Ana-Maria Bordei | Mathematics | Best Researcher Award

Ms. Ana-Maria Bordei | Mathematics | Best Researcher Award

Research Scientist III from NATIONAL INSTITUTE FOR AEROSPACE RESEARCH “ELIE CARAFOLI” – INCAS, Bucharest, Romania

Dr. Ana-Maria Bordei is a seasoned researcher in Applied Mathematics, with particular expertise in control theory, delay differential equations (DDEs), and aerospace systems modeling. Currently serving as a Research Scientist III at the National Institute for Aerospace Research “Elie Carafoli” (INCAS) in Bucharest, she contributes significantly to Romania’s aerospace innovation landscape. Her work involves the mathematical modeling and control of UAV swarms, especially under time-delayed conditions—an area of growing significance in modern aerospace engineering. Dr. Bordei’s research merges deep theoretical knowledge with practical engineering applications, targeting problems in both aviation and biomedical sciences. She has authored several peer-reviewed articles in ISI-indexed journals and presented her work at major international conferences such as ICNFAA and ETAMS. Beyond research, she actively engages in technical workshops and collaborative missions such as orbital flight simulations and UAV traffic management systems. Her academic and professional journey exemplifies a balanced blend of analytical rigor, interdisciplinary thinking, and technical innovation. Dr. Bordei’s dedication to advancing aerospace science through mathematical precision makes her a leading figure in her field and a strong nominee for the Best Researcher Award. Her future work is anticipated to impact both theoretical advancements and real-world aerospace applications on a global scale.

Professional Profile

Education

Dr. Ana-Maria Bordei possesses a comprehensive academic background in mathematics and its applications in engineering and science. She earned her Ph.D. in Applied Mathematics from the University Politehnica of Bucharest between 2015 and 2020. Her doctoral research, titled “Control Delay Differential Equations with Applications in Engineering and Medicine,” focused on the development and analysis of dynamic control systems with delays—highly relevant to aerospace control strategies and medical modeling. Before pursuing her doctorate, she completed a Master’s degree in Applied Mathematics from the same university (2013–2015), where she deepened her understanding of differential equations, control systems, and optimization techniques. Her academic journey began with a Bachelor’s degree in Mathematics at the University ‘Dunărea de Jos’ in Galați (2009–2012), which provided a strong theoretical foundation. Throughout her studies, Dr. Bordei demonstrated consistent academic excellence and a passion for bridging mathematical theory with engineering applications. Her educational experiences have enabled her to work at the intersection of mathematics, aerospace systems, and biomedical modeling, making her well-equipped for both academic research and industrial collaboration. She continues to apply her academic background toward the development of innovative aerospace control systems and delay-based mathematical models.

Professional Experience

Since 2018, Dr. Ana-Maria Bordei has held the position of Research Scientist III at the National Institute for Aerospace Research “Elie Carafoli” (INCAS) in Bucharest, Romania. In this role, she contributes to national and international research projects focused on advanced aerospace technologies, including unmanned aerial vehicle (UAV) swarm modeling and orbital mission control systems. Her responsibilities include mathematical modeling, stability analysis, simulation, and control strategy development for delayed dynamic systems. She has played a pivotal role in various aerospace programs, including the Space System Laboratory’s orbital missions and UAV traffic management systems. Prior to her current role, Dr. Bordei was actively involved in academic research throughout her doctoral and postdoctoral journey, collaborating with prominent mathematicians and aerospace engineers. Her experience extends to the development of robust control algorithms, the application of PID and SDRE methods for spacecraft tracking, and stability analysis in nonlinear flight dynamics. She frequently collaborates across disciplines, working with engineers, physicists, and medical professionals to solve complex, real-world problems. Through her applied work and theoretical insight, Dr. Bordei demonstrates strong leadership and technical capabilities. Her professional trajectory reflects a consistent focus on bridging mathematics with aerospace engineering to drive research innovation.

Research Interests

Dr. Ana-Maria Bordei’s research interests lie at the nexus of applied mathematics and aerospace engineering, with a particular focus on control theory, delay differential equations (DDEs), stability analysis, and autonomous UAV systems. Her academic background in mathematics and her practical experience at INCAS have led her to investigate control problems involving time delays, a critical issue in the design of modern aerospace and engineering systems. One of her core research themes is the behavior of UAV swarms under delayed control feedback, for which she has developed novel mathematical models and stability theorems. She also explores the biomedical applications of DDEs, such as modeling the dynamics of chronic diseases like leukemia under drug treatment. This multidisciplinary approach allows her to apply rigorous mathematical methods to both engineering and healthcare challenges. Additionally, she has worked on spacecraft rendezvous and tracking control using PID and state-dependent Riccati equation (SDRE) methods. Dr. Bordei is particularly interested in expanding her research into intelligent control systems, nonlinear dynamics, and aerospace traffic management in increasingly autonomous and interconnected systems. Her work bridges theoretical insights with real-world application, ensuring that mathematical precision translates into engineering reliability.

Research Skills

Dr. Ana-Maria Bordei possesses a robust set of research skills that enable her to tackle complex problems in applied mathematics and control systems engineering. She has advanced expertise in the formulation and analysis of delay differential equations (DDEs), including their use in stability theory and dynamic modeling. Her computational skills include proficiency in MATLAB/Simulink for simulation of control systems and numerical analysis, and she is adept at using LaTeX for scientific documentation. She is experienced in the design of feedback control strategies, particularly PID and SDRE-based controllers, which she has applied to aerospace navigation and rendezvous problems. Dr. Bordei is also skilled in mathematical modeling of biological systems, notably in modeling the progression of diseases and treatment resistance. Her analytical capabilities are complemented by her ability to collaborate across disciplines and convey complex mathematical concepts to engineering audiences. She regularly contributes to research reports, peer-reviewed journal articles, and conference proceedings. Moreover, her involvement in experimental simulation environments and systems validation through real-time modeling at INCAS demonstrates her aptitude in applied research and technology transfer. These combined skills make her a valuable contributor to both academic and applied science communities.

Awards and Honors

Dr. Ana-Maria Bordei has earned notable recognition throughout her academic and professional career for her contributions to mathematics and aerospace research. While formal award titles are not extensively listed, her continuous progression within one of Romania’s leading aerospace research institutions (INCAS) reflects institutional acknowledgment of her expertise and innovation. Her selection to present at prominent international conferences such as ICNFAA, ETAMS, and AEROSPATIAL showcases her scholarly merit and the relevance of her research to the global community. Participation in prestigious summer schools such as Computational Tools for Delay Differential Equations underlines her academic potential and the recognition she has received from training bodies. In addition, her appointment as a Research Scientist III signifies both trust and leadership within her organization. Dr. Bordei’s co-authorship in multiple ISI-indexed journal articles, and invitations to contribute to collaborative projects across Europe, serve as implicit endorsements of her research caliber. While further international accolades or fellowships could elevate her profile globally, her consistent publication record and leadership roles in applied projects clearly mark her as a respected researcher in her field. Future award recognitions will likely follow as she continues to expand her research outreach and collaborations.

Conclusion

Dr. Ana-Maria Bordei exemplifies the qualities of an outstanding researcher through her interdisciplinary expertise, scientific rigor, and impactful contributions to applied mathematics and aerospace systems. Her academic foundation, fortified by a Ph.D. in Applied Mathematics, enables her to approach complex engineering challenges with precision and depth. Her work on delay differential equations and their application to UAV control systems not only advances theoretical knowledge but also addresses practical engineering problems of national and international significance. Through her role at INCAS, she has led and contributed to critical aerospace initiatives, cementing her as a key figure in Romania’s aerospace research community. She has consistently demonstrated scholarly excellence through her publications, presentations, and collaborative projects. Her future research holds promise in expanding into intelligent autonomous systems and broader biomedical modeling. With her unique blend of mathematical insight and engineering application, Dr. Bordei stands as a deserving candidate for the Best Researcher Award. Her trajectory indicates a strong potential for future leadership in academic and applied research environments, and her contributions continue to inspire innovation at the interface of mathematics, aerospace, and system control.

Publications Top Notes

  1. Dynamics of Chronic Myeloid Leukemia Under Imatinib Treatment: A Study of Resistance Development
    I. Badralexi, A.M. Bordei, A. Halanay, I.R. Rădulescu
    Mathematics, 2024, Vol. 12 (24), Article 3937
    ➤ Explores resistance development in leukemia using dynamic models under Imatinib therapy.

  2. Rank-One Perturbations and Stability of Some Equilibrium Points in a Complex Model of Cells Evolution in Leukemia
    I. Badralexi, A.M. Bordei, A. Halanay
    Scientific Bulletin. Series A, Polytechnical University of Bucharest, 2018
    ➤ Investigates mathematical stability conditions for leukemia cell models.

  3. Stability Analysis for a UAV Model in Longitudinal Flight
    A.M. Bordei, A. Halanay
    INCAS Bulletin, 2017, 9(4): 21–29
    ➤ Discusses stability in UAV dynamics under linear control approximations.

  4. Stability of Limit Cycles in a Longitudinal Flight of a UAV
    A.M. Bordei, A. Halanay
    AIP Conference Proceedings, 2018, 2046(1): 020011
    ➤ Addresses periodic behavior in nonlinear UAV flight systems.

  5. Stability Study for the Longitudinal Flight of Formations of UAVs Considering Delays in Controls
    A.M. Bordei, A. Halanay
    ➤ A systems-level analysis of UAV formations with time-delay feedback systems.

  6. Stability for Small Delays, Metzler Matrices and an Application to a Flight Controller Design
    A.M. Bordei, A. Halanay
    ➤ Theoretical insights into delay-tolerant flight controller synthesis using structured matrix theory.

  7. Using PID Controller and SDRE Methods for Tracking Control of Spacecrafts in Closed-Rendezvous Process
    T. Van Nguyen, A.M. Bordei, T.M. Nguyen, A. Ionita
    INCAS Bulletin, 2019, 11(1): 139–150
    ➤ Combines classical and nonlinear control techniques for precise satellite docking maneuvers.

 

 

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