Beata Naumnik | Data Science | Best Researcher Award

Published on by Math Scientist

Prof. Beata Naumnik | Data Science | Best Researcher Award

Medical University of Bialystok, Poland

Prof. Beata Naumnik is a highly accomplished nephrologist and transplant specialist whose career reflects exceptional contributions to medical science, research, and education. As Head of the Department of Nephrology and Transplantation with Dialysis Unit at the Medical University of Bialystok, she has advanced pioneering studies in chronic kidney disease, dialysis, and post-transplantation management. She has authored over 200 publications and book chapters, with her research presented at leading international congresses including ASN, ERA-EDTA, and ISN. Her leadership extends beyond academia as an organizer of major scientific conferences, editorial board member, mentor for Ph.D. scholars, and active participant in national and international medical societies. Through her dedication to research excellence, patient care, and global collaboration, Prof. Naumnik continues to play a transformative role in shaping the future of nephrology.

Professional Profile

Scopus Profile | ORCID Profile 

Education

Prof. Beata Naumnik pursued her medical studies at the Faculty of Medicine, Medical University of Bialystok, graduating with honors and later completing her Ph.D. in medical sciences at the same institution. She specialized in internal medicine, nephrology, and clinical transplantology, establishing strong academic and clinical expertise. Her habilitation and professorship further consolidated her academic standing, enabling her to take leadership roles in both teaching and research. Over the years, she has combined academic excellence with professional training, equipping herself with deep insights into nephrology and transplantation medicine. As an educator, she has lectured across multiple faculties, supervised doctoral and specialist training programs, and contributed to coursebooks. Her academic foundation is marked by dedication, innovation, and excellence, reflecting her commitment to advancing nephrology, transplantation, and patient-centered medical education.

Experience

Prof. Beata Naumnik’s professional journey reflects a rich blend of clinical practice, academic leadership, and organizational achievements. She began her career in nephrology practice and steadily advanced into academic positions, eventually becoming Head of the 1st Department of Nephrology and Transplantation with Dialysis Unit at the Medical University of Bialystok. Her teaching experience spans medical, dentistry, dietetics, and pharmaceutical faculties, where she prepared examination sessions, coordinated curricula, and supervised specialist training. She has also played significant roles in state examination commissions, quality of education committees, and university governance boards. In parallel, she has organized numerous national and international conferences, chaired scientific committees, and developed specialized dialysis monitoring systems. Through these roles, she has demonstrated exceptional experience in research, teaching, clinical practice, and organizational leadership within the medical and academic community.

Research Interest

Prof. Beata Naumnik’s research interests are deeply rooted in nephrology, chronic kidney disease, dialysis, and transplantation medicine. Her work explores endothelial dysfunction in chronic kidney disease, mineral bone disorders in renal failure, peritoneal dialysis monitoring, and post-transplantation complications such as viral infections. She has investigated the effects of heparins on endothelial markers, coagulation pathways, and growth factors, linking them to cardiovascular complications in renal patients. A major part of her research has focused on donor-specific antibodies and their impact on transplantation outcomes, advancing clinical approaches to long-term graft survival. Her dedication to innovative methodologies has enabled better diagnostic and therapeutic strategies for kidney patients. By bridging clinical care with scientific discovery, she has established herself as a leading voice in advancing nephrology and improving patient outcomes globally.

Awards and Honors

Prof. Beata Naumnik’s remarkable contributions have been recognized through numerous awards and honors in academia and medical research. She has received prestigious scientific awards for her groundbreaking studies on endothelial dysfunction and heparin effects in renal failure, as well as multiple academic and didactic excellence awards from her university. Her recognition extends internationally, with prizes for outstanding oral presentations at major nephrology congresses. Additionally, she has been consistently acknowledged for her collaborative projects, mentorship, and contributions to advancing medical education. Her leadership roles within professional societies and her influence on nephrology practice have further reinforced her reputation as a distinguished researcher and educator. These honors underscore her sustained commitment to research innovation, clinical excellence, and knowledge dissemination, reflecting her profound impact on nephrology and medical sciences worldwide.

Research Skill

Prof. Beata Naumnik possesses exceptional research skills spanning experimental design, clinical trial leadership, and international collaboration. She has successfully led multiple research grants and projects investigating dialysis, transplantation, and vascular complications, often partnering with leading European and Asian research institutions. With more than 200 publications in high-impact journals, she demonstrates expertise in scientific writing, data analysis, and translational research. She has served as reviewer for internationally recognized journals including the Journal of the American Society of Nephrology and Nephrology Dialysis Transplantation, reflecting her critical scientific evaluation skills. Her editorial roles in nephrology-focused journals highlight her leadership in shaping research directions. Additionally, her ability to mentor doctoral students and specialists demonstrates her capacity to transfer research skills to future generations, ensuring long-term contributions to nephrology and medical science.

Publication Top Notes

  • Title: iFGF23:cFGF23 Ratio Is a Questionable Diagnostic Marker for Distinguishing Between Acute and Chronic Kidney Disease
    Authors: Joanna Szczykowska-Miller; Tomasz Hryszko; Ewa Koc-Żórawska; Beata Naumnik
    Year: 2025
    Citation: International Journal of Molecular Sciences, 26(16), 7952. DOI: 10.3390/ijms26167952

  • Title: C-terminal and intact FGF23 in critical illness and their associations with acute kidney injury and in-hospital mortality
    Authors: K. Rygasiewicz; T. Hryszko; A. Siemiatkowski; S. Brzosko; A. Rydzewska-Rosolowska; B. Naumnik
    Year: 2018
    Citation: Cytokine, 111: 44–50. DOI: 10.1016/j.cyto.2017.12.024

  • Title: Age and gender predict OPG level and OPG/sRANKL ratio in maintenance hemodialysis patients
    Authors: Beata Naumnik; K. Klejna; E. Koc-Zórawska; M. Myśliwiec
    Year: 2013
    Citation: Advances in Medical Sciences, 58(2): 292–297. DOI: 10.2478/ams-2013-0026

  • Title: Comparison of Post-Transplantation Lymphoproliferative Disorder Risk and Prognostic Factors between Kidney and Liver Transplant Recipients
    Authors: Krzysztof Mucha; Rafał Staros; Bartosz Foroncewicz; Bogna Ziarkiewicz-Wróblewska; Maciej Kosieradzki; Sławomir Nazarewski; Beata Naumnik; Joanna Raszeja-Wyszomirska; Krzysztof Zieniewicz; Leszek Pączek
    Year: 2022
    Citation: Cancers, 14(8): 1953. DOI: 10.3390/cancers14081953

  • Title: Clinicopathologic correlations of renal pathology in the adult population of Poland
    Authors: A. Perkowska-Ptasinska; A. Bartczak; M. Wagrowska-Danilewicz; A. Halon; K. Okon; A. Wozniak; M. Danilewicz; H. Karkoszka; A. Marszałek; J. Kowalewska; B. Naumnik et al.
    Year: 2017
    Citation: Nephrology Dialysis Transplantation, 32(suppl_2): ii192–ii200. DOI: 10.1093/ndt/gfw365

  • Title: Factors Influencing Longevity of Humoral Response to SARS-CoV-2 Vaccination in Patients with End Stage Kidney Disease Receiving Renal Replacement Therapy
    Authors: Irena Glowinska; Barbara Labij-Reduta; Jerzy Juzwiuk; Magdalena Lukaszewicz; Adam Pietruczuk; Agata Poplawska; Anna Daniluk-Jamro; Katarzyna Kakareko; Alicja Rydzewska-Rosolowska; Beata Naumnik et al.
    Year: 2022
    Citation: Journal of Clinical Medicine, 11(17): 4984. DOI: 10.3390/jcm11174984

  • Title: Prognostic value of osteoprotegerin and sRANKL in bronchoalveolar lavage fluid of patients with advanced non-small cell lung cancer
    Authors: W. Naumnik; I. Płońska; M. Ossolińska; J. Nikliński; B. Naumnik
    Year: 2018
    Citation: Advances in Experimental Medicine and Biology, vol 1021: 47–56. DOI: 10.1007/5584_2017_111

  • Title: The effect of nephrectomy on Klotho, FGF-23 and bone metabolism
    Authors: Katarzyna Kakareko; Alicja Rydzewska-Rosolowska; S. Brzosko; J. Gozdzikiewicz-Lapinska; E. Koc-Zorawska; P. Samocik; R. Kozlowski; M. Mysliwiec; B. Naumnik; T. Hryszko
    Year: 2017
    Citation: International Urology and Nephrology, 49(9): 1653–1661. DOI: 10.1007/s11255-017-1519-9

  • Title: Unexpected and striking effect of heparin-free dialysis on cytokine release
    Authors: A. Rydzewska-Rosolowska; J. Gozdzikiewicz-Lapinska; J. Borawski; E. Koc-Zorawska; M. Mysliwiec; B. Naumnik
    Year: 2017
    Citation: International Urology and Nephrology, 49(6): 1117–1125. DOI: 10.1007/s11255-017-1589-8

  • Title: Different effects of enoxaparin, nadroparin, and dalteparin on plasma TFPI during hemodialysis: A prospective crossover randomized study
    Authors: Beata Naumnik; Alicja Rydzewska-Rosolowska; M. Myśliwiec
    Year: 2011
    Citation: Clinical and Applied Thrombosis/Hemostasis, 17(6): 612–618. DOI: 10.1177/1076029610376936

Conclusion

Prof. Beata Naumnik’s career stands as a model of excellence in medical research, education, and leadership. Her education, extensive experience, and pioneering research have advanced the understanding of kidney disease, dialysis, and transplantation, making a lasting impact on patient care and scientific development. Recognized with national and international honors, she has consistently demonstrated her ability to translate research into meaningful clinical outcomes. Her strong record of publications, editorial contributions, and leadership within professional societies underscores her influence on the global nephrology community. With a proven history of innovation, collaboration, and mentorship, she exemplifies the qualities of a world-class researcher. Prof. Naumnik’s ongoing dedication ensures her continued contributions to scientific progress, medical education, and patient well-being, making her a truly deserving candidate for recognition at the highest level.

 

Seho Lee | Data Science | Best Researcher Award

Published on by Math Scientist

Prof. Seho Lee | Data Science | Best Researcher Award

Assistant Professor at University of Ulsan, South Korea

Dr. Seho Lee, Assistant Professor in the Department of AI Convergence, is a distinguished researcher specializing in neuroengineering, brain–computer interfaces (BCI), and clinical artificial intelligence. He earned his Ph.D. in Brain and Cognitive Engineering from Korea University, following advanced degrees in biomedical engineering and electrophysics. His research focuses on advanced neurophysiological signal analysis, AI-based clinical decision support, and predictive modeling for neurological disorders. Dr. Lee has played key roles in multiple international, grant-funded projects and has published extensively in high-impact journals, including IEEE and Frontiers in Neuroscience. Holding several patents in BCI and biomedical AI, he is also an active member of professional bodies like IEEE. With a strong commitment to innovation, interdisciplinary collaboration, and mentorship, Dr. Lee continues to advance technologies that bridge engineering and clinical applications for global impact.

Professional Profile

Google Scholar | Scopus Profile | ORCID Profile

Education

Dr. Seho Lee holds a Ph.D. in Brain and Cognitive Engineering from Korea University, where he specialized in advanced neurophysiological signal processing and AI applications in neuroscience. He earned his Master’s degree in Biomedical Engineering from Hanyang University, focusing on biomedical signal analysis and neural interface technologies. His academic journey began with a Bachelor’s degree in Electrophysics from Kwangwoon University, where he developed a strong foundation in physics and electronics. This diverse educational background has enabled Dr. Lee to integrate engineering, computer science, and neuroscience in his research. His training at leading Korean institutions provided both theoretical depth and practical expertise, positioning him to contribute meaningfully to the rapidly evolving fields of neuroengineering, artificial intelligence, and clinical technology innovation at both national and global levels.

Experience

Dr. Lee currently serves as an Assistant Professor in the Department of AI Convergence, where he leads research at the intersection of neuroscience, artificial intelligence, and clinical applications. He has been a key contributor to multiple multi-year, grant-funded projects, collaborating with hospitals, research institutes, and industry partners. His work spans developing brain–computer interface (BCI) systems, AI-powered clinical decision support tools, and predictive models for neurological disorder progression. Dr. Lee’s experience includes managing large datasets, integrating wearable and invasive neural monitoring technologies, and designing patient-centric solutions. His portfolio also features active involvement in interdisciplinary teams, student supervision, and community-driven scientific initiatives. Through his extensive project work and academic contributions, he has developed a global research perspective while ensuring his innovations address practical, real-world needs in healthcare and rehabilitation technologies.

Research Interest

Dr. Lee’s research interests focus on neuroengineering, brain–computer interfaces (BCI), clinical artificial intelligence, and neuroscience applications for patient rehabilitation. He specializes in advanced analysis of continuously measured neurophysiological signals, quantitative brain network modeling, and AI-driven diagnostic tools. His work aims to create practical solutions for individuals with neurological impairments by enhancing brain–machine communication and predictive clinical analytics. Key topics include the use of AI for clinical data interpretation, development of real-time decision support systems, and non-invasive neural stimulation methods. Dr. Lee is also deeply engaged in studying pathological progression in neurological disorders, with the goal of early intervention. His multidisciplinary approach combines engineering, cognitive science, and medicine, contributing to breakthroughs that directly improve patient quality of life and expand the capabilities of modern neurotechnology.

Award and Honor

While building his academic career, Dr. Lee has earned recognition through successful participation in competitive, nationally funded research projects and prestigious institutional appointments. His innovations in brain–computer interface technology and AI-based biomedical systems have resulted in multiple patents in Korea and the United States, marking him as a thought leader in his domain. He has been invited to present at leading IEEE conferences, demonstrating peer acknowledgment of his contributions. His publications in high-impact journals further attest to his research excellence. The combination of competitive grant awards, impactful publications, and translational research outcomes underscores Dr. Lee’s professional standing. These achievements not only highlight his expertise but also his commitment to advancing science with tangible applications, making him a strong candidate for distinguished research recognitions and honors.

Research Skill

Dr. Lee possesses a comprehensive set of research skills spanning AI model development, neurophysiological data acquisition and analysis, brain network modeling, and clinical signal interpretation. He is adept in programming, machine learning, and deep learning techniques applied to healthcare data, including EEG, EMG, and imaging modalities. His expertise extends to designing and implementing both hardware and software components for brain–computer interfaces, ensuring reliability and usability in clinical environments. Dr. Lee is skilled in statistical modeling, biomedical signal preprocessing, and data visualization for translational research. He has extensive experience collaborating across disciplines, managing international research collaborations, and guiding graduate students in advanced projects. Combined with his patent-proven innovation capabilities, these skills enable him to transform theoretical concepts into impactful neuroengineering solutions that address pressing healthcare challenges.

Publication Top Notes

  • Title: Improved prediction of bimanual movements by a two-staged (effector-then-trajectory) decoder with epidural ECoG in nonhuman primates
    Authors: H Choi, J Lee, J Park, S Lee, K Ahn, IY Kim, KM Lee, DP Jang
    Year: 2018
    Citations: 26

  • Title: Physicochemical factors that affect electroporation of lung cancer and normal cell lines
    Authors: HB Kim, S Lee, Y Shen, PD Ryu, Y Lee, JH Chung, CK Sung, KY Baik
    Year: 2019
    Citations: 24

  • Title: Effects of actin cytoskeleton disruption on electroporation in vitro
    Authors: HB Kim, S Lee, JH Chung, SN Kim, CK Sung, KY Baik
    Year: 2020
    Citations: 19

  • Title: Importance of reliable EEG data in motor imagery classification: Attention level-based approach
    Authors: S Lee, YT Kim, SO Hwang, H Kim, DJ Kim
    Year: 2020
    Citations: 7

  • Title: Long-term evaluation and feasibility study of the insulated screw electrode for ECoG recording
    Authors: H Choi, S Lee, J Lee, K Min, S Lim, J Park, K Ahn, IY Kim, KM Lee
    Year: 2018
    Citations: 6

  • Title: Decoding saccadic directions using epidural ECoG in non-human primates
    Authors: J Lee, H Choi, S Lee, BH Cho, K Ahn, IY Kim, KM Lee, DP Jang
    Year: 2017
    Citations: 6

  • Title: Reduced burden of individual calibration process in brain–computer interface by clustering the subjects based on brain activation
    Authors: YT Kim, S Lee, H Kim, SB Lee, SW Lee, DJ Kim
    Year: 2019
    Citations: 4

  • Title: Right hemisphere lateralization in neural connectivity within fronto-parietal networks in non-human primates during a visual reaching task
    Authors: J Lee, H Choi, K Min, S Lee, KH Ahn, HJ Jo, IY Kim, DP Jang, KM Lee
    Year: 2018
    Citations: 3

  • Title: Investigating the effect of mindfulness training for stress management in military training: the relationship between the autonomic nervous system and emotional regulation
    Authors: S Lee, JH Kim, H Kim, SH Kim, SS Park, CW Hong, KT Kwon, SH Lee
    Year: 2025
    Citations: 2

  • Title: Effects of altered functional connectivity on motor imagery brain–computer interfaces based on the laterality of paralysis in hemiplegia patients
    Authors: S Lee, H Kim, JB Kim, DJ Kim
    Year: 2023
    Citations: 2

  • Title: Classification of the motion artifacts in near-infrared spectroscopy based on wavelet statistical feature
    Authors: SB Lee, H Kim, S Lee, HJ Kim, SW Lee, DJ Kim
    Year: 2019
    Citations: 2

  • Title: Heart rate variability as a preictal marker for determining the laterality of seizure onset zone in frontal lobe epilepsy
    Authors: S Lee, H Kim, JH Kim, M So, JB Kim, DJ Kim
    Year: 2024

Conclusion

Dr. Seho Lee represents the next generation of innovators at the convergence of neuroscience, artificial intelligence, and clinical technology. His unique blend of academic excellence, research experience, and practical innovation has positioned him to make transformative contributions to healthcare and rehabilitation sciences. With numerous high-impact publications, patents, and international collaborations, he has demonstrated the ability to move ideas from concept to clinical reality. His work directly improves the lives of individuals with neurological disorders while advancing the scientific understanding of brain–machine interaction. As both a leader and mentor, Dr. Lee continues to inspire new research directions in neuroengineering. His commitment to interdisciplinary collaboration, societal impact, and global engagement makes him an exemplary figure deserving of recognition as a top researcher in his field.

Shaohuai Feng | Data Science | Best Researcher Award | 2350

Published on by Math Scientist

Dr. Shaohuai Feng | Data Science | Best Researcher Award

Student at Feng CGSS, China

Feng Shaohuai is a dedicated researcher focused on sustainable development 🌍 and carbon neutrality 🌱. His work explores how industrial systems, environmental policies, and technological innovation can drive the low-carbon transition, particularly in emerging economies. Through interdisciplinary approaches, Feng bridges academic research with practical solutions to address global climate challenges. His projects, such as sustainable industrial transformation and data-driven environmental policy models, offer actionable frameworks for achieving long-term sustainability goals 🌿. With a commitment to policy implementation, his research informs industry and government decision-making. Feng’s recent publications in top journals reflect his expertise in environmental governance and low-carbon industrial policies. Despite his impressive academic contributions, there is room for expansion in industry partnerships, patents, and editorial roles 📚. Feng is a rising star in his field, bringing impactful, real-world solutions to pressing global issues and advancing the sustainability agenda 🌟.

Professional Profile

Scopus Profile

Education 🎓

Feng Shaohuai’s academic journey is rooted in the study of sustainability and carbon neutrality 🌍. He holds degrees specializing in environmental governance and low-carbon technologies 🌱, which have shaped his expertise in addressing global climate issues. His education provides a deep understanding of sustainable development challenges, particularly in the context of developing economies 🌏. Feng’s studies have focused on green innovation, energy efficiency, and policy frameworks that support the transition to a low-carbon future 🔋. This educational background enables him to merge theory with practice, crafting real-world solutions that align with global climate goals 🌐. Through his learning, Feng has honed interdisciplinary skills to create strategies that foster sustainability across various sectors, positioning him as a key figure in the field of environmental research 🔬.

Professional Experience 💼

Feng Shaohuai currently serves as a researcher at Universiti Sains Malaysia, where he focuses on sustainable industrial transformation and energy efficiency ⚙️. His professional work bridges the gap between policy, data, and technology, creating practical solutions for sustainable development 🌍. Feng leads projects that develop low-carbon industrial policies and green innovation strategies, aiming to transform industries and promote sustainability in emerging economies 🌱. His role enables him to work with governments, academia, and industry leaders to drive global sustainability agendas. Through his interdisciplinary approach, Feng has made valuable contributions to carbon neutrality and energy efficiency, ensuring that his research delivers real-world impact in the fight against climate change 🌡️.

Research Interest 🔬

Feng Shaohuai’s research is dedicated to carbon neutrality, low-carbon industrial policies, and sustainable development 🌱. He explores the intersection of technological innovation, environmental governance, and market mechanisms to develop solutions that address global sustainability challenges 🌍. His focus is on how data-driven environmental policies can enhance decision-making and improve energy efficiency 🔋. Feng also investigates strategies for sustainable industrial transformation, particularly in developing economies, to foster green innovation and reduce carbon footprints 🌳. His interdisciplinary research combines policy, technology, and industry, aiming to create actionable solutions for global climate goals 🌏. Through this work, Feng seeks to accelerate the transition to a low-carbon future and promote environmental sustainability across sectors 🌐.

Awards and Honors 🏆

While Feng Shaohuai has yet to receive major formal awards, his research has earned recognition in the field of sustainability and carbon neutrality 🌿. His articles in respected journals like Resources Policy and Energy Strategy Reviews showcase his growing influence in the academic world 📚. Feng’s work on low-carbon industrial transformation and environmental policies has contributed to advancing sustainable development goals 🌏. Though not yet awarded, his published research and interdisciplinary approach are a testament to his expertise and potential for future recognition 🌟. As his work continues to influence the fields of green innovation and sustainable development, Feng is well-positioned to receive accolades for his contributions to the low-carbon transition and global climate solutions 🌱.

Conclusion 🌟

Feng Shaohuai is an emerging leader in sustainability research, focusing on carbon neutrality, green innovation, and low-carbon industrial policies 🌿. His academic background and professional expertise enable him to bridge the gap between policy, data, and technology, driving impactful solutions for global sustainability 🌍. Feng’s research on sustainable industrial transformation and energy efficiency plays a pivotal role in shaping strategies that support carbon neutrality and environmental governance 🌱. Through his interdisciplinary approach, Feng is actively contributing to the global shift toward low-carbon futures 🌏. As he continues to collaborate with governments, industries, and researchers, Feng’s work will accelerate climate goals and contribute to a sustainable and green world 🌳.

Publications Top Notes

Unlocking the potential of natural resources, fintech and fiscal policy for carbon neutrality; evidence from N-11 nations

  • Authors: Shaohuai Feng, Mohd Wira Mohd Shafiei, Theam Foo Ng, Jie Ren

  • Year: November 2024

  • Source: Resources Policy 🌍

The intersection of economic growth and environmental sustainability in China: Pathways to achieving SDG

  • Authors: Shaohuai Feng, Mohd Wira Mohd Shafiei, Theam Foo Ng, Yefeng Jiang

  • Year: September 2024

  • Citations: 9 📚

  • Source: Energy Strategy Reviews ⚡

 

Iliyas Khan | Statistics | Best Researcher Award

Published on by Math Scientist

Dr. Iliyas Khan | Statistics | Best Researcher Award

Teaching Assistance at Universiti Teknologi PETRONAS, Malaysia

Dr. Iliyas Karim Khan is a dedicated researcher specializing in machine learning, statistical modeling, forecasting, and big data analysis. He holds a Ph.D. from Universiti Teknologi PETRONAS (UTP), Malaysia, along with advanced degrees in statistics from Peshawar University, Pakistan. With a strong publication record in Q1 journals, his research focuses on optimizing clustering algorithms, particularly in K-means clustering and data science applications. His expertise extends to programming and statistical tools such as Python, SPSS, Stata, and EViews. Dr. Khan has gained extensive teaching experience, serving as a Teaching Assistant at UTP and a Subject Specialist in Pakistan. He was recognized with a Publication Recognition Achievement (2024) at UTP, underscoring his research contributions. His work is instrumental in improving data-driven decision-making and computational efficiency, making him a valuable asset in the academic and research community. His commitment to innovation and education positions him as a promising leader in his field.

Professional Profile 

Google Scholar
Scopus Profile

Education

Dr. Iliyas Karim Khan has a strong academic background in statistics and data science. He earned his Ph.D. in 2024 from Universiti Teknologi PETRONAS (UTP), Malaysia, focusing on optimizing machine learning algorithms. Prior to that, he completed an M.Phil. (2016) and M.Sc. (2014) in Statistics from Peshawar University, Pakistan, and a B.Sc. in Statistics (2012) from SBBU Sheringhal, Upper Dir, Pakistan. His foundational studies in science and engineering were completed at BISE Peshawar, along with a B.Ed. (2015) for pedagogical training. His educational journey reflects his commitment to advanced research in big data analysis, forecasting, and statistical modeling. Throughout his studies, he has demonstrated exceptional analytical skills, contributing to high-impact research in data clustering and computational efficiency. His academic achievements have positioned him as a promising researcher in the field of machine learning and statistical analytics, making significant contributions to data science methodologies.

Professional Experience

Dr. Iliyas Karim Khan has gained extensive teaching and research experience across multiple institutions. He worked as a Teaching Assistant at Universiti Teknologi PETRONAS (UTP), Malaysia, where he was actively involved in data science research and statistical analysis. In Pakistan, he served as a Subject Specialist at GHSS Bang Chitral for four years, strengthening his expertise in applied statistics and data analysis. His teaching career also includes one year at Abbottabad University of Science and Technology, where he mentored students in statistical modeling and machine learning techniques. Additionally, he completed an internship at the University of Peshawar and taught at Darban Degree College, Chitral. His experience encompasses curriculum development, student mentoring, and advanced research in statistical computing, making him an accomplished educator and researcher. His hands-on expertise in Python, SPSS, Stata, and EViews further enhances his ability to train future data scientists and statisticians.

Research Interest

Dr. Iliyas Karim Khan’s research revolves around machine learning, big data analytics, statistical modeling, and forecasting. His primary focus is on clustering algorithms, particularly enhancing the K-means clustering method for improved efficiency and accuracy. His work addresses key challenges in data science, such as non-spherical data, outlier handling, and optimal cluster selection, which have significant implications for AI-driven decision-making. Additionally, he explores computational time optimization and statistical accuracy in clustering techniques, contributing to the advancement of data-driven methodologies. His studies extend to forecasting models, applied statistical techniques, and real-world big data applications. Through numerous Q1 journal publications, he has proposed innovative solutions for refining data science models. His research is highly relevant in industries reliant on machine learning, artificial intelligence, and predictive analytics, positioning him as a key contributor to the evolution of data-centric technologies and computational intelligence.

Awards and Honors

Dr. Iliyas Karim Khan’s academic excellence and research contributions have been recognized through prestigious accolades. In 2024, he received the “Publication Recognition Achievement” award from Universiti Teknologi PETRONAS (UTP), Malaysia, honoring his impactful research in machine learning and statistical analysis. His Q1 journal publications in high-impact journals demonstrate his ability to produce innovative and widely acknowledged research. Additionally, his contributions to data clustering and computational efficiency have been well-received within the academic and research communities. His work on addressing K-means clustering limitations and enhancing algorithmic efficiency has been cited extensively, highlighting its significance in data science and artificial intelligence. His growing recognition in machine learning and big data analytics marks him as a promising scholar in his field. Through his research, he continues to make valuable contributions that shape the future of data-driven decision-making and statistical computing.

Conclusion

Dr. Iliyas Karim Khan is an exceptional researcher, educator, and innovator in the field of machine learning, statistical modeling, and big data analysis. His strong academic background, extensive teaching experience, and high-impact research make him a significant contributor to computational intelligence and data science advancements. His studies on enhancing K-means clustering efficiency, outlier handling, and computational time optimization have added valuable insights to the field. Through prestigious publications and academic honors, he has demonstrated his expertise in refining statistical methodologies for real-world applications. His proficiency in Python, SPSS, Stata, and advanced statistical techniques enables him to bridge the gap between theoretical advancements and practical applications in data science. As he continues to explore new frontiers in machine learning and predictive analytics, his work is expected to have a lasting impact on data-driven industries and AI-based decision-making systems.

Publications Top Noted

  • Title: Determining the Optimal Number of Clusters by Enhanced Gap Statistic in K-Mean Algorithm
    Authors: Iliyas Karim Khan, HB Daud, NB Zainuddin, R Sokkalingam, M Farooq, ME Baig, …
    Year: 2024
    Citations: 7
    Source: Egyptian Informatics Journal, Volume 27, Article 100504

  • Title: Numerical Solution of Heat Equation Using Modified Cubic B-Spline Collocation Method
    Authors: M Iqbal, N Zainuddin, H Daud, R Kanan, R Jusoh, A Ullah, Iliyas Karim Khan
    Year: 2024
    Citations: 3
    Source: Journal of Advanced Research in Numerical Heat Transfer, Volume 20, Pages 23-35

  • Title: Numerical Solution by Kernelized Rank Order Distance (KROD) for Non-Spherical Data Conversion to Spherical Data
    Authors: Iliyas Karim Khan, HB Daud, R Sokkalingam, NB Zainuddin, A Abdussamad, …
    Year: 2024
    Citations: 2
    Source: AIP Conference Proceedings, Volume 3123 (1)

  • Title: A Modified Basis of Cubic B-Spline with Free Parameter for Linear Second Order Boundary Value Problems: Application to Engineering Problems
    Authors: M Iqbal, N Zainuddin, H Daud, R Kanan, H Soomro, R Jusoh, A Ullah, …
    Year: 2024
    Citations: 1
    Source: Journal of King Saud University-Science, Volume 36 (9), Article 103397

  • Title: Standardizing Reference Data in Gap Statistic for Selection of Optimal Number of Clusters in K-Means Algorithm
    Authors: Iliyas Karim Khan, H Daud, N Zainuddin, R Sokkalingam
    Year: 2025
    Source: Alexandria Engineering Journal, Volume 118, Pages 246-260

  • Title: A Hybrid Stacked Sparse Autoencoder (HSSAE) Model for Predicting Type 2 Diabetes
    Authors: A Abdussamad, H Daud, R Sokkalingam, M Zubair, Iliyas Karim Khan, Z Mahmood
    Year: 2025
    Source: To be published

  • Title: A Mini Review of the State-of-the-Art Development in Oil Recovery Under the Influence of Geometries in Nanoflood
    Authors: M Zafar, H Sakidin, A Hussain, M Sheremet, I Dzulkarnain, R Safdar, …
    Year: 2024
    Source: Journal of Advanced Research in Micro and Nano Engineering, Volume 26 (1), Pages 83-101

  • Title: Exploring K-Means Clustering Efficiency: Accuracy and Computational Time Across Multiple Datasets
    Authors: Iliyas Karim Khan, H Daud, N Zainuddin, R Sokkalingam, A Abdussamad, AS Azad, …
    Year: 2024
    Source: Journal of Advanced Research in Applied Sciences and Engineering Technology

  • Title: Forecasting the Southeast Asian Currencies Against the British Pound Sterling Using Probability Distributions
    Authors: Iliyas Karim Khan, Ahmad Abubakar Suleiman, Hanita Daud, Mahmod Othman, Abdullah …
    Year: 2023
    Source: Data Science Insights, Volume 1 (1), Pages 31-51

  • Title: Addressing Limitations of the K-Means Clustering Algorithm: Outliers, Non-Spherical Data, and Optimal Cluster Selection
    Authors: Iliyas Karim Khan, Abdussamad, Abdul Museeb, Inayat Agha
    Year: 2024
    Citations: 4
    Source: AIMS Mathematics, Volume 9, Pages 25070-25097

 

 

Sandipan Mondal | Data Science | Young Scientist Award

Published on by Math Scientist

Dr. Sandipan Mondal | Data Science | Young Scientist Award

Post Doctoral Researcher & Adjunct Assistant Professor at National Taiwan Ocean University, India

Dr. Sandipan Mondal is a Post-Doctoral Researcher and Adjunct Assistant Professor at the National Taiwan Ocean University, specializing in fisheries oceanography, climate change effects, species distribution modeling, and marine ecosystem dynamics. His expertise spans fish feeding ecology, taxonomic identification, stable isotope analysis, and fishing gear technology. With a strong research background, he has contributed significantly to habitat modeling and the impact of climate variability on fisheries in the Indian Ocean and Taiwan Strait. Dr. Mondal has an impressive publication record in top-tier journals and has received accolades such as the Young Academician Award and a research grant from the National Science and Technology Council of Taiwan. His ability to integrate advanced computational techniques, machine learning models, and remote sensing in ecological research sets him apart. A dedicated scientist committed to environmental sustainability, he actively collaborates on interdisciplinary projects and participates in academic awards, driving impactful contributions to marine and fishery sciences.

Professional Profile 

Google Scholar
Scopus Profile

Education

Dr. Sandipan Mondal holds a Ph.D. in Fisheries Resource Management from ICAR-Central Institute of Fisheries Education, India. His doctoral research focused on the impact of climate variability on fisheries and marine ecosystems, integrating statistical and computational approaches. Prior to this, he earned a Master’s degree in Fisheries Science with a specialization in Fisheries Resource Management, where he developed expertise in species distribution modeling and fish population dynamics. He also holds a Bachelor’s degree in Fisheries Science, which laid the foundation for his knowledge in aquaculture, fish biology, and marine ecology. His academic journey has been marked by rigorous training in advanced data analysis, remote sensing applications in fisheries, and ecological modeling. Throughout his education, he actively participated in research projects, workshops, and field studies, refining his skills in experimental design and marine biodiversity assessment. His strong academic background and multidisciplinary expertise have enabled him to contribute significantly to fisheries and marine research.

Professional Experience

Dr. Sandipan Mondal is currently a Post-Doctoral Researcher and Adjunct Assistant Professor at the National Taiwan Ocean University. In this role, he conducts research on fisheries oceanography, climate change impacts, and ecosystem-based fisheries management. He has extensive experience in species distribution modeling, stable isotope analysis, and fish feeding ecology, contributing to marine conservation and sustainable fisheries management. Before this, he worked as a Research Associate at ICAR-Central Institute of Fisheries Education, where he engaged in projects related to fisheries stock assessment, climate resilience, and marine habitat modeling. He has also collaborated with international research teams on machine learning applications in ecological studies. Additionally, he has served as a mentor and guest lecturer, sharing his expertise in fisheries science, oceanography, and statistical modeling. His professional journey reflects a strong commitment to interdisciplinary research, academic mentorship, and practical applications of fisheries and marine ecosystem studies.

Research Interest

Dr. Sandipan Mondal’s research interests focus on fisheries oceanography, marine ecosystem modeling, and the impact of climate change on aquatic biodiversity. He specializes in species distribution modeling, habitat suitability analysis, and the use of remote sensing and GIS in fisheries research. His work integrates machine learning techniques and advanced statistical approaches to predict fish population dynamics and assess marine environmental changes. He is particularly interested in the trophic interactions of marine species, stable isotope applications in food web studies, and the sustainability of fisheries resources under changing climatic conditions. His research extends to the development of fishing gear technology, ecological niche modeling, and conservation strategies for commercially important fish species. By combining computational tools and field-based studies, he aims to contribute to sustainable fisheries management and marine biodiversity conservation. His interdisciplinary approach enables him to address complex challenges in fisheries science and oceanographic research.

Awards and Honors

Dr. Sandipan Mondal has received several prestigious awards and honors in recognition of his outstanding contributions to fisheries and marine sciences. He was honored with the Young Academician Award for his groundbreaking research in fisheries oceanography and climate change impacts. He has also been awarded a research grant by the National Science and Technology Council of Taiwan, supporting his innovative work in species distribution modeling and marine ecosystem dynamics. His academic excellence has been acknowledged through multiple best paper and presentation awards at international awards. Additionally, he has been a recipient of merit-based scholarships and fellowships during his academic journey. His commitment to research and innovation has positioned him as a leading expert in fisheries resource management. These accolades reflect his dedication to advancing marine science and his continuous pursuit of solutions for sustainable fisheries and environmental conservation.

Conclusion

Dr. Sandipan Mondal is a dedicated marine scientist whose expertise in fisheries oceanography, climate change impacts, and ecosystem modeling has significantly contributed to the field of fisheries and marine research. His strong academic background, combined with extensive research experience, has allowed him to integrate advanced computational tools and ecological theories to address critical challenges in fisheries management. Through his interdisciplinary approach, he has made notable contributions to marine conservation, sustainable fisheries practices, and climate adaptation strategies. His work has been recognized through numerous awards, grants, and publications in high-impact journals. Beyond research, he is actively involved in academic mentorship and collaborative projects, driving innovation and knowledge exchange in the scientific community. With a passion for environmental sustainability and marine biodiversity conservation, Dr. Mondal continues to explore new frontiers in fisheries science, aiming to bridge the gap between research and practical applications for the benefit of global aquatic ecosystems.

Publications Top Noted

1.

  • Title: Habitat suitability modeling for the feeding ground of immature albacore in the southern Indian Ocean using satellite-derived sea surface temperature and chlorophyll data
  • Authors: S Mondal, AH Vayghan, MA Lee, YC Wang, B Semedi
  • Year: 2021
  • Citations: 26
  • Source: Remote Sensing 13 (14), 2669

2.

3.

  • Title: Long-term observations of sea surface temperature variability in the Gulf of Mannar
  • Authors: S Mondal, MA Lee
  • Year: 2023
  • Citations: 10
  • Source: Journal of Marine Science and Engineering 11 (1), 102

4.

  • Title: Seasonal distribution patterns of Scomberomorus commerson in the Taiwan Strait in relation to oceanographic conditions: An ensemble modeling approach
  • Authors: S Mondal, MA Lee, JS Weng, KE Osuka, YK Chen, A Ray
  • Year: 2023
  • Citations: 9
  • Source: Marine Pollution Bulletin 197, 115733

5.

  • Title: Ensemble modeling of black pomfret (Parastromateus niger) habitat in the Taiwan Strait based on oceanographic variables
  • Authors: S Mondal, MA Lee, YK Chen, YC Wang
  • Year: 2023
  • Citations: 9
  • Source: PeerJ 11, e14990

6.

  • Title: Habitat modeling of mature albacore (Thunnus alalunga) tuna in the Indian Ocean
  • Authors: S Mondal, MA Lee
  • Year: 2023
  • Citations: 8
  • Source: Frontiers in Marine Science 10, 1258535

7.

8.

  • Title: Ensemble three-dimensional habitat modeling of Indian Ocean immature albacore tuna (Thunnus alalunga) using remote sensing data
  • Authors: S Mondal, YC Wang, MA Lee, JS Weng, BK Mondal
  • Year: 2022
  • Citations: 8
  • Source: Remote Sensing 14 (20), 5278

9.

  • Title: Long-term variation of sea surface temperature in relation to sea level pressure and surface wind speed in the southern Indian Ocean
  • Authors: S Mondal, MA Lee, YC Wang, B Semedi
  • Year: 2022
  • Citations: 7
  • Source: Journal of Marine Science and Technology 29 (6), 784-793

10.

  • Title: Changes in properties of polyamide netting materials exposed to different environments
  • Authors: S Mondal, SN Thomas, B Manoj Kumar
  • Year: 2019
  • Citations: 7
  • Source: J Fish Res. 2019; 3 (2): 1-3. J Fish Res 2019 Volume 3 Issue 2

11.

  • Title: Impact of climatic oscillations on marlin catch rates of Taiwanese long-line vessels in the Indian Ocean
  • Authors: S Mondal, A Ray, KE Osuka, RI Sihombing, MA Lee, YK Chen
  • Year: 2023
  • Citations: 6
  • Source: Scientific Reports 13 (1), 22438

12.

  • Title: Detecting the feeding habitat zone of albacore tuna (Thunnus alalunga) in the southern Indian Ocean using multisatellite remote sensing data
  • Authors: S Mondal, YC Lan, MA Lee, YC Wang, B Semedi, WY Su
  • Year: 2022
  • Citations: 5
  • Source: Journal of Marine Science and Technology 29 (6), 794-807

13.

  • Title: Habitat modelling of escolar fish (Lepidocybium flavobrunneum, Smith 1843) in the southwestern Indian Ocean using remote sensing data
  • Authors: RI Sihombing, A Ray, S Mondal, MA Lee
  • Year: 2024
  • Citations: 4
  • Source: International Journal of Remote Sensing 45 (23), 8722-8741

14.

15.

  • Title: Fishery-based adaptation to climate change: The case of migratory species flathead grey mullet (Mugil cephalus L.) in Taiwan Strait, Northwestern Pacific
  • Authors: MA Lee, S Mondal, SY Teng, ML Nguyen, P Lin, JH Wu, BK Mondal
  • Year: 2023
  • Citations: 4
  • Source: PeerJ 11, e15788

16.

  • Title: Distribution patterns of grey mullet in the Taiwan Strait in relation to oceanographic conditions
  • Authors: SY Teng, S Mondal, QH Lu, P Lin, MA Lee, LG Korowi
  • Year: 2024
  • Citations: 2
  • Source: Journal of Marine Science and Engineering 12 (4), 648

17.

  • Title: Modeling of swordtip squid (Uroteuthis edulis) monthly habitat preference using remote sensing environmental data and climate indices
  • Authors: A Haghi Vayghan, A Ray, S Mondal, MA Lee
  • Year: 2024
  • Citations: 2
  • Source: Frontiers in Marine Science 11, 1329254

18.

  • Title: Total catch variability in the coastal waters of Taiwan in relation to climatic oscillations and possible impacts
  • Authors: MA Lee, S Mondal, JH Wu, M Boas
  • Year: 2022
  • Citations: 2
  • Source: Journal of Taiwan Fisheries Society 49 (2), 127-143

19.

  • Title: Cyclic variation in fishing catch rates influenced by climatic variability in the waters around Taiwan
  • Authors: MA Lee, S Mondal, JH Wu, YH Huang, M Boas
  • Year: 2022
  • Citations: 2
  • Source: Journal of Taiwan Fisheries Society 49 (2), 113-125

20.

  • Title: The influence of sea surface temperature on the distribution of albacore tuna (Thunnus alalunga) in the southern Indian Ocean
  • Authors: S Mondal, MA Lee
  • Year: 2018
  • Citations: 1
  • Source: Journal of Fisheries Society Taiwan 45 (4), 253-260

Meichen Feng | Data Science | Best Researcher Award

Published on by Math Scientist

Prof. Meichen Feng | Data Science | Best Researcher Award

Professor at Shanxi Agricultural University, China.

Feng Meichen is a distinguished professor at Shanxi Agricultural University, specializing in crop ecology, precision agriculture, and agricultural information technology. As the Deputy Dean of the College of Agriculture, she has led 22 research projects, authored 82 SCI/Scopus-indexed papers, and secured 18 patents, demonstrating a strong commitment to advancing sustainable agriculture. With 988 citations and an H-index of 19, her work has significantly impacted agricultural innovation and technology. She has published 5 books, contributed to multiple academic committees, and serves on the editorial boards of leading agricultural journals. Her research focuses on improving crop yield, resource efficiency, and environmental sustainability, benefiting both academia and local farming communities. While her expertise is well-recognized in China, expanding global collaborations could further enhance her research impact. With a remarkable career in agricultural research and innovation, Feng Meichen is an outstanding candidate for the Best Researcher Award.

Professional Profile 

Scopus Profile
ORCID Profile

Education

Feng Meichen holds an advanced degree in agriculture and crop ecology, equipping her with a deep understanding of agricultural information technology, precision farming, and ecological sustainability. Her academic journey has been dedicated to exploring innovative agricultural techniques that improve productivity while ensuring environmental sustainability. Through extensive research and continuous professional development, she has gained expertise in 3S technology (GIS, GPS, and remote sensing) and its application in modern agriculture. Her education has provided a strong foundation for her contributions to precision agriculture, crop management, and smart farming technologies. With a commitment to advancing agricultural science, she has successfully integrated academic knowledge with practical applications, benefiting both researchers and farming communities. Her ability to translate theoretical concepts into real-world solutions has made her a recognized leader in the field of crop science and agricultural technology.

Professional Experience

As a Professor and Deputy Dean at the College of Agriculture, Shanxi Agricultural University, Feng Meichen has established herself as a leader in agricultural research and education. She has successfully led 22 major research projects, contributing to advancements in crop ecology, precision farming, and smart agriculture. Her expertise extends beyond academia, as she actively collaborates with government agencies, research institutions, and industry leaders to develop sustainable farming practices. She has authored 82 peer-reviewed journal articles, secured 18 patents, and published 5 books, showcasing her multidisciplinary expertise. Additionally, she serves on the editorial boards of prestigious agricultural journals, including the Journal of Smart Agriculture and Shanxi Agricultural Sciences. She is also a member of multiple professional committees, influencing agricultural policies and research directions in China. Her extensive academic, research, and administrative experience highlights her dedication to advancing agricultural science and technology for long-term sustainability.

Research Interests

Feng Meichen’s research focuses on crop ecology, precision agriculture, and agricultural information technology, with an emphasis on sustainable and smart farming solutions. She integrates 3S technology (GIS, GPS, remote sensing) with crop production models to enhance agricultural efficiency, resource management, and environmental conservation. Her work aims to optimize crop yield, reduce environmental impact, and improve agricultural decision-making processes. She is particularly interested in applying artificial intelligence and big data analytics to develop predictive models for crop health monitoring and precision irrigation systems. Her research extends to organic dryland agriculture, where she explores climate-resilient farming techniques. By collaborating with industry experts, policymakers, and farmers, she ensures that her research findings have practical applications that benefit the agricultural sector. Her commitment to advancing smart agriculture technologies positions her as a pioneering researcher in the field of modern agriculture.

Awards and Honors

Feng Meichen has received multiple awards and recognitions for her outstanding contributions to agricultural science and research. As a Deputy Chief Expert in the Shanxi Modern Agricultural Specialty Grain Industry Technology System, she has played a pivotal role in shaping agricultural policies and technologies. Her patents and scientific contributions have earned her recognition at national and provincial levels. She has been honored by Shanxi Agricultural University and various academic organizations for her contributions to precision farming, agricultural technology development, and ecological sustainability. She is a member of several prestigious agricultural committees, including the China Modern Agriculture Graduate School and the Chinese Society of Crops. Through her active involvement in academic and industry collaborations, she continues to make a lasting impact on the agricultural sector. Her dedication to agricultural innovation and sustainability has established her as a leading researcher and academician.

Conclusion

Feng Meichen is a highly accomplished researcher, academic leader, and innovator in agricultural science. With extensive research contributions, patents, and leadership roles, she has significantly advanced the fields of crop ecology, precision agriculture, and smart farming technologies. Her work has not only improved crop productivity and resource efficiency but also contributed to sustainable farming practices that benefit both academic research and practical applications. While her impact is widely recognized in China, expanding international collaborations and industry partnerships could further elevate her global research influence. Her dedication to scientific excellence, innovation, and sustainability makes her an outstanding candidate for the Best Researcher Award.

Publications Top Noted

2025 Publications

🔹 Evaluating the Potential of Airborne Hyperspectral Imagery in Monitoring Common Beans with Common Bacterial Blight at Different Infection Stages

  • Authors: Binghan Jing, Jiachen Wang, Xin Zhang, Xiaoxiang Hou, Kunming Huang, Qianyu Wang, Yiwei Wang, Yaoxuan Jia, Meichen Feng, Wude Yang et al.
  • Year: 2025
  • DOI: 10.1016/j.biosystemseng.2025.02.002
  • Source: Biosystems Engineering (Crossref)

🔹 Potential Impacts of Climate Change on the Spatial Distribution Pattern of Naked Oats in China

  • Authors: Zhenwei Yang, Xujing Yang, Yuheng Huang, Yalin Zhang, Yao Guo, Meichen Feng, Mingxing Qin, Ning Jin, Muhammad Amjad, Chao Wang et al.
  • Year: 2025
  • DOI: 10.3390/agronomy15020362
  • Source: Agronomy (Crossref)

2024 Publications

🔹 A Model for the Detection of β-Glucan Content in Oat Grain Based on Near Infrared Spectroscopy

  • Authors: Yang Z., Cheng Z., Su P., Wang C., Qin M., Song X., Xiao L., Yang W., Feng M., Zhang M.
  • Year: 2024
  • DOI: 10.1016/j.jfca.2024.106105
  • Source: Journal of Food Composition and Analysis (Scopus – Elsevier)

🔹 Combined Use of Spectral Resampling and Machine Learning Algorithms to Estimate Soybean Leaf Chlorophyll

  • Authors: Gao C., Li H., Wang J., Zhang X., Huang K., Song X., Yang W., Feng M., Xiao L., Zhao Y. et al.
  • Year: 2024
  • DOI: 10.1016/j.compag.2024.108675
  • Source: Computers and Electronics in Agriculture (Scopus – Elsevier)

🔹 Efficient Prediction of SOC and Aggregate OC Components by Continuous Wavelet Transform Spectra Under Different Feature Selection Methods

  • Authors: Yang S., Wang Z., Ji C., Hao Y., Liang Z., Yan X., Qiao X., Feng M., Xiao L., Song X. et al.
  • Year: 2024
  • DOI: 10.1016/j.compag.2023.108550
  • Source: Computers and Electronics in Agriculture (Scopus – Elsevier)

🔹 Prediction of the Potential Distribution and Analysis of the Freezing Injury Risk of Winter Wheat on the Loess Plateau Under Climate Change

  • Authors: Qing Liang, Xujing Yang, Yuheng Huang, Zhenwei Yang, Meichen Feng, Mingxing Qing, Chao Wang, Wude Yang, Zhigang Wang, Meijun Zhang et al.
  • Year: 2024
  • Source: Journal of Integrative Agriculture

2023 Publications

🔹 AMF Inoculation Positively Regulates Soil Microbial Activity and Drought Tolerance of Oat

  • Authors: Li Y., Li L., Zhang B., Lü Y.-F., Feng M.-C., Wang C., Song X.-Y., Yang W.-D., Zhang M.-J.
  • Year: 2023
  • DOI: 10.11674/zwyf.2022561
  • Source: Journal of Plant Nutrition and Fertilizers (Scopus – Elsevier)

🔹 Analyzing Protein Concentration from Intact Wheat Caryopsis Using Hyperspectral Reflectance

  • Authors: Zhang X., Hou X., Su Y., Yan X., Qiao X., Yang W., Feng M., Kong H., Zhang Z., Shafiq F. et al.
  • Year: 2023
  • DOI: 10.21203/rs.3.rs-2887647/v1
  • Source: Research Square

🔹 Hyperspectral Monitoring of Growth and Physiology Parameters of Winter Wheat Based on Different Quantification Methods

  • Authors: Wang Z.-G., Yang S., Feng M.-C., Yang W.-D., Liang Q., Yang X.-J., Yan X.-B., Sun X.-K., Qin M.-X., Wang C. et al.
  • Year: 2023
  • DOI: 10.2139/ssrn.4535833
  • Source: SSRN

🔹 Identification of Structural Variations Related to Drought Tolerance in Wheat (Triticum aestivum L.)

  • Authors: Zhao J., Li X., Qiao L., Zheng X., Wu B., Guo M., Feng M., Qi Z., Yang W., Zheng J.
  • Year: 2023
  • DOI: 10.1007/s00122-023-04283-4
  • Source: Theoretical and Applied Genetics (Scopus – Elsevier)