Assoc. Prof. Dr. Kincső Decsi | Data in Brief | Best Researcher Award

Assoc. Prof. Dr. Kincső Decsi | Data in Brief | Best Researcher Award

Assoc. Prof. Dr. Kincső Decsi, Hungarian University of Agricultural and Life Sciences, Institute of Agronomy, Hungary

Assoc. Prof. Dr. Kincső Decsi is a renowned academic in the field of plant physiology and plant ecology, currently serving as an associate professor at the Hungarian University of Agriculture and Life Sciences, Georgikon Campus. She has an extensive academic career, having previously held assistant professor roles at the same institution and at Pannon University. Dr. Decsi earned her Ph.D. in Agricultural and Horticultural Sciences in 2005, summa cum laude, with a dissertation on abiotic stress effects in maize. Her research and teaching focus on plant biotic and abiotic stress physiology, plant growth, and development. She has taught a wide range of courses at the BSc, MSc, and PhD levels, in both Hungarian and English. Dr. Decsi’s research contributions, particularly in plant genetics, bioinformatics, and environmental stress physiology, have significantly advanced our understanding of plant resilience and adaptation. 🌱📚🌍

Professional Profile

Orcid

Suitability for Award

Assoc. Prof. Dr. Kincső Decsi is an exceptional candidate for the Research for Best Researcher Award due to her significant contributions to plant physiology, environmental stress, and plant genetics. Her extensive teaching experience at both undergraduate and postgraduate levels, coupled with her research on plant adaptation to biotic and abiotic stresses, has earned her recognition in academia. Dr. Decsi’s work in bioinformatics and transcriptomics has enhanced the understanding of plant responses to environmental challenges, which is vital for sustainable agriculture. Her leadership in the scientific community, especially in plant physiology and molecular biology, makes her a suitable candidate for this prestigious award. Dr. Decsi’s ability to bridge research and teaching, coupled with her impact on both local and international scientific communities, reflects her dedication to advancing agricultural sciences. 🌾🔬🏅

Education

Assoc. Prof. Dr. Kincső Decsi has an extensive academic background in agricultural sciences. She earned her Ph.D. in Agricultural and Horticultural Sciences from the Hungarian University of Agriculture and Life Sciences in 2005, with summa cum laude honors. Her doctoral research focused on examining the effects of various abiotic stresses on maize. Dr. Decsi’s educational journey began with a Certified Agricultural Engineer qualification from the University of Veszprém, where she also studied plant genetics and plant breeding. Additionally, she completed a Certified Chemistry Teacher qualification at Pannon University in 2023. Dr. Decsi’s early academic experiences were enriched by scholarships such as the Martonvásár and Pioneer Hi-Bred Rt. scholarships, which allowed her to deepen her expertise in plant science. Her education has laid the foundation for her ongoing research and teaching in plant physiology, molecular biology, and bioinformatics. 🎓🌾📖

Experience 

Assoc. Prof. Dr. Kincső Decsi has over two decades of experience in both research and teaching. She currently holds the position of associate professor at the Hungarian University of Agriculture and Life Sciences, Georgikon Campus, where she has taught various plant physiology and molecular biology courses at the BSc, MSc, and PhD levels. Her research experience spans from genetic mapping of potato blight resistance genes to the study of abiotic stress effects in plants. Dr. Decsi has also been involved in bioinformatics research, particularly in transcriptomic studies, enhancing her expertise in plant adaptation and resilience. Her role as a scientific associate at the Festetics György Bioinnovation Research Center further strengthened her research portfolio, contributing to projects on plant genetic mapping and resistance genes. Dr. Decsi’s experience is a blend of practical research, teaching, and leadership in the scientific community. 🌿💼🔬

Awards and Honors

Assoc. Prof. Dr. Kincső Decsi has been recognized for her academic excellence through various scholarships and awards. She received the Pioneer Hi-Bred Rt. Scientific Scholarship and the Martonvásár Scientific Scholarship in the late 1990s and early 2000s, which supported her early academic development. Dr. Decsi was also honored with the Georgikon Outstanding Scholarship for her exceptional performance during her studies. Additionally, she was awarded the Lászlóffy Woldemár Diploma Thesis Application special fee in recognition of her outstanding academic achievements. Her participation in international language courses, such as the Sommerakademie in Neubrandenburg and Wiener Internationale Hochschulkurse, further enriched her academic journey. These awards and honors reflect Dr. Decsi’s dedication to her field and her commitment to advancing plant science research. 🏆🎓🌍

Research Focus 

Assoc. Prof. Dr. Kincső Decsi’s research focuses on plant physiology, particularly the effects of biotic and abiotic stresses on plant growth and development. Her work explores how plants respond to environmental challenges such as drought, salinity, and pathogen attacks, which are critical for improving agricultural resilience. Dr. Decsi has contributed significantly to the field of plant genetics, including the genetic mapping of resistance genes for potato blight and PVY virus resistance. Her research also delves into bioinformatics, particularly in transcriptomic studies, to understand gene expression under stress conditions. Dr. Decsi’s work aims to enhance the sustainability of agricultural practices by improving plant stress tolerance, which is essential for food security in the face of climate change. Her contributions to molecular plant biology, biotechnology, and environmental stress physiology are pivotal in advancing our understanding of plant adaptation mechanisms. 🌱🔬🌿

Publication Top Notes

  • Title: RNA-seq Datasets of Field Rapeseed (Brassica napus) Cultures Conditioned by Elice16Indures (R) Biostimulator
    • Year: 2022
  • Title: RNA-seq Datasets of Field Soybean Cultures Conditioned by Elice16Indures (R) Biostimulator
    • Year: 2022
  • Title: Time-course Gene Expression Profiling Data of Triticum Aestivum Treated by Supercritical CO2 Garlic Extract Encapsulated in Nanoscale Liposomes
    • Year: 2022
  • Title: Transcriptome Datasets of Beta-Aminobutyric Acid (BABA)-Primed Mono- and Dicotyledonous Plants, Hordeum Vulgare and Arabidopsis Thaliana
    • Year: 2022
  • Title: Transcriptome Profiling Dataset of Different Developmental Stage Flowers of Soybean (Glycine Max)
    • Year: 2022

 

 

Prof. Dr. Lei Geng | Data Analysis | Best Researcher Award

Prof. Dr. Lei Geng | Data Analysis | Best Researcher Award

Prof. Dr. Lei Geng, Tiangong University, China

Prof. Dr. Lei Geng is a distinguished professor at the School of Life Sciences, Tiangong University, with a focus on computer vision, machine learning, and measurement technology. He received his Ph.D. in 2012 from Tianjin University and has since made significant contributions to the fields of AI, machine vision, and medical technology. With over 80 published papers, Dr. Geng has played a pivotal role in the development of advanced imaging and measurement technologies for industrial and medical applications. His research includes applications in image analysis, 3D dimensional measurement, and hemostatic medical equipment. As a leader in his field, he has led more than 10 national and provincial-level projects and received numerous awards for his technological innovations. 🚀

Professional Profile:

Scopus
Orcid

Suitability for the Award

Prof. Dr. Lei Geng is highly suitable for the Best Researcher Award due to his groundbreaking work in AI, machine vision, and medical technology. His research has led to the development of advanced image analysis techniques and high-precision measurement tools, with far-reaching implications for both industrial and healthcare applications. Dr. Geng’s leadership in national and provincial projects, combined with his three provincial-level awards, highlights his ability to drive technological advancements that have a direct impact on society. His contributions to AI-based diagnostics, particularly in otolaryngology, underscore his dedication to improving healthcare through cutting-edge technologies. Prof. Geng’s consistent excellence in research, innovation, and application makes him an ideal candidate for this prestigious award. 🏅

Education

🎓 Dr. Lei Geng earned his Ph.D. in 2012 from Tianjin University, specializing in areas at the intersection of computer vision, machine learning, and measurement technology. His academic journey laid the foundation for his extensive contributions to these fields, including the development of cutting-edge applications in industrial and medical sectors. Dr. Geng’s deep understanding of both theoretical and practical aspects of machine vision and artificial intelligence has made him an expert in creating innovative solutions across multiple industries. His education has fueled his ongoing research and contributions to advancements in AI-driven healthcare and precision measurement technologies. 📘

Experience

🧑‍🏫 Prof. Dr. Lei Geng has extensive teaching and research experience, currently serving as a professor at the School of Life Sciences at Tiangong University. He has been involved in both undergraduate and postgraduate education, teaching courses such as Machine Vision and Deep Learning. Over his career, Dr. Geng has undertaken more than 10 national, provincial, and ministerial-level projects, focusing on industrial and medical applications of machine vision and AI. His experience includes pioneering work in hemostatic medical equipment and high-precision 2D/3D measurement systems. This broad range of expertise positions Dr. Geng as a leader in his field, particularly in the integration of AI technologies with practical, real-world applications. 🌍

Awards and Honors

🏅 Dr. Lei Geng’s excellence in research and technological innovation has been recognized through several prestigious awards. He has received three provincial-level awards, including the Tianjin Second Prize for Technological Invention and the Special Prize of the National Award for Business Science and Technology Progress. These accolades are a testament to his significant contributions to the fields of AI, computer vision, and medical technology. Dr. Geng’s ability to bridge the gap between advanced scientific research and practical applications in industries such as healthcare and manufacturing has made him a highly respected figure in the scientific community. 🌟

Research Focus

🔬 Dr. Lei Geng’s research focuses on four key areas:

  1. Image Analysis & Understanding: Developing AI-based systems for image classification, object detection, and segmentation for industrial and medical applications.
  2. Dimensional Measurement: Applying machine vision and 3D scanning technology for high-precision industrial measurement and target positioning.
  3. Hemostatic Medical Equipment: Innovating in extracorporeal compression and intravascular interventional devices for medical bleeding control.
  4. AI in Otorhinolaryngology: Applying deep learning for disease diagnosis in ear, nose, and throat (ENT) medicine.

His work in these areas aims to integrate AI and machine vision to solve real-world problems, particularly in medical diagnostics and industrial automation. 💡

Publication Top Notes:

  • Direct May Not Be the Best: An Incremental Evolution View of Pose Generation
    • Year: 2024
    • Citations: 1
  • Multi-parametric investigations on the effects of vascular disrupting agents based on a platform of chorioallantoic membrane of chick embryos
    • Year: 2024
  • Label-Aware Dual Graph Neural Networks for Multi-Label Fundus Image Classification
    • Year: 2024
  • Cross-scale contrastive triplet networks for graph representation learning
    • Year: 2024
    • Citations: 4
  • Objective rating method for fabric pilling based on LSNet network
    • Year: 2024
    • Citations: 3

Abdul-Majeed Al-Izeri | Data Science | Best Scholar Award

Abdul-Majeed Al-Izeri | Data Science | Best Scholar Award

Dr. Abdul-Majeed Al-Izeri , Clermont Auvergne University, France.

Publication profile

Googlescholar

Education and Experience

  • 2020-2021: University degree in Data Science, University Clermont Auvergne, France. 🎓
  • 2013-2016: PhD in Mathematics (Mathematical analysis of PDEs), University Clermont Auvergne, France. 📜
  • 2011-2012: Master 2 in Mathematical Modelling (PDEs, calculation, epidemiology), University of Bordeaux, France. 💻
  • 2010-2011: Master 1 in Mathematics (Modelling, calculation, environment), University of Bordeaux, France. 📐
  • 2002-2006: BSc in Mathematics, University of Thamar, Yemen. 📘
  • October 2021-Present: Assistant Professor, Applied Mathematics, Clermont Auvergne University, France. 👩‍🏫
  • January 2018-July 2021: Postdoctoral Researcher in Epidemiology and PDEs, Clermont Auvergne University, France. 🔬
  • 2017: Postdoctoral Project in PDEs Dynamics, Clermont Auvergne University, France. 🧮
  • 2013-2016: Thesis Project in Mathematical Analysis of Population Dynamics, Blaise Pascal University, France. 🔍
  • 2012: Research Internship, Epidemic Model Study, University of Bordeaux, France. 💡
  • 2011: Project in Mathematical Modelling for Fishing Resources, University of Bordeaux, France. 🐟

Suitability For The Award

Dr. Abdul-Majeed Al-Izeri is indeed a highly suitable candidate for the Best Scholar Award based on his extensive academic qualifications, professional experience, and notable contributions to the field of Applied Mathematics and Data Science. His academic background, including a PhD in Mathematics with a specialization in Partial Differential Equations (PDEs), as well as a strong postdoctoral research profile, makes him a valuable asset in both academia and research communities.

Professional Development 

Dr. Al-Izeri has gained comprehensive skills in programming languages like Fortran, Matlab, Python, and R, along with proficiency in parallel computation using MPI. His expertise extends to using Latex and other office software for academic writing and presentations. He has been involved in several international research projects focused on applying mathematical theories to solve real-world problems in epidemiology and population dynamics. Dr. Al-Izeri’s ongoing commitment to improving his mathematical expertise and expanding his knowledge in data science and computational methods keeps him at the forefront of his field. 📊💻🔍

Research Focus 

Awards and Honors

  • 2021: Assistant Professor Appointment, Clermont Auvergne University, France. 🎓
  • 2016: PhD Completion, Mathematical Analysis of PDEs, University Clermont Auvergne. 🏆
  • 2012: Research Internship Excellence Award, University of Bordeaux. 🌟
  • 2011: Best Project in Mathematical Modelling for Resource Management, University of Bordeaux. 🏅

Publoication Top Notes

  1. On the solutions for a nonlinear boundary value problem modeling a proliferating cell population with inherited cycle length – AM Al-Izeri, K Latrach, Nonlinear Analysis: Theory, Methods & Applications 143, 1-18, Cited by 6, 2016 📘🧬
  2. Well-posedness of a nonlinear model of proliferating cell populations with inherited cycle length – ALI Abdul-Majeed, K Latrach, Acta Mathematica Scientia 36 (5), 1225-1244, Cited by 5, 2016 📊🧫
  3. Nonlinear semigroup approach to transport equations with delayed neutrons – ALI Abdul-Majeed, K Latrach, Acta Mathematica Scientia 38 (6), 1637-1654, Cited by 3, 2018 🔬⏳
  4. A nonlinear age-structured model of population dynamics with inherited properties – AM Al-Izeri, K Latrach, Mediterranean Journal of Mathematics 13, 1571-1587, Cited by 3, 2016 🌱🔢
  5. On the asymptotic spectrum of a transport operator with elastic and inelastic collision operators – AM Al-Izeri, K Latrach, Acta Mathematica Scientia 40, 805-823, Cited by 2, 2020 🔍🔄
  6. A note on fixed point theory for multivalued mappings – AM Al-Izeri, K Latrach, Fixed Point Theory 24 (1, 2023), 233-240, Cited by 1, 2023 📐📍

 

Dr. Julius Olaniyan | Machine Learning Award |Best Researcher Award

Dr. Julius Olaniyan | Machine Learning Award |Best Researcher Award

Dr. Julius Olaniyan, Bowen University, Nigeria 

Olaniyan Julius in Odo-Owa, Kwara State, Nigeria. He is a Lecturer II in the Computer Science Department at Bowen University, Iwo, Osun State, Nigeria. Julius holds a Ph.D. in Computer Science (2023) and has extensive experience in software development, data analysis, and teaching. He has worked in several institutions, including Landmark University, Federal Polytechnic Auchi, and Feghas Solutions Ltd. Over his career, he has developed various applications using programming languages such as C, C++, Java, Python, and PHP. Julius specializes in Artificial Intelligence, Computer Vision, Natural Language Processing, and Machine Translation. A devoted husband and father of three, Julius is passionate about advancing AI and its application in healthcare and education. He has contributed to several innovative research papers in the field of computer science and AI.

Professional Profile:

Google Scholar

Summary of Suitability for Award:

Dr. Olaniyan has demonstrated outstanding proficiency and expertise in the fields of Artificial Intelligence, Computer Vision, Natural Language Processing, and Machine Translation, with a solid academic background in Computer Science. He holds a Ph.D. in Computer Science from Landmark University, and has published extensively in high-impact journals and conferences. His work on cataract detection using deep learning, as well as his innovative contributions in areas like speech refinement and emotion recognition, highlights his commitment to advancing technology for real-world applications. Furthermore, his ability to collaborate across interdisciplinary research teams and contribute to several peer-reviewed articles reflects his academic rigor and leadership.

🎓Education: 

Olaniyan Julius completed his Ph.D. in Computer Science at Landmark University (2023). He also holds a Master’s in Computer Science (M.Tech) from the Federal University of Technology, Akure (2019), where he also earned a Postgraduate Diploma (PGD) in 2012. Julius started his academic journey with a Bachelor’s in Computer Science from the Federal University of Oye Ekiti (2022). His earlier qualifications include a Higher National Diploma (HND) in Computer Science from Auchi Polytechnic (2006), and a National Diploma (ND) in the same field (2000). Julius completed his Secondary Education at Orota Community High School, Odo-Owa (1994) and his Primary Education at St. Thomas Catholic School (1988). His strong educational foundation in Computer Science has shaped his successful academic and professional career.

🏢Work Experience:

Olaniyan Julius has a diverse career in academia and industry. He is currently a Lecturer II at Bowen University, Nigeria. Previously, he served as a Lecturer II at Landmark University (2023-2024) and as a Data Analyst at Federal Polytechnic Auchi (2013-2022). His industry experience includes working as a Software Developer/Business Developer at Feghas Solutions Ltd. (2009-2012) and a Tutor/Application Developer at Pesoka Systems Ltd. (2008). Julius also has teaching experience from his time as a Lecturer during his NYSC service at Maritime Academy of Nigeria (2007-2008). His early career included roles like Data Processing Officer at Ajaokuta Steel Company (2002-2004) and School Database Admin at Sani Bello Secondary School (2001). Julius’s experience spans academic teaching, research, software development, data analysis, and project management.

🏅Awards:

Olaniyan Julius has received numerous accolades throughout his academic and professional journey. His Ph.D. dissertation was highly recognized, contributing to his recognition as an emerging scholar in Computer Science. He was awarded a best student award during his time at Landmark University and has been recognized by the Federal Polytechnic Auchi for his outstanding performance as a Data Analyst. Julius’s commitment to education and research has earned him several institutional commendations for his efforts in developing AI-driven solutions in healthcare and education. His research in Artificial Intelligence and Machine Translation has garnered him recognition at international conferences. He is also an active member of several professional organizations in computer science and artificial intelligence. Julius’s leadership and contributions to academic and professional initiatives have cemented his reputation as a passionate educator and researcher.

🔬Research Focus:

Olaniyan Julius specializes in Artificial Intelligence (AI), with a focus on Computer Vision, Natural Language Processing (NLP), and Machine Translation. His work primarily involves using deep learning techniques to create solutions for healthcare (e.g., cataract detection) and education (e.g., student performance evaluation). Julius is dedicated to developing hybrid AI models that combine traditional methods with transformative learning approaches. His research in audio signal denoising and speech-to-speech translation aims to enhance communication and multilingual interaction. He is passionate about designing AI-powered systems that can automate and optimize processes, improving outcomes in health diagnostics and online learning environments. Julius’s work on emotion detection in virtual classrooms and the integration of CNN models for speech emotion recognition represents a significant contribution to the AI field. His interdisciplinary research approach holds promise for real-world AI applications in various domains.

Publication Top Notes: 

  • “Utilizing an Attention-Based LSTM Model for Detecting Sarcasm and Irony in Social Media”
  • “Implementation of Audio Signals Denoising for Perfect Speech-to-Speech Translation Using Principal Component Analysis”
  • “Advancements in Accurate Speech Emotion Recognition Through the Integration of CNN-AM Model”
  • “Transformative Transparent Hybrid Deep Learning Framework for Accurate Cataract Detection”
  • “Parallel Attention Driven Model for Student Performance Evaluation”

 

 

 

 

Dr. Kittichai Lavangnananda | Data Science Awards | Best Researcher Award

Dr. Kittichai Lavangnananda | Data Science Awards | Best Researcher Award

Dr. Kittichai Lavangnananda, University of Luxembourg, Thailand

Dr. Kittichai Lavangnananda holds a Ph.D. in Artificial Intelligence from Cardiff University, UK (1996), an M.Sc. in Computer Science from The University of Wales Cardiff, UK (1987), and a B.Sc. in Computer Science from The University of Hull, UK (1985). He currently serves as an Associate Professor at King Mongkut’s University of Technology Thonburi (KMUTT), where he also holds administrative positions as Associate Dean on Research, International Relations, and Academic Quality Assurance, and Head of Software Technology Division. His research interests include Computational Intelligence, Data Science, Evolutionary Computation, Machine Learning, Deep Learning, and Urban Planning. Kittichai has extensive international collaboration and experience in academia and technology development. 🤖

Professional Profile:

Scopus

🎓 Qualification:

Dr. Kittichai Lavangnananda is an accomplished academic with a Ph.D. in Artificial Intelligence from Cardiff University, UK (1996), complemented by an M.Sc. in Computer Science from The University of Wales Cardiff (1987), and a B.Sc. in Computer Science from The University of Hull, UK (1985). Currently serving as an Associate Professor at King Mongkut’s University of Technology Thonburi (KMUTT), he holds pivotal administrative roles including Associate Dean for Research, International Relations, and Academic Quality Assurance. Dr. Lavangnananda also heads the Software Technology Division, contributing significantly to the fields of Computational Intelligence, Data Science, Evolutionary Computation, Machine Learning, Deep Learning, and Urban Planning through his research and leadership.

👨‍🏫 Teaching Experience:

Dr. Kittichai Lavangnananda is an Associate Professor at King Mongkut’s University of Technology Thonburi (KMUTT), where he serves as the Associate Dean of Research, International Relations, and Academic Quality Assurance, and Head of the Software Technology Division. With a Ph.D. in Artificial Intelligence from Cardiff University, UK, and extensive international experience, his teaching spans key areas including Artificial Intelligence, Data Structures and Algorithms, Human-Computer Interaction, Qualitative & Model-based Reasoning, and Object-oriented programming. He brings a wealth of knowledge and practical insight to his educational role, fostering a deep understanding of complex computational concepts among his students.

🔬 Research Interests:

Dr. Kittichai Lavangnananda, Ph.D., is an Associate Professor at King Mongkut’s University of Technology Thonburi (KMUTT), where he serves as Associate Dean of Research, International Relations, and Academic Quality Assurance, and Head of the Software Technology Division. His research interests encompass Computational Intelligence, Data Science, Evolutionary Computation, Machine Learning, Deep Learning, Meta-heuristics, and Multi-Objective Optimization. With a strong background in Artificial Intelligence and extensive experience in academia and technology development, Dr. Lavangnananda contributes significantly to advancing knowledge in these fields through research, teaching, and collaborative projects both nationally and internationally.

Publication Top Notes:

  • Title: Scheduling Deep Learning Training in GPU Cluster Using the Model-Similarity-Based Policy
    • Publication Year: 2023
  • Title: Implementation of Predictive Model for Diarrhea among Afghanistan Children Based on Medical and Non-Medical Attributes
    • Publication Year: 2022
  • Title: Implementing Predictive Model for Child Mortality in Afghanistan
    • Publication Year: 2022
    • Citations: 2
  • Title: Optimization of Carsharing Fleet Placement in Round-Trip Carsharing Service
    • Publication Year: 2021
    • Citations: 7
  • Title: Application of Machine Learning in Assignment of Child Delivery Service in Afghanistan
    • Publication Year: 2021
    • Citations: 3