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)

Assoc. Prof. Dr Rui Mao – Artificial intelligence – Best Researcher Award

Assoc. Prof. Dr Rui Mao - Artificial intelligence - Best Researcher Award

Northwest A&F University - China

AUTHOR PROFILE 

SCOPUS 

ORCID 

EARLY ACADEMIC PURSUITS 🎓

Rui Mao’s academic journey began with a master’s degree from Xi’an JiaoTong University, where she developed a keen interest in the application of technology in agriculture. She then pursued a Ph.D. from Northwest A&F University, where her research focused on the intersection of machine learning, image processing, and agriculture. Her strong foundation in these fields allowed her to push the boundaries of innovation in precision agriculture, laying the groundwork for her future research endeavors.

PROFESSIONAL ENDEAVORS 🏫

As an Associate Professor at Northwest A&F University, Rui Mao has been a key figure in bridging the gap between computer science and agriculture. Her extensive academic career includes presiding over four key research and development programs in Shaanxi Province. Additionally, she has contributed to multiple consultancy and industry projects, providing expert guidance on the implementation of machine learning and image processing in real-world agricultural settings.

CONTRIBUTIONS AND RESEARCH FOCUS 🔬

Rui’s research focuses on machine learning, image processing, and pattern recognition, with a primary emphasis on precision agriculture. Her projects have led to the development of innovative solutions for improving agricultural productivity and sustainability. By integrating advanced technologies, her research provides practical applications for improving crop Artificial intelligence management, pest control, and resource optimization. She is also pioneering work on digital agriculture through her collaborations and ongoing projects, which are poised to transform the agricultural industry.

ACCREDITATIONS AND RECOGNITION 🏅

Rui Mao’s work has earned her significant recognition in the scientific community. With a citation index of 128 and 12 publications in prestigious journals, her research has had a considerable impact on the fields of agriculture and technology. Her contributions to digital agriculture and image processing have positioned her as a leading figure in her field. Rui’s expertise is further Artificial intelligence acknowledged through her membership in esteemed professional bodies such as the China Computer Society and the China Association of Image Graphics.

IMPACT AND INFLUENCE 🌍

Rui’s influence extends beyond academia. As a senior member of the China Computer Society and an executive committee member of its Digital Agriculture Branch, she has shaped the Artificial intelligence direction of research in the application of computer science to agriculture. Her work has contributed to the development of smarter, more efficient agricultural practices, which are essential for meeting global food security challenges. Through her innovations, Rui has directly impacted the agricultural technology landscape in China and beyond.

LEGACY AND FUTURE CONTRIBUTIONS 🌱

Rui Mao’s future work promises to continue advancing the integration of machine learning and image processing in agriculture. Her ongoing research on digital agriculture and precision farming has the potential to revolutionize farming practices globally, ensuring more sustainable and efficient food production. As a passionate educator and researcher, Rui is poised to inspire future generations of scientists and innovators, further solidifying her legacy as a pioneer in agricultural technology and machine learning applications.

NOTABLE PUBLICATIONS 

  • Title: A Real-Time Lightweight Behavior Recognition Model for Multiple Dairy Goats
    Authors: Xiaobo Wang, Yufan Hu, Meili Wang, Mei Li, Wenxiao Zhao, Rui Mao
    Journal: Animals (2024-12)
    DOI: 10.3390/ani14243667
  • Title: An Integrated Gather-and-Distribute Mechanism and Attention-Enhanced Deformable Convolution Model for Pig Behavior Recognition
    Authors: Rui Mao, Dongzhen Shen, Ruiqi Wang, Yiming Cui, Yufan Hu, Mei Li, Meili Wang
    Journal: Animals (2024-04)
    DOI: 10.3390/ani14091316
  • Title: GSEYOLOX-s: An Improved Lightweight Network for Identifying the Severity of Wheat Fusarium Head Blight
    Authors: Rui Mao, Zhengchao Wang, Feilong Li, Jia Zhou, Yinbing Chen, Xiaoping Hu
    Journal: Agronomy (2023-01)
    DOI: 10.3390/agronomy13010242

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

Prof . Balasubbareddy Mallala – Machine Learning – Best Researcher Award 

Prof . Balasubbareddy Mallala - Machine Learning - Best Researcher Award 

Chaitanya Bharathi Institute of Technology, Hyderabad - India 

Author Profile

GOOGLE SCHOLAR 

🎓 Early academic pursuits

Dr. M. Balasubbareddy embarked on his academic journey with a strong foundation in electrical and electronics engineering, earning a b.e. degree with distinction. further advancing his expertise, he pursued an m.tech. in power systems, achieving first-class honors. his relentless pursuit of knowledge culminated in a ph.d. in electrical and electronics engineering, where he delved into cutting-edge research, laying the groundwork for a prolific career. his academic curiosity extended to post-doctoral studies, further cementing his reputation as a dedicated scholar.

💼 Professional endeavors

As a professor at chaitanya bharathi institute of technology (cbit), dr. balasubbareddy has dedicated over two decades to teaching and mentoring. since joining cbit in 2017, he has taken on diverse roles, including membership in the college academic committee, anti-ragging committee, and intellectual property rights cell. his leadership as a convener of the ethics committee and departmental research committee has significantly shaped institutional policies and academic growth. with a career spanning 22 years in teaching and 16 years in research, he remains a cornerstone of excellence in academia.

🔬 Contributions and research focus

Dr. Balasubbareddy's research focuses on power systems, power electronics, and soft computing techniques. his innovative work bridges theoretical advancements and practical applications, contributing to sustainable and efficient energy solutions. as an active researcher, he has guided numerous projects and students, fostering a culture of inquiry and innovation. his Machine Learning participation in various institutional committees ensures the integration of research-driven strategies into curriculum development and academic practices.

🏅 Accolades and recognition

Dr. Balasubbareddy has received numerous prestigious awards that underscore his excellence in teaching and research. notable accolades include the best researcher of the year award from Machine Learning jnt university, the national award for teaching excellence, and the dr. radhakrishna award for engineering college teachers. his achievements also include international recognition, such as the global eminent scientist award and best open source learner awards. these honors reflect his dedication to academic and research excellence over the years.

🌟 Impact and influence

Through his extensive teaching and mentorship, dr. balasubbareddy has influenced countless students and colleagues, fostering a legacy of innovation and excellence. his involvement in nba Machine Learning accreditation, institute innovation, and patenting committees has significantly enhanced the academic framework of cbit. his dedication to fostering interdisciplinary collaboration and industry partnerships exemplifies his commitment to advancing the field of electrical and electronics engineering.

🏛️ Legacy and future contributions

Dr. Balasubbareddy's enduring legacy is built on his passion for education, research, and innovation. his ongoing efforts to integrate cutting-edge research with practical applications continue to inspire the next generation of engineers and researchers. as a dedicated mentor, academic leader, and researcher, he envisions a future where his contributions to power systems and soft computing techniques pave the way for sustainable technological advancements.

Notable Publications 

  • Title: Multi-objective optimization in the presence of practical constraints using non-dominated sorting hybrid cuckoo search algorithm
    Authors: M. Balasubbareddy, S. Sivanagaraju, C. V. Suresh
    Journal: Engineering Science and Technology, an International Journal
  • Title: Multi-objective optimization in the presence of ramp-rate limits using non-dominated sorting hybrid fruit fly algorithm
    Authors: M. Balasubbareddy
    Journal: Ain Shams Engineering Journal
  • Title: Salp swarm algorithm for solving optimal power flow problem with thyristor-controlled series capacitor
    Authors: B. Mallala, D. Dwivedi
    Journal: Journal of Electronic Science and Technology
  • Title: Generation and utilization of electrical energy
    Authors: S. Sivanagaraju, M. B. Reddy, D. Srilatha
    Journal: Pearson Education India
  • Title: A non-dominated sorting hybrid cuckoo search algorithm for multi-objective optimization in the presence of FACTS devices
    Authors: M. Balasubbareddy, S. Sivanagaraju, C. Venkata Suresh
    Journal: Russian Electrical Engineering

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