Alexander Zlotnik | Mathematics | Best Researcher Award

Prof. Dr. Alexander Zlotnik | Mathematics | Best Researcher Award

Professor from Higher School of Economics, Russia

Alexander A. Zlotnik is a leading Russian mathematician and a Professor-Researcher at the Department of Mathematics, Faculty of Economic Sciences, Higher School of Economics (HSE) University in Moscow. With a deep focus on computational mathematics, he has made extensive contributions to the numerical analysis of partial differential equations (PDEs). Zlotnik’s research spans a variety of mathematical models, including quasi-gasdynamic systems, wave equations, and hyperbolic-parabolic equations. His theoretical contributions have led to the development of robust and stable numerical schemes with proven convergence properties and applications in fluid dynamics, heat conduction, and wave propagation. He has authored over 225 scientific publications in top-tier international journals and has collaborated with researchers from Europe, Asia, and the Middle East. Zlotnik is also known for mentoring graduate students and serving on editorial boards of influential journals. His academic journey reflects both depth and breadth in applied mathematics, making him a respected voice in the global mathematical community. He is also recognized for his interdisciplinary applications of numerical methods to real-world problems, which positions him as a bridge between theory and practice in modern computational science. His continued academic excellence and leadership exemplify his eligibility for global recognition.

Professional Profile

Education

Professor Alexander A. Zlotnik earned his foundational education in mathematics at Lomonosov Moscow State University, one of Russia’s most prestigious institutions. He completed his Ph.D. in Computational Mathematics in 1980, focusing on the numerical methods for solving complex partial differential equations. His early academic achievements were marked by a rigorous training in applied mathematics, providing a strong foundation for his future research. In 1993, he was awarded the Doctor of Science (D.Sc.) degree, which is the highest academic qualification in Russia, signifying a significant contribution to a scientific field. This advanced degree focused on the mathematical theory and numerical implementation of gas dynamics and wave models, areas that would become central to his career. His academic training at Moscow State University provided not only technical expertise but also exposure to the prominent mathematical thinkers of the time. Over the years, Zlotnik’s academic qualifications have been further enriched by research fellowships and academic visits across Europe and Asia, including collaborations in France, Germany, Korea, and China. These global academic experiences have expanded his intellectual horizons and informed the interdisciplinary nature of his subsequent work in computational mathematics and numerical analysis.

Professional Experience

Alexander A. Zlotnik has built a prolific academic and research career across several esteemed Russian and international institutions. He began his professional journey as a researcher and faculty member at the Moscow Power Engineering Institute, where he worked on numerical simulations and stability of physical systems modeled by partial differential equations. Later, he held positions at the Keldysh Institute of Applied Mathematics of the Russian Academy of Sciences, contributing significantly to theoretical and applied computational mathematics. Since 2002, he has served as a Professor-Researcher at the Higher School of Economics (HSE) University, one of Russia’s leading academic institutions. At HSE, he has been instrumental in advancing research in mathematical modeling and numerical analysis, teaching advanced mathematics, and supervising doctoral students. Beyond Russia, Zlotnik has held visiting positions and collaborated with universities in France, Germany, Sweden, Korea, and China, further enriching his professional expertise. His experience includes project leadership for major research grants funded by the Russian Science Foundation and Russian Foundation for Basic Research. Throughout his career, he has consistently bridged theoretical work with practical computational solutions, making him a respected figure in applied mathematics and computational sciences.

Research Interest

Professor Zlotnik’s research interests lie at the intersection of applied mathematics, numerical analysis, and mathematical modeling of physical systems. His primary focus is on numerical methods for partial differential equations (PDEs), particularly hyperbolic, parabolic, and quasi-gasdynamic systems. He is recognized for developing compact, stable, and conservative numerical schemes that preserve the structural properties of PDEs and ensure accurate simulation of physical phenomena such as fluid flow, heat transfer, and wave propagation. He has extensively worked on the theory of dissipativity, convergence, and stability of difference methods, providing rigorous mathematical justifications for computational algorithms. Zlotnik is also interested in the mathematical modeling of multiphase flows, acoustics, and electromagnetism, aiming to provide reliable simulations for industrial and scientific applications. His research integrates both theoretical foundations and practical computations, ensuring that models are both mathematically sound and computationally efficient. His ongoing projects include the development of new algorithms for solving initial-boundary value problems and studying the asymptotic behavior of solutions. Through his research, Zlotnik contributes to advancing computational tools that support scientific discovery and engineering innovation. His interdisciplinary approach connects mathematics with physics, computer science, and engineering, making his work widely applicable and globally relevant.

Research Skills

Professor Alexander Zlotnik possesses a robust set of research skills centered on numerical methods, differential equations, and computational modeling. His expertise includes designing and analyzing finite difference and finite element schemes for solving complex physical problems governed by PDEs. He is highly skilled in establishing mathematical proofs of convergence and stability, critical for validating computational methods used in simulations of gas dynamics, wave phenomena, and heat conduction. Zlotnik also has in-depth knowledge of numerical linear algebra, approximation theory, and functional analysis, which supports his ability to construct efficient algorithms for large-scale simulations. He is proficient in software development for mathematical modeling and has collaborated on the implementation of custom numerical solvers. His analytical rigor allows him to translate theoretical insights into practical computing solutions. He is also experienced in supervising experimental validations in partnership with physicists and engineers. Furthermore, Zlotnik demonstrates strong project management and research leadership skills, successfully directing multi-institutional research collaborations and securing competitive research grants. His versatility in blending deep theory with computational tools and cross-disciplinary methods makes him a valuable asset in advancing both academic research and real-world applications.

Awards and Honors

Over his distinguished career, Professor Alexander A. Zlotnik has received several honors that highlight his contributions to mathematics and science. While formal national awards may not be frequently publicized, his recognition comes through academic distinctions, international invitations, and editorial board appointments. He has been entrusted with principal investigator roles in numerous competitive grants from the Russian Science Foundation (RSF) and the Russian Foundation for Basic Research (RFBR)—a testament to his research excellence and national reputation. He has been regularly invited to speak at international conferences, including those in France, Germany, Sweden, China, Korea, and Algeria, and has led key collaborations with European research institutions. Zlotnik serves as an editorial board member of prestigious journals such as Applicable Analysis, Entropy, and Symmetry, and formerly Computational Methods in Applied Mathematics, which underscores his standing in the scholarly community. His extensive reviewing activities for over 30 scientific journals also demonstrate peer recognition and trust. Moreover, he has successfully supervised Ph.D. students who have gone on to become academics and researchers, amplifying his academic legacy. These honors reflect his commitment to advancing mathematical sciences and mentoring the next generation of scholars.

Conclusion

Professor Alexander A. Zlotnik stands as a paragon of academic rigor, innovation, and global collaboration in the field of numerical mathematics. His extensive contributions to the theory and application of numerical methods for PDEs have significantly advanced the understanding and computational modeling of physical systems. With over 225 publications, he continues to impact both theoretical and applied research communities. His academic background, rooted in the world-class tradition of Moscow State University, has evolved through decades of research, teaching, and international engagement. He exemplifies the rare combination of deep theoretical insight, practical computational skill, and the ability to lead large-scale research efforts. Zlotnik’s influence extends beyond publications to mentoring students, fostering collaborations, and shaping editorial standards in mathematical journals. His interdisciplinary work connects mathematics with engineering, physics, and computer science, addressing contemporary scientific and industrial challenges. As a result, he has rightfully earned respect as a thought leader in computational science. Professor Zlotnik’s profile makes him an outstanding nominee for any global research award, recognizing both his lifetime achievements and his ongoing contributions to mathematical sciences and computational innovation.

Publications Top Notes

  1. Uniform estimates and stabilization of symmetric solutions of a system of quasilinear equations
    Author: A.A. Zlotnik
    Journal: Differential Equations, Vol. 36(5), pp. 701–716
    Year: 2000
    Citations: 142
  2. Parabolicity of the quasi-gasdynamic system of equations, its hyperbolic second-order modification, and the stability of small perturbations for them
    Authors: A.A. Zlotnik, B.N. Chetverushkin
    Journal: Computational Mathematics and Mathematical Physics, Vol. 48(3), pp. 420–446
    Year: 2008
    Citations: 119
  3. Lyapunov functional method for 1D radiative and reactive viscous gas dynamics
    Authors: B. Ducomet, A. Zlotnik
    Journal: Archive for Rational Mechanics and Analysis, Vol. 177(2), pp. 185–229
    Year: 2005
    Citations: 78
  4. Global generalized solutions of the equations of the one-dimensional motion of a viscous heat-conducting gas
    Authors: A.A. Amosov, A.A. Zlotnik
    Journal: Soviet Math. Dokl, Vol. 38(1), p. 5
    Year: 1989
    Citations: 78
  5. Solvability “in the large” of a system of equations of the one-dimensional motion of an inhomogeneous viscous heat-conducting gas
    Authors: A.A. Amosov, A.A. Zlotnik
    Journal: Mathematical Notes, Vol. 52(2), pp. 753–763
    Year: 1992
    Citations: 73
  6. Convergence rate estimates of finite-element methods for second-order hyperbolic equations
    Author: A.A. Zlotnik
    Book: Numerical Methods and Applications, CRC Press, Boca Raton, pp. 155–220
    Year: 1994
    Citations: 72
  7. On stability of generalized solutions to the equations of one-dimensional motion of a viscous heat conducting gas
    Authors: A.A. Zlotnik, A.A. Amosov
    Journal: Siberian Mathematical Journal, Vol. 38(4), pp. 663–684
    Year: 1997
    Citations: 69
  8. Energy equalities and estimates for barotropic quasi-gasdynamic and quasi-hydrodynamic systems of equations
    Author: A.A. Zlotnik
    Journal: Computational Mathematics and Mathematical Physics, Vol. 50(2), pp. 310–321
    Year: 2010
    Citations: 68
  9. On the large-time behavior of 1D radiative and reactive viscous flows for higher-order kinetics
    Authors: B. Ducomet, A. Zlotnik
    Journal: Nonlinear Analysis: Theory, Methods & Applications, Vol. 63(8), pp. 1011–1033
    Year: 2005
    Citations: 62
  10. Parabolicity of a quasihydrodynamic system of equations and the stability of its small perturbations
    Author: A.A. Zlotnik
    Journal: Mathematical Notes, Vol. 83(5), pp. 610–623
    Year: 2008
    Citations: 61

 

Syed Anwar | signal processing | Best Researcher Award

Syed Anwar | signal processing | Best Researcher Award

Principal Investigator at Childrens National Hopsital, United States.

Syed Muhammad Anwar is a distinguished researcher in the fields of medical imaging, deep learning, and computer vision. He is currently a Principal Investigator at the Sheikh Zayed Institute for Pediatric Surgical Innovation at Children’s National Hospital in Washington, DC, and serves as an Associate Professor at George Washington University. With over two decades of academic and professional experience, Dr. Anwar has co-founded tech ventures and contributed significantly to cutting-edge research in machine learning and medical image analysis. His expertise spans across multiple countries and academic institutions, with an impressive h-index of 38 and over 6,800 citations. A prolific scholar and inventor, he has secured numerous grants and awards for his research contributions in both academia and industry, particularly in the development of healthcare technologies. His leadership roles in education, research, and industry highlight his commitment to innovation and interdisciplinary collaboration in emerging technology fields.

Profile👤

Scopus

ORCID

Education📝

Dr. Anwar’s educational background showcases an impressive academic journey through prestigious institutions. He earned his PhD in Electronic and Electrical Engineering from the University of Sheffield, UK, in 2012, where his research focused on detecting neuronal fields using MR imaging. Prior to that, he obtained a distinction in his MS in Data Communications, also from the University of Sheffield. His undergraduate education was completed at the University of Engineering and Technology (UET), Taxila, where he graduated with honors in Computer Engineering, finishing with the second-highest percentage in his class. In 2019-2020, he was awarded a prestigious Fulbright Fellowship at the University of Central Florida, focusing on deep learning for medical image analysis. His diverse and interdisciplinary academic foundation, spanning engineering and medical technology, forms the basis of his expertise in cutting-edge research areas like artificial intelligence, machine learning, and medical image computing.

Experience👨‍🏫

Dr. Anwar’s career spans a wide array of academic and industry positions. Currently, he serves as Principal Investigator at Children’s National Hospital and Associate Professor at George Washington University. He was previously an Associate Professor at the University of Engineering and Technology, Taxila, where he held numerous administrative and advisory roles. He has also worked internationally, including as a Research Fellow at the University of Surrey, UK, and a Research Associate at the University of Central Florida, USA. Dr. Anwar has extensive experience in the tech industry, having co-founded several companies, including EcoEdge AI and Sense Digital Pvt. Ltd., where he served as CTO. His industrial roles have focused on deep learning, medical imaging, and healthcare solutions. Additionally, he has mentored entrepreneurs and served as an advisor at national incubation centers, underscoring his role as a bridge between academia and industry in technology and innovation.

Research Interest🔬 

Dr. Anwar’s research interests are deeply rooted in medical image analysis, artificial intelligence, and deep learning. His work primarily focuses on utilizing deep learning models to improve medical diagnostics, especially in fields such as brain tumor segmentation, pediatric health, and cardiac health monitoring. He is particularly interested in applying machine learning techniques to enhance medical imaging technologies, exploring areas like brain-computer interfaces and wearable health technologies. His projects also delve into federated learning for medical imaging security and using AI to predict health outcomes, such as in sickle cell disease management. Throughout his career, Dr. Anwar has sought to bridge the gap between medical science and computational technology, aiming to create innovative, data-driven healthcare solutions. His interdisciplinary research has earned him international recognition, positioning him as a key figure in advancing AI-driven medical applications.

Awards and Honors🏆

Dr. Anwar has received numerous prestigious awards and honors throughout his career. He was a Fulbright Fellow at the University of Central Florida, USA, where he focused on applying deep learning to medical image analysis. He has also been awarded several research grants, including a $220,000 seed grant from IGNITE for his work in fashion retrieval using deep learning and a $1200 grant from NVIDIA for hardware development. His contributions to academia have been widely recognized, with multiple travel grants awarded by the Higher Education Commission of Pakistan for presenting his research at international conferences. Additionally, Dr. Anwar has played a leading role in student mentorship, entrepreneurship, and incubation programs, where he has been recognized as a mentor at national incubation centers and the Pak-US Alumni Network. His leadership roles and innovative research projects have earned him a reputation for academic excellence and contribution to the global research community.

Skills🛠️

Dr. Anwar possesses a robust set of technical and leadership skills. His core expertise lies in deep learning, medical image analysis, and artificial intelligence. He is proficient in applying machine learning algorithms to a variety of real-world problems, especially in healthcare technologies. His strong background in software and hardware engineering includes experience with EEG-based systems, brain-computer interfaces, and remote health monitoring. Additionally, Dr. Anwar is skilled in research design, grant writing, and project management, having secured significant funding for his projects. His entrepreneurial abilities are demonstrated through his co-founding of tech startups and his role as CTO, where he has led development teams in creating innovative AI solutions. He also excels in academic mentoring, having supervised multiple PhD students and contributed to curriculum development in machine learning and computer vision at universities.

Conclusion 🔍 

Dr. Syed Muhammad Anwar is a highly accomplished researcher whose contributions to medical image analysis, deep learning, and AI in healthcare make him a strong candidate for the Best Researcher Award. His distinguished career, which spans academia, industry, and entrepreneurial ventures, highlights his ability to blend research innovation with real-world applications. His extensive publication record, high citation count, and successful leadership in numerous research projects underscore his academic impact. Dr. Anwar’s interdisciplinary approach, combining engineering with healthcare solutions, and his ability to secure significant research funding demonstrate his excellence in research and innovation. With a deep commitment to advancing technology for medical applications, Dr. Anwar’s work continues to influence both academic research and the practical development of AI-driven healthcare systems.

Publication Top Notes

Title: BPMN extension evaluation for security requirements engineering framework
Authors: Zareen, S., Anwar, S.M.
Year: 2024
Citation Count: 1

Title: Development of a Modular Real-time Shared-control System for a Smart Wheelchair
Authors: Ramaraj, V., Paralikar, A., Lee, E.J., Anwar, S.M., Monfaredi, R.
Year: 2024
Citation Count: 0

Title: An automated framework for pediatric hip surveillance and severity assessment using radiographs
Authors: Lam, V.K., Fischer, E., Jawad, K., Cleary, K., Anwar, S.M.
Year: 2024
Citation Count: 0

Title: Quantitative Metrics for Benchmarking Medical Image Harmonization
Authors: Parida, A., Jiang, Z., Packer, R.J., Anwar, S.M., Linguraru, M.G.
Year: 2024
Citation Count: 0

Title: MR to CT Synthesis Using 3d Latent Diffusion
Authors: Tapp, A., Parida, A., Zhao, C., Anwar, S.M., Linguraru, M.G.
Year: 2024
Citation Count: 0

Title: Zero-Shot Pediatric Tuberculosis Detection in Chest X-Rays Using Self-Supervised Learning
Authors: Capellan-Martin, D., Parida, A., Gomez-Valverde, J.J., Ledesma-Carbayo, M.J., Anwar, S.M.
Year: 2024
Citation Count: 0

Title: Early prognostication of overall survival for pediatric diffuse midline gliomas using MRI radiomics and machine learning: A two-center study
Authors: Liu, X., Jiang, Z., Roth, H.R., Bornhorst, M., Linguraru, M.G.
Year: 2024
Citation Count: 0

Title: EEG-Based Emotion Recognition during Mobile Gameplay
Authors: Khan, S.H., Raheel, A., Majid, M., Anwar, S.M., Arsalan, A.
Year: 2024
Citation Count: 0

Title: CHILD FER: DOMAIN-AGNOSTIC FACIAL EXPRESSION RECOGNITION IN CHILDREN USING A SECONDARY IMAGE DIFFUSION MODEL
Authors: Lee, E., Lee, E.-J., Anwar, S.M., Yoo, S.B.
Year: 2024
Citation Count: 0

Title: Self-Supervised Learning for Seizure Classification using ECoG spectrograms
Authors: Lam, V., Oliugbo, C., Parida, A., Linguraru, M.G., Anwar, S.M.
Year: 2024
Citation Count: 0

Laxmi Rathour | Mathematics | Young Scientist Award

Laxmi Rathour | Mathematics | Young Scientist Award

Research Scholar at National Institute of Technology Mizoram, India.

Laxmi Rathour is an emerging scholar in the field of mathematics, currently serving as a researcher at the National Institute of Technology (NIT), Mizoram. With a strong academic background and a focused research agenda, her expertise lies in both pure and applied mathematics, particularly in areas such as Multi-Attribute Decision Making (MADM), Multi-Criteria Decision Making (MCDM), and Nonlinear Analysis. She is actively involved in research, contributing to journals and collaborating internationally as a reviewer for prestigious publications like Mathematical Reviews (USA) and Zentralblatt Math (Germany). As she continues to pursue her Ph.D., Rathour is deeply engaged in advancing mathematical theory and its practical applications. Her research presence is growing on platforms such as SCOPUS and ResearchGate, and she is quickly establishing herself as a dedicated and impactful researcher in her field, making significant strides in her academic and professional career.

Profile👤

Scopus

ORCID

Education📝

Laxmi Rathour holds a Master’s degree in Mathematics from the Indira Gandhi National Tribal University in Amarkantak, Madhya Pradesh, India. She pursued her postgraduate studies from July 2019 to August 2021, during which she developed her foundational knowledge and research skills in various mathematical disciplines. Currently, she is furthering her academic pursuits by working toward a Ph.D., with a focus on advanced mathematical topics such as Meta Heuristic algorithms and Fractional Calculus. Her educational background has provided her with a strong grounding in both theoretical and applied aspects of mathematics, equipping her to explore complex mathematical problems. Rathour’s academic journey reflects her dedication to research and her desire to contribute new knowledge to the field of mathematics. Her ongoing Ph.D. studies are expected to deepen her expertise and enhance her impact as a researcher.

Experience👨‍🏫

Laxmi Rathour has been affiliated with the National Institute of Technology (NIT), Mizoram, since July 2023, where she serves as a researcher in the Department of Mathematics. Her role involves conducting research in specialized areas such as Multi-Objective Transportation Problems (MOTP) and Nonlinear Analysis. Prior to joining NIT, Rathour was actively involved in research during her master’s studies at Indira Gandhi National Tribal University, where she began developing her interests in optimization and decision-making algorithms. Additionally, she has gained experience as a voluntary reviewer for international mathematical publications, enhancing her exposure to global academic standards. This role has provided her with valuable insights into current trends in mathematical research, as well as opportunities to engage with complex theoretical concepts and methodologies, which have contributed to her growth as a researcher.

Research Interest🔬 

Laxmi Rathour’s research interests lie in a variety of mathematical disciplines, primarily focusing on applied and pure mathematics. Her areas of expertise include Multi-Attribute Decision Making (MADM), Multi-Criteria Decision Making (MCDM), and Multi-Objective Transportation Problems (MOTP), which are important in the context of optimization and decision-making processes. Additionally, she explores Fractional Calculus, Nonlinear Analysis, and Meta Heuristic algorithms. Rathour’s work in Fixed Point Theory and Approximation Theory contributes to solving complex mathematical models, with applications in both academic and real-world problems. Her research is oriented toward advancing mathematical theory while also seeking practical applications in optimization and decision-making, making her contributions valuable in a wide range of industries and scientific disciplines.

Awards and Honors🏆

Though specific awards and honors are not explicitly listed, Laxmi Rathour’s academic achievements and professional engagements highlight her growing recognition in the field of mathematics. She has earned respect as a reviewer for leading mathematical journals, including Mathematical Reviews (USA) and Zentralblatt Math (Germany). These roles demonstrate her expertise and the recognition she has gained within the global mathematical community. In addition to her reviewer positions, Rathour’s research has been published in several national and international journals, further indicating her contributions to her field. As her career progresses, it is likely that she will continue to earn accolades for her research and academic achievements, solidifying her status as an accomplished mathematician.

Skills🛠️

Laxmi Rathour possesses a diverse skill set that complements her research in mathematics. Her technical expertise includes proficiency in decision-making algorithms such as MADM and MCDM, as well as optimization techniques involving Multi-Objective Transportation Problems (MOTP). Additionally, she is skilled in using Meta Heuristic algorithms and advanced mathematical methods such as Fractional Calculus and Nonlinear Analysis. These skills are crucial for tackling complex mathematical problems, particularly in the areas of optimization and decision-making. Beyond her technical capabilities, Rathour also has strong analytical and problem-solving abilities, which are essential for conducting high-level research. Her role as a reviewer further underscores her critical thinking and editorial skills, making her a well-rounded researcher with both theoretical and applied mathematical expertise.

Conclusion 🔍 

Laxmi Rathour is a promising researcher in the field of mathematics, with a particular focus on decision-making algorithms, optimization, and advanced mathematical theories. Her academic journey, which began at Indira Gandhi National Tribal University and continues with her Ph.D. studies, reflects her dedication to expanding her knowledge and contributing to the global body of mathematical research. Her current role at the National Institute of Technology, Mizoram, allows her to further her research in specialized areas while also engaging with the broader academic community through publications and peer-review activities. As she continues to develop her skills and expertise, Rathour is poised to make significant contributions to both the theoretical and applied aspects of mathematics, positioning herself as an influential figure in the field.

Publication Top Notes

A simple and efficient preprocessing step for convex hull problem
Author: Laxmi Rathour
Year: 2024
Citation: Rathour, L. (2024). A simple and efficient preprocessing step for convex hull problem. Discrete Mathematics, Algorithms and Applications. https://doi.org/10.1142/S179383092350091X

Tracing roots and linkages: Harnessing graph theory and social network analysis in genealogical research, based on the kin naming system
Author: Laxmi Rathour
Year: 2024
Citation: Rathour, L. (2024). Tracing roots and linkages: Harnessing graph theory and social network analysis in genealogical research, based on the kin naming system. Discrete Mathematics, Algorithms and Applications. https://doi.org/10.1142/S1793830924500678

On r-dynamic k-coloring of ladder graph families
Author: Laxmi Rathour
Year: 2024
Citation: Rathour, L. (2024). On r-dynamic k-coloring of ladder graph families. Discrete Mathematics, Algorithms and Applications. https://doi.org/10.1142/S1793830924500356

Duality under novel generalizations of the D-Type-I functions for multiple objective nonlinear programming problems
Author: Laxmi Rathour
Year: 2024
Citation: Rathour, L. (2024). Duality under novel generalizations of the D-Type-I functions for multiple objective nonlinear programming problems. Scientific African. https://doi.org/10.1016/j.sciaf.2024.e02067

A Time-Sequential Probabilistic Hesitant Fuzzy Approach to a 3-Dimensional Green Transportation System
Author: Laxmi Rathour
Year: 2024
Citation: Rathour, L. (2024). A Time-Sequential Probabilistic Hesitant Fuzzy Approach to a 3-Dimensional Green Transportation System. In book: Smart Green Innovations for Sustainable Development. https://doi.org/10.1007/978-3-031-56304-1_9

Generalized Rational Type Contraction and Fixed Point Theorems in Partially Ordered Metric Spaces
Author: Laxmi Rathour
Year: 2023
Citation: Rathour, L. (2023). Generalized Rational Type Contraction and Fixed Point Theorems in Partially Ordered Metric Spaces. Journal of Advances in Applied & Computational Mathematics. https://doi.org/10.15377/2409-5761.2023.10.13

Integration of Rational Functions
Author: Laxmi Rathour
Year: 2023
Citation: Rathour, L. (2023). Integration of Rational Functions. Journal of Multidisciplinary Applied Natural Science. https://doi.org/10.47352/jmans.2774-3047.186

Possible directions of increasing the efficiency of the health system through software development
Author: Laxmi Rathour
Year: 2023
Citation: Rathour, L. (2023). Possible directions of increasing the efficiency of the health system through software development. Brazilian Journal of Science. https://doi.org/10.14295/bjs.v3i1.450

A Newton-like Midpoint Method for Solving Equations in Banach Space
Author: Laxmi Rathour
Year: 2023
Citation: Rathour, L. (2023). A Newton-like Midpoint Method for Solving Equations in Banach Space. Foundations. https://doi.org/10.3390/foundations3020014

Coupled Fixed Point Theorems with Rational Type Contractive Condition via C-Class Functions and Inverse Ck-Class Functions
Author: Laxmi Rathour
Year: 2022
Citation: Rathour, L. (2022). Coupled Fixed Point Theorems with Rational Type Contractive Condition via C-Class Functions and Inverse Ck-Class Functions. Symmetry. https://doi.org/10.3390/sym14081663