Dr. Bruce a. wade – Computational Mathematics – Best Researcher Award

Dr. Bruce a. wade - Computational Mathematics - Best Researcher Award

University of Louisiana at Lafayette - United States

Author Profile 

SCOPUS 

Early academic pursuits 🎓

Bruce a. wade's journey in mathematics began with an unwavering passion for numerical analysis and computational mathematics. he pursued his bachelor’s degree in mathematics from the university of wisconsin-madison in 1982, followed by a master’s degree in mathematics in 1984. eager to delve deeper into the complexities of mathematical modeling and optimization, he completed his ph.d. in mathematics in 1987 under the guidance of professor j.c. strikwerda. during his doctoral research, he explored numerical methods for solving partial differential equations, setting the foundation for his future contributions to computational mathematics.

Professional endeavors 💼

Bruce wade has had a distinguished academic career, holding key positions at several esteemed institutions. he began his professional journey as a post-doctoral fellow at cornell university’s mathematical sciences institute, where he worked under the mentorship of l.b. wahlbin. he later joined the university of wisconsin–milwaukee, progressing from assistant professor to full professor, and ultimately serving as chair of the department of mathematical sciences. in 2018, he transitioned to the university of louisiana at lafayette, where he currently serves as professor and head of the department of mathematics. his leadership roles have significantly shaped academic programs, research initiatives, and technological advancements within these institutions.

Contributions and research focus 🔬

Bruce wade's research is deeply rooted in numerical analysis and computational mathematics, particularly in the areas of partial differential equations, optimization, data science, and machine learning. he has developed advanced numerical techniques for solving complex mathematical models, contributing to various fields such as industrial mathematics and stochastic processes. Computational Mathematics his interdisciplinary approach has led to significant advancements in modeling real-world phenomena, including pigment and filler settling in coatings and nonlinear control systems for the paper industry. his research also extends to numerical solutions of reaction-diffusion equations and adaptive techniques for satellite orbit calculations.

Accolades and recognition 🏆

Bruce wade’s contributions to mathematics have been widely recognized, earning him prestigious positions and honors. he was appointed as the c.b.i.t. tc/leqsf regents professor at the Computational Mathematics university of louisiana at lafayette in 2019. in addition, he has served as a professor emeritus at the university of wisconsin-milwaukee since 2018. his extensive list of grants from esteemed institutions, including the national science foundation (nsf) and the national security agency (nsa), showcases the significance of his research in applied mathematics and computational techniques.

Impact and influence 🌎

The impact of bruce wade's work extends beyond academia, influencing industries and governmental research initiatives. as the founder and director of the center for industrial mathematics at the university of wisconsin-milwaukee, he played a pivotal role in bridging the gap between theoretical mathematics and practical industrial applications. his collaborative projects with Computational Mathematics companies like rust-oleum corporation and rockwell automation have led to innovative solutions in material science and control systems. his research has not only enhanced scientific understanding but has also contributed to technological advancements with real-world implications.

Legacy and future contributions 🎨

Bruce wade’s legacy is defined by his unwavering commitment to advancing computational mathematics and fostering future generations of mathematicians. his mentorship and leadership have inspired countless students and researchers to pursue careers in numerical analysis and data science. as he continues his academic and research journey, his future contributions promise to further expand the applications of numerical modeling in various scientific domains. his dedication to exploring new mathematical frontiers ensures that his influence in the field of computational mathematics will endure for years to come.

Notable Publications 

  • Title: A fourth-order exponential time differencing scheme with dimensional splitting for non-linear reaction–diffusion systems
    Author(s): Emmanuel O. Asante-Asamani, Andreas Kleefeld, Bruce Alan Wade
    Journal: Journal of Computational and Applied Mathematics, 2025

  • Title: Global-Padé Approximation of the Three-Parameter Mittag-Leffler Function: Generalized Derivation and Numerical Implementation Issues
    Author(s): Yusuf O. Afolabi, Toheeb A. Biala, Ibrahim O. Sarumi, Bruce Alan Wade
    Journal: Communications on Applied Mathematics and Computation, 2025

  • Title: Two new generators of Archimedean copulas with their properties
    Author(s): Agnideep Aich, Ashit Baran Aich, Bruce Alan Wade
    Journal: Communications in Statistics - Theory and Methods, 2025

  • Title: Exploring a Mathematical Model with Saturated Treatment for the Co-Dynamics of Tuberculosis and Diabetes
    Author(s): Saburi Rasheed, Olaniyi S. Iyiola, S. I. Oke, Bruce Alan Wade
    Journal: Mathematics, 2024

Dr. Agnieszka Niemczynowicz – Machine Learning – Best Researcher Award 

Dr. Agnieszka Niemczynowicz - Machine Learning - Best Researcher Award 

Cracow University of technology - Poland

AUTHOR PROFILE 

ORCID 

EARLY ACADEMIC PURSUITS 🎓

Agnieszka Niemczynowicz began her academic journey in the field of solid-state physics, earning her Ph.D. from the Faculty of Physics and Applied Informatics at the University of Łódź, Poland, in 2014. Her early research laid a strong foundation in the fundamental aspects of physics, equipping her with a deep understanding of physical systems and analytical techniques.

PROFESSIONAL ENDEAVORS 🏢

Upon completing her doctorate, Agnieszka transitioned into academia, taking up the role of Associate Professor at the Cracow University of Technology. She has since been instrumental in bridging the gap between physics and computational sciences, expanding her research horizons to include computational and mathematical methods for analyzing complex data sets across various disciplines.

CONTRIBUTIONS AND RESEARCH FOCUS 🔍

Agnieszka’s research is at the forefront of computational analysis, focusing on multivariate statistics, chemometrics, and deep learning. She has developed advanced statistical and machine Machine Learning learning models that have found applications in diverse fields such as engineering, biology, medicine, and management. Her work is characterized by its interdisciplinary approach, integrating complex data analysis methods into practical applications.

ACCREDITATIONS AND RECOGNITION 🏅

A prolific researcher, Agnieszka has authored around 50 publications in international journals, contributing significantly to her field. Her excellence in research was recognized with the Machine Learning prestigious Doak Award in 2022, highlighting her impactful contributions to the scientific community and her role as a thought leader in computational analysis.

IMPACT AND INFLUENCE 🌍

Agnieszka’s work has had a significant impact on how complex analytical data is interpreted and utilized across various sectors. Her models have improved the accuracy of data-driven Machine Learning decisions in numerous applications, thereby enhancing the efficiency and effectiveness of processes in engineering, biology, medicine, and more.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Currently leading international research grants, Agnieszka investigates the mathematical foundations of hypercomplex neural networks and their applications. Her ongoing work promises to further unravel the complexities of data analysis, pushing the boundaries of what machine learning and computational methods can achieve. Her legacy lies in her pioneering efforts to integrate advanced mathematical models into practical solutions, ensuring that her influence will be felt across multiple disciplines for years to come.

NOTABLE PUBLICATIONS 

  • Title: A critical analysis of the theoretical framework of the Extreme Learning Machine
    Authors: Irina Perfilieva, Nicolás Madrid, Manuel Ojeda-Aciego, Piotr Artiemjew, Agnieszka Niemczynowicz
    Journal: Neurocomputing
  • Title: Use of physicochemical, FTIR and chemometric analysis for quality assessment of selected monofloral honeys
    Authors: Monika Kędzierska-Matysek, Anna Teter, Mariusz Florek, Arkadiusz Matwijczuk, Agnieszka Niemczynowicz, Alicja Matwijczuk, Grzegorz Czernel, Piotr Skałecki, Bożena Gładyszewska
    Journal: Journal of Apicultural Research
  • Title: Conclusions
    Authors: Joanna Nieżurawska, Radosław Antoni Kycia, Agnieszka Niemczynowicz
    Journal: (Book chapter, not a journal)
  • Title: Current research methods in mathematical and computer modelling of motivation management
    Authors: Agnieszka Niemczynowicz, Radosław Antoni Kycia
    Journal: (Book chapter, not a journal)
  • Title: Introduction
    Authors: Joanna Nieżurawska, Radosław Antoni Kycia, Agnieszka Niemczynowicz
    Journal: (Book chapter, not a journal)

Prof. Irina Perfilieva – machine learning – Best Researcher Award 

Prof. Irina Perfilieva - machine learning - Best Researcher Award 

University of Ostrava - Czech Republic

AUTHOR PROFILE 

ORCID 

🎓 EARLY ACADEMIC PURSUITS

Professor Irina Perfilieva embarked on her academic journey at the prestigious Lomonosov State University in Moscow, Russia, where she earned her M.S. in Applied Mathematics in 1975, followed by a Ph.D. in 1980. Her early academic endeavors laid a solid foundation in applied mathematics, setting the stage for her future contributions to the field.

🏫 PROFESSIONAL ENDEAVORS

Irina Perfilieva holds the position of full professor of Applied Mathematics at the University of Ostrava in the Czech Republic. Her esteemed career has included roles as Professor Honoris Causa at the Amity Institute of Information Technology, India, and Doctor Honoris Causa at the University of Latvia. Throughout her professional journey, she has been an influential figure in the academic community, especially in the realm of fuzzy logic and applied mathematics.

📚 CONTRIBUTIONS AND RESEARCH FOCUS

Professor Perfilieva has made significant contributions to the field of fuzzy logic and mathematical modeling. She is the author and co-author of six influential books and has published over 270 papers. Her pioneering method of fuzzy transforms has found successful applications in image and time series processing, numerical analysis, and solving complex equations. Her machine learning research also delves into data analysis and the mathematical foundations of neural networks, utilizing both modern and classical approaches.

🏆 ACCOLADES AND RECOGNITION

Her extensive contributions to the scientific community have earned her numerous awards, including being named an IFSA Fellow and an honorary member of EUSFLAT. In 2012, she was the machine learning recipient of the 1st memorial Da Ruan award. These accolades reflect her esteemed status and the impact of her work globally.

🌍 IMPACT AND INFLUENCE

As an area editor for Soft Computing and a member of several prestigious editorial boards, Professor Perfilieva has influenced the direction of research in fuzzy systems. She has also served on machine learning Program Committees for leading international conferences, further amplifying her impact in the academic and research communities.

🌟 LEGACY AND FUTURE CONTRIBUTIONS

With her innovations in fuzzy logic and mathematical modeling, Irina Perfilieva's work continues to shape future research. Her methods are widely accepted and applied, demonstrating a legacy of academic excellence and practical utility. Her ongoing exploration into data analysis and neural networks signifies her commitment to advancing knowledge in these critical areas.

NOTABLE PUBLICATIONS 

  • Title: "A critical analysis of the theoretical framework of the Extreme Learning Machine"
    Authors: Irina Perfilieva, Nicolás Madrid, Manuel Ojeda-Aciego, Piotr Artiemjew, Agnieszka Niemczynowicz
    Journal: Neurocomputing
  • Title: "Extreme Learning Machine – A New Machine Learning Paradigm"
    Author: Irina Perfilieva
    Journal: Book Chapter (part of a book series, not a journal)
  • Title: "F-transform utility in the operational-matrix approach to the Volterra integral equation"
    Authors: Perfilieva, Irina; Ziari, Shokrollah; Nuraei, Rahele; Pham, Thi Minh Tam
    Journal: Fuzzy Sets and Systems
  • Title: "Generalized Fuzzy Transform and Non-Local Laplace Operator"
    Authors: Hana Zamecnıkova, Simone Cammarasana, Irina Perfilieva, Giuseppe Patane
    Journal: IEEE Transactions on Fuzzy Systems
  • Title: "Numerical solution of a new mathematical model for intravenous drug administration"
    Authors: Alijani, Zahra; Shiri, Babak; Perfilieva, Irina; Baleanu, Dumitru
    Journal: Evolutionary Intelligence

Dr. S. Gopal Krishna Patro – Machine Learning and Deep Learning – Best Researcher Award

Dr. S. Gopal Krishna Patro - Machine Learning and Deep Learning - Best Researcher Award

Woxsen University - India

Professional Profile

SCOPUS

ORCID

Early Academic Pursuits

Dr. S. Gopal Krishna Patro embarked on his academic journey with a focus on computer science and engineering. His dedication to education and research is evident from his extensive teaching experience, which began shortly after completing his advanced studies. His early academic pursuits laid a strong foundation in various aspects of computer science, particularly in automata theory, formal language, and neural networks.

Contributions and Research Focus

Dr. Patro's research and teaching interests span a wide range of topics within computer science. His undergraduate teaching interests include automata theory, formal language, and neural networks. For postgraduate students, he focuses on data mining, data warehousing, and machine learning, particularly recommender systems. His contributions to these fields involve both theoretical exploration and practical applications, Machine Learning and Deep Learning preparing students for both academic and industry careers.

Accolades and Recognition

Throughout his career, Dr. Patro has been recognized for his dedication to teaching and his contributions to academia. His administrative roles, including professor-in-charge of the exam section and coordinator positions, highlight his leadership abilities and commitment to improving Machine Learning and Deep Learning educational outcomes.

Impact and Influence

Dr. Patro's impact extends beyond the classroom. His involvement in placement coordination at GIET University helped bridge the gap between academia and industry, providing students with valuable career opportunities. His role in managing the exam section at K L Deemed to be Machine Learning and Deep Learning University ensured the smooth functioning of academic assessments, contributing to the overall academic integrity of the institution.

Legacy and Future Contributions

Dr. Patro continues to influence the field of computer science education through his teaching, administrative roles, and research. His legacy is marked by his commitment to student success and his efforts to enhance the academic and professional pathways for his students. As he continues his career at Woxsen University, his future contributions are anticipated to further advance the fields of data mining, machine learning, and neural networks, fostering innovation and excellence in computer science education.

NOTABLE PUBLICATIONS