation and Asymptotic Properties of Solutions
    • Authors: O. Bazighifan, M. Al-Kandari, K.S. Al-Ghafri, F. Ghanim, S. Askar, G.I. Oros
    • Year: 2021
    • Citations: 7
  • Calculus 1 College Students’ Concept of Function
    • Authors: A.H. Alajmi, M.M. Al-Kandari
    • Year: 2022
    • Citations: 5
  • New Criteria for Oscillation of Half-Linear Differential Equations with p-Laplacian-like Operators
    • Authors: O. Bazighifan, F. Ghanim, J. Awrejcewicz, K.S. Al-Ghafri, M. Al-Kandari
    • Year: 2021
    • Citations: 4
  • Enhancing Kuwaiti Teachers’ Technology-Assisted Mathematics Teaching Practices
    • Authors: M. Soliman, Z. Lavicza, T. Prodromou, M. Al-Kandari, T. Houghton
    • Year: 2019
    • Citations: 4
  • Some Oscillation Results for Even-Order Differential Equations with Neutral Term
    • Authors: M. Al-Kandari, O. Bazighifan
    • Year: 2021
    • Citations: 3
  • On an Extension of the Mikusiński Type Operational Calculus for the Caputo Fractional Derivative
    • Authors: M. Al-Kandari, L.A.M. Hanna, Y. Luchko
    • Year: 2021
    • Citations: 3
  • A Convolution Family in the Dimovski Sense for the Composed Erdélyi-Kober Fractional Integrals
    • Authors: M. Al-Kandari, L.A.M. Hanna, Y.F. Luchko
    • Year: 2019
    • Citations: 3
  • Operational Calculus for the 1st Level General Fractional Derivatives and its Applications
    • Authors: M. Al-Kandari, Y. Luchko
    • Year: 2024
    • Citations: 2
  • A New Modification of an Iterative Method Based on Inverse Polynomial for Solving Cauchy Problems
    • Authors: A.H. Ali, O. Alabdali, M.T. Yaseen, M. Al-Kandari, O. Bazighifan
    • Year: 2023
    • Citations: 1

 

 

Aviv Gibali | Applied Mathematics | Best Researcher Award

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Prof. Aviv Gibali | Applied Mathematics | Best Researcher Award

Researcher at Holon Institute of Technology, Israel

Dr. Aviv Gibali is a distinguished mathematician and researcher specializing in applied mathematics, optimization, and variational inequalities. He holds a Ph.D. from the Technion – Israel Institute of Technology and has completed postdoctoral studies at the Fraunhofer Institute for Industrial Mathematics in Germany. Currently serving as the Head of the Department of Applied Mathematics at HIT – Holon Institute of Technology, he has previously held leadership roles at ORT Braude College of Engineering. Dr. Gibali has made significant contributions through numerous scholarly publications, award presentations, and editorial positions in prestigious journals. His expertise spans optimization algorithms, superiorization techniques, and mathematical modeling with applications in science and engineering. Actively engaged in international collaborations and academic committees, he has also received multiple awards for his impactful research. His dedication to advancing mathematical methodologies and their real-world applications establishes him as a leading figure in the field.

Professional Profile 

Scopus Profile
ORCID Profile

Education

Dr. Aviv Gibali holds a strong academic background in mathematics, with degrees from prestigious institutions. He earned his Ph.D. in Mathematics from the Technion – Israel Institute of Technology in 2012, where his doctoral research focused on algorithms for solving variational inequalities and their applications under the supervision of Prof. Simeon Reich and Prof. Yair Censor. Prior to that, he completed his M.Sc. in Mathematics at the University of Haifa in 2008, working on iterative algorithms for solving variational inequality problems under the guidance of Prof. Yair Censor. His academic journey began with a B.Sc. in Mathematics from the University of Haifa in 2005. Following his Ph.D., Dr. Gibali pursued postdoctoral research in optimization at the Fraunhofer Institute for Industrial Mathematics (ITWM) in Kaiserslautern, Germany, from 2012 to 2014. His educational foundation has equipped him with deep expertise in mathematical modeling, optimization, and computational algorithms.

Professional Experience

Dr. Aviv Gibali is an accomplished mathematician and researcher specializing in optimization, variational inequalities, and applied mathematics. He currently serves as the Head of the Department of Applied Mathematics at HIT – Holon Institute of Technology and holds the rank of Associate Professor. Previously, he was an Associate Professor and Head of the Mathematics Department at ORT Braude College of Engineering. Dr. Gibali completed his Ph.D. at The Technion – Israel Institute of Technology and pursued postdoctoral research at the Fraunhofer Institute for Industrial Mathematics in Germany. His extensive academic contributions include serving as an associate editor for multiple prestigious journals, organizing international awards, and collaborating with leading institutions worldwide. With numerous invited talks, scientific visits, and interdisciplinary research projects, he has significantly advanced the field of mathematical optimization. His expertise spans theoretical advancements and industrial applications, earning him multiple awards and recognition in applied and computational mathematics.

Research Interest

Dr. Aviv Gibali’s research interests lie at the intersection of applied mathematics, optimization, and computational methods, with a strong focus on projection algorithms, variational inequalities, and convex feasibility problems. His work spans both theoretical advancements and real-world applications, particularly in industrial mathematics, medical imaging, radiation therapy planning, and data science. He has made significant contributions to superiorization techniques, an innovative approach to improving iterative algorithms for constrained optimization problems. Dr. Gibali is also actively engaged in developing and analyzing numerical algorithms for large-scale optimization, leveraging mathematical modeling to solve complex problems in engineering, machine learning, and healthcare. His interdisciplinary collaborations with international research institutions and industry partners enhance the practical impact of his studies. With a keen interest in mathematical education, he also contributes to innovative pedagogical methods, fostering a new generation of researchers in applied and computational mathematics.

Award and Honor

Dr. Aviv Gibali, a distinguished mathematician and researcher, has been widely recognized for his outstanding contributions to applied mathematics and optimization. He has received numerous accolades, including the prestigious Fourth Most Cited Article Award from Optimization Methods and Software in 2021, highlighting the impact of his research. In 2020, he secured First Prize in the Hackathon on Free Writing Home Exams, organized by Tel-Aviv University and Shenkar, demonstrating his innovative approach to education. His scholarly excellence has also been acknowledged through esteemed fellowships such as the Mathematics for Industry Network’s Short-Term Scientific Mission (2018) in Germany and the Austria-Israel Academic Network Innsbruck (AIANI) Fellowship (2017). With an extensive academic career, editorial roles in leading journals, and significant contributions to industrial mathematics, Dr. Gibali’s work continues to shape the field, earning him widespread recognition and respect within the global mathematical community.

Conclusion

Dr. Aviv Gibali is a distinguished researcher in applied mathematics, with a prolific academic career spanning optimization, variational inequalities, and superiorization techniques. His extensive contributions include over a decade of impactful research, international collaborations, editorial roles in leading mathematical journals, and leadership positions in academia. As an associate professor and head of the Department of Applied Mathematics at HIT – Holon Institute of Technology, Dr. Gibali has played a pivotal role in advancing mathematical research and fostering industry-academic partnerships. His numerous scientific visits, award organizations, and editorial engagements reflect his dedication to global knowledge dissemination. Recognized with prestigious awards and citations, he has demonstrated excellence in both theoretical advancements and real-world applications. While his achievements are remarkable, continued exploration of interdisciplinary applications and mentorship initiatives could further enhance his academic influence. Dr. Gibali’s scholarly impact and leadership make him a highly deserving candidate for the Best Researcher Award.

Publications Top Noted

  • Multidimensional Evolution Effects on Non-Cooperative Strategic Games
    Authors: Shipra Singh, Aviv Gibali, Simeon Reich
    Year: 2024
    Source: Mathematics
  • Resolvent-Free Method for Solving Monotone Inclusions
    Authors: Yan Tang, Aviv Gibali
    Year: 2023
    Source: Axioms
  • Special Issue “Symmetry in Optimization and Control with Real-World Applications”
    Authors: Kok Lay Teo, Aviv Gibali, Yong Wu
    Year: 2022
    Source: Symmetry
  • New Self-Adaptive Inertial-Like Proximal Point Methods for the Split Common Null Point Problem
    Authors: Yan Tang, Yeyu Zhang, Aviv Gibali
    Year: 2021
    Source: Symmetry
  • Multi-Time Generalized Nash Equilibria with Dynamic Flow Applications
    Authors: Shipra Singh, Aviv Gibali, Simeon Reich
    Year: 2021
    Source: Mathematics
  • An Analytic and Numerical Investigation of a Differential Game
    Authors: Aviv Gibali, Oleg Kelis
    Year: 2021
    Source: Axioms
  • Projected-Reflected Subgradient-Extragradient Method and Its Real-World Applications
    Authors: Aviv Gibali, O.S. Iyiola, Lanre Akinyemi, Yekini
    Year: 2021
    Source: Symmetry
  • A Symmetric FBF Method for Solving Monotone Inclusions
    Authors: Aviv Gibali, Yekini
    Year: 2020
    Source: Symmetry
  • Inertial Krasnoselskii–Mann Method in Banach Spaces
    Authors: Yekini Shehu, Aviv Gibali
    Year: 2020
    Source: Mathematics

 

Danko Jocic | Pure Mathematics | Outstanding Pure Mathematics Contribution

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Prof. Dr. Danko Jocic | Pure Mathematics | Outstanding Pure Mathematics Contribution

Professor at University of Belgrade, Faculty of mathematics, Serbia

Prof. Dr. Danko Jocić is a distinguished mathematician specializing in functional analysis and operator theory, with a prolific research career spanning several decades. His contributions focus on norm inequalities, operator inequalities, perturbation theory, and elementary operators in norm ideals. He has authored numerous high-impact journal articles in prestigious international publications such as the Journal of Functional Analysis, Proceedings of the American Mathematical Society, and Linear Algebra and Its Applications. His research has significantly advanced understanding in areas like Schatten ideals, noncommutative analysis, and operator monotone functions. Additionally, he has co-authored influential books and book chapters, furthering mathematical knowledge dissemination. Prof. Jocić has mentored doctoral students and actively contributed to the academic community through award presentations and editorial work. His extensive body of work and leadership in mathematical research make him a strong candidate for the Best Researcher Award, recognizing his profound influence in pure and applied mathematics.

Professional Profile 

Google Scholar
Scopus Profile

Education

Prof. Dr. Danko Jocić is a distinguished mathematician specializing in functional analysis and operator theory. He obtained his undergraduate, master’s, and doctoral degrees from esteemed institutions, demonstrating academic excellence throughout his education. His doctoral research focused on advanced topics in operator theory, laying the foundation for his prolific contributions to mathematical inequalities and functional analysis. Under the mentorship of leading experts, he developed a deep understanding of norm inequalities, derivations, and spectral theory, which later became central to his research. His education equipped him with the analytical skills necessary to explore perturbation inequalities, operator ideals, and noncommutative analysis. Throughout his academic journey, he engaged in rigorous training, attending specialized courses and participating in mathematical awards, further refining his expertise. His solid educational background has been instrumental in shaping his career as a leading researcher, educator, and mentor in the field of mathematical sciences.

Professional Experience

Prof. Dr. Danko Jocić is a distinguished mathematician specializing in functional analysis, operator theory, and norm inequalities. With a prolific academic career, he has authored numerous research papers in high-impact international journals, including the Journal of Functional Analysis, Linear Algebra and Its Applications, and Complex Analysis and Operator Theory. His contributions focus on operator inequalities, perturbation theory, and Schatten ideals, significantly advancing the field of mathematical analysis. He has co-authored influential monographs and book chapters, further enriching the mathematical community. Prof. Jocić has presented his research at prestigious international awards and has mentored multiple doctoral students, shaping future generations of mathematicians. His expertise and dedication to advancing operator theory have earned him recognition as a leading researcher in mathematical sciences. Through his extensive publication record and academic leadership, he continues to contribute profoundly to the study of mathematical operators and functional analysis.

Research Interest

Prof. Dr. Danko Jocić’s research interests lie in functional analysis, operator theory, and norm inequalities, with a particular focus on elementary operators, norm ideals of compact operators, and perturbation theory. His work extensively explores inequalities related to self-adjoint operators, Schatten-von Neumann classes, and various integral transformations in operator algebras. He has contributed significantly to the study of Cauchy-Schwarz, Minkowski, Landau, and Grüss-type inequalities, refining classical operator inequalities and extending them to new mathematical structures. Additionally, his research encompasses norm estimates for derivations, noncommutative analysis, and inequalities for hypercontractive quasinormal operators. Prof. Jocić has collaborated on developing new mathematical tools for studying accretive and quasinormal operators, leading to applications in functional spaces and spectral theory. His contributions, published in prestigious international journals, demonstrate a deep commitment to advancing mathematical understanding in the field of operator theory and its broader implications in functional analysis.

Award and Honor

Prof. Dr. Danko Jocić is a distinguished mathematician renowned for his contributions to functional analysis, operator theory, and norm inequalities. With an extensive body of research published in prestigious international journals, he has significantly advanced the understanding of elementary operators, Schatten ideals, and norm inequalities in compact operator theory. His scholarly impact is further evidenced by his authorship of influential books and monographs, as well as his mentorship of doctoral students, shaping the next generation of mathematicians. Throughout his career, Prof. Jocić has received recognition for his exceptional research, including invitations to present at esteemed mathematical awards and symposiums worldwide. His work has been cited extensively, demonstrating its lasting influence on the field. As a respected academic, he has also played a vital role in the mathematical community, contributing to the development of contemporary operator theory. His unwavering dedication and scholarly excellence make him a deserving candidate for prestigious research awards.

Conclusion

Prof. Dr. Danko Jocić is a distinguished researcher in the field of functional analysis and operator theory, with a prolific academic career marked by high-impact publications in prestigious international journals. His contributions span a wide range of topics, including norm inequalities, elementary operators, and generalized derivations, showcasing both depth and innovation in mathematical research. His work has been widely cited, demonstrating its relevance and influence within the mathematical community. Additionally, his role as a mentor for doctoral students highlights his commitment to academic development and knowledge dissemination. Despite his impressive contributions, continued engagement in cutting-edge research and interdisciplinary collaborations could further enhance his global recognition. Overall, his extensive body of work, leadership in mathematical research, and dedication to education make him a strong candidate for the Best Researcher Award, solidifying his status as a key figure in contemporary mathematical analysis.

Publications Top Noted

  • Norm Estimates for Remainders of Noncommutative Taylor Approximations for Laplace Transformers Defined by Hyperaccretive Operators
    Author: Jocić, D.R.
    Year: 2024
    Citations: 0
  • Norm Inequalities for the Iterated Perturbations of Laplace Transformers Generated by Accretive N-Tuples of Operators in Q and Q Ideals of Compact Operators*
    Authors: Jocić, D.R., Golubović, Z.L., Krstić, M., Milašinović, S.
    Year: 2024
    Citations: 1
  • Norm Inequalities for Hyperaccretive Quasinormal Operators, with Extensions of the Arithmetic-Geometric Means Inequality
    Authors: Jocić, D.R., Lazarević, M.
    Year: 2024
    Citations: 2
  • Noncommutative Pick–Julia Theorems for Generalized Derivations in Q, Q and Schatten–von Neumann Ideals of Compact Operators*
    Author: Jocić, D.R.
    Year: 2023
    Citations: 2
  • Norm Inequalities for Hypercontractive Quasinormal Operators and Related Higher Order Sylvester–Stein Equations in Ideals of Compact Operators
    Authors: Jocić, D.R., Lazarević, M.
    Year: 2023
    Citations: 1
  • Noncommutative Schwarz Lemma and Pick–Julia Theorems for Generalized Derivations in Norm Ideals of Compact Operators
    Author: Jocić, D.R.
    Year: 2022
    Citations: 3
  • Perturbation Norm Inequalities for Elementary Operators Generated by Analytic Functions with Positive Taylor Coefficients
    Authors: Jocić, D.R., Lazarević, M., Milović, M.
    Year: 2022
    Citations: 1
  • Cauchy–Schwarz Norm Inequalities for Elementary Operators and Inner Product Type Transformers Generated by Families of Subnormal Operators
    Authors: Jocić, D.R., Lazarević, M.
    Year: 2022
    Citations: 3
  • Cauchy–Schwarz Operator and Norm Inequalities for Inner Product Type Transformers in Norm Ideals of Compact Operators, with Applications
    Authors: Jocić, D.R., Lazarević, M.
    Year: 2022
    Citations: 0
  • Extensions of the Arithmetic–Geometric Means and Young’s Norm Inequalities to Accretive Operators, with Applications
    Authors: Jocić, D.R., Krtinić, Đ., Lazarević, M.
    Year: 2022
    Citations: 6