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

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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

 

 

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

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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. Bechoo Lal | Data Science Awards | Best Researcher Award

Dr. Bechoo Lal | Data Science Awards | Best Researcher Award

Dr. Bechoo Lal, KLEF – KL University Vijayawada Campus Andhra Pradesh, India

Dr. Bechoo Lal is a distinguished academic with a diverse educational background, holding a PhD in Computer Science and Information Systems from the University of Mumbai, India. He also earned a Master’s in Computer Applications from Banaras Hindu University, UP, India, a Master of Technology in Computer Science Engineering from AAI-Deemed University, Allahabad, India, and a PGP in Data Science from Purdue University, USA. With over two decades of teaching experience, Dr. Lal has served in various roles, including Assistant Professor at Western College, University of Mumbai, and Lecturer at JPG College, Purvanchal University, India. His research interests in Machine Learning, Data Science, and Big Data Analytics drive his passion for predictive modeling and enhancing data analysis accuracy. Dr. Lal has also contributed extensively to academic governance and program development, reflecting his commitment to education and research excellence.

Professional Profile:

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Scopus

📚 Academic Qualifications:

Dr. Lal holds a diverse academic background, including a PhD in Computer Science and Information Systems from University of Mumbai, India, and a Master’s in Computer Applications from Banaras Hindu University, UP, India. He also completed a Master of Technology in Computer Science Engineering from AAI-Deemed University, Allahabad, India, and a PGP in Data Science from Purdue University, USA.

🔬 Research and Teaching Interests:

His primary research interests encompass Machine Learning, Data Science, and Big Data Analytics. Dr. Lal is passionate about exploring predictive modeling using machine learning techniques and enhancing accuracy in data analysis.

👨‍🏫 Teaching Experience:

With over two decades of teaching experience, Dr. Lal has served as an Assistant Professor at Western College, University of Mumbai, and as a Lecturer at JPG College, Purvanchal University, India. He has also contributed to IGNOU’s BCA/MCA programs as a Counsellor.

🎓 Academic and Administrative Roles:

Dr. Lal has taken on various administrative roles, including Co-coordinator and Examination Chairperson at Western College, University of Mumbai. He has supervised numerous research projects at SJJT University, India, and contributed significantly to academic governance and program development.

Publication Top Notes:

  • Title: Improving migration forecasting for transitory foreign tourists using an Ensemble DNN-LSTM model
    • Journal: Entertainment Computing
    • Year: 2024
  • Title: Using social networking evidence to examine the impact of environmental factors on social Followings: An innovative Machine learning method
    • Journal: Entertainment Computing
    • Year: 2024
  • Title: Real-Time Convolutional Neural Networks for Emotion and Gender Classification
    • Conference: Procedia Computer Science
    • Year: 2024
  • Title: Identification of Brain Diseases using Image Classification: A Deep Learning Approach
    • Conference: Procedia Computer Science
    • Year: 2024
  • Title: Fake News Detection Using Transfer Learning
    • Conference: Communications in Computer and Information Science
    • Year: 2024

 

 

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

 

 

Mr. Yan hui Wu | Machine Learning Awards | Best Researcher Award

Mr. Yan hui Wu | Machine Learning Awards | Best Researcher Award

Mr. Yan hui Wu , Hebei University of Engineering , China

Yanhui Wu is a Senior Engineer at the School of Mining and Surveying Engineering, Hebei University of Engineering. He completed his Ph.D. in Geophysical Exploration and Information Technology at the China University of Mining and Technology (Beijing) in 2023. He also holds an M.Sc. in the same field from the China University of Geosciences (Beijing) and a B.Sc. in Computer Science and Technology from Hebei University of Technology. Wu’s career includes nearly a decade at the Geological Geophysical Center, Hebei Coal Science Research Institute, Jizhong Energy Group, where he served as a Senior Engineer. He has participated in significant research projects, including the Ministry of Science and Technology’s National Key R&D Program on dynamic intelligent detection technology for hidden disaster geological factors in coal mines. Wu’s research has been published in several renowned journals, with notable works on seismic multiattribute machine learning, fault evaluation, and collapse column prediction in coal strata.

Professional Profile:

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 🎓Education:

Yanhui Wu holds a Ph.D. in Geophysical Exploration and Information Technology from the China University of Mining and Technology (Beijing), which he completed in June 2023. He also earned an M.Sc. in the same field from the China University of Geosciences (Beijing) in June 2010. Additionally, Wu has a B.Sc. in Computer Science and Technology from Hebei University of Technology, which he obtained in June 2007.

 🏢Work Experience:

Yanhui Wu currently serves as a Senior Engineer at the School of Mining and Surveying Engineering, Hebei University of Engineering. Prior to this role, he held a Senior Engineer position at the Geological Geophysical Center of Hebei Coal Science Research Institute, part of the Jizhong Energy Group, from August 2010 to July 2019.

Publication Top Notes:

  • Application of seismic multiattribute machine learning to determine coal strata thickness
    • Published Year: 2021
    • Journal: Journal of Geophysics and Engineering
    • Cited by: 834-844
  • Quantitative Evaluation of Faults by Combined Channel Wave Seismic Transmission-Reflection Detection Method
    • Published Year: 2022
    • Journal: Minerals
    • Cited by: 1022-1032
  • Precise prediction of the collapse column based on channel wave spectral disparity characteristics and velocity tomography imaging
    • Published Year: 2022
    • Journal: Journal of Geophysics and Engineering
    • Cited by: 326-335
  • Application research of combined detection of transmission and reflection slot waves for small structures—Taking Longquan Mining Area in Shanxi as an example
    • Published Year: 2021
    • Journal: Progress in Geophysics
    • Cited by: 1325-1332