Axelle Hego | Data Science | Best Researcher Award

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Dr. Axelle Hego | Data Science | Best Researcher Award

Dr. Axelle Hego, University of Lorraine, France

Dr. Axelle Hego is a research engineer at the University of Lorraine, France. She specializes in model analysis, sensitivity analysis, and environmental system modeling. Her doctoral research focused on hydric models for green roof structures, exploring the influence of soil and meteorological parameters using advanced control and analysis techniques. With a strong background in Control and Complex Systems Engineering, Dr. Hego has collaborated with institutions like Cerema and contributed to international conferences and journals in the field of environmental modeling and risk assessment.

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Summary:

Dr. Axelle Hego’s research stands at the intersection of control systems and environmental modeling, with significant implications for urban ecological design. Her innovative work on dynamic hydric models for green roofs addresses key questions in soil science, water retention, and climate resilience. Though still early in her career, her technical strengths, research relevance, and international engagement make her a compelling candidate.

🎓 Education

Axelle HEGO holds an engineering degree complemented by a specialized master’s degree in Control and Complex Systems Engineering. Her academic training laid the foundation for her later doctoral research focused on hydric modeling, specifically applied to green roof structures. Her educational journey provided her with a deep understanding of control systems, dynamic models, and analytical methods suited to complex environmental systems.

💼Experience

Currently serving as a Research Engineer at CEA-Liten, Axelle brings both academic and applied research experience to her role. During her PhD, she worked closely with Cerema—a public institution under France’s Ministry for Ecological Transition and Territorial Cohesion—which provided technical expertise and experimental data crucial to her research. She is also affiliated with the CRAN (Research Center on Automatic Control of Nancy), within the department of Control, Identification, and Diagnostic. Her role has encompassed model analysis and sensitivity testing, contributing to advancements in hydric modeling for ecological infrastructure.

🔬Research Focus

Her primary research focus revolves around the analysis of hydric models adapted for green roof systems, particularly in understanding how soil properties and meteorological variables influence model behavior. Her work uniquely adapts sensitivity analysis methodologies to handle dynamic outputs, addressing uncertainties inherent in time-dependent environmental parameters. This research is of high relevance to urban sustainability and ecological engineering.

🛠️Skills

Axelle HEGO possesses specialized skills in model analysis, dynamic system modeling, and sensitivity analysis. She is proficient in adapting analytical methodologies to account for uncertainties in environmental parameters. Her expertise lies in integrating engineering control systems with environmental modeling, focusing on soil and meteorological interactions in urban green infrastructure.

🏆Awards

Axelle HEGO has been actively involved in presenting her research at international conferences. Her PhD work has resulted in two proceedings presented at conferences on Automatic Control and Modeling, as well as a dedicated presentation at a Sensitivity Analysis conference. Additionally, she has published a journal paper in the reputable Stochastic Environmental Research and Risk Assessment. She has applied for the prestigious Best Researcher Award under the International Soil Scientist Awards 2025.

📚 Publications

Title: Sensitivity analysis of a green roof model with uncertain time-varying parameter
Year: 2025
Author: Axelle Hego
Journal: Stochastic Environmental Research and Risk Assessment

Conclusion:

Dr. Axelle Hego is a suitable and promising candidate for the Best Researcher Award in the soil science domain. While her academic portfolio is still growing, her contributions demonstrate innovation, interdisciplinary insight, and a clear commitment to sustainability. With continued support and recognition, she is well-positioned to become a leading researcher in environmentally driven systems modeling.

Fatimah Hameed Naser | Data Science | Best Researcher Award

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Prof. Dr. Fatimah Hameed Naser | Data Science | Best Researcher Award

Prof. Dr. Fatimah Hameed Naser, Al-Qasim Green University, Iraq

Prof. Dr. Fatimah Hameed Naser is a distinguished professor of structural engineering at Al-Qasim Green University, Iraq. With a Ph.D. in Structural Engineering from Babylon University, her research specializes in advanced concrete technologies, fiber-reinforced polymers (FRP), finite element modeling, and sustainable construction materials. She has authored numerous peer-reviewed publications and contributed significantly to civil engineering education and innovation in Iraq.

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Summary:

Prof. Dr. Fatimah Hameed Naser is an accomplished structural engineering academic whose research is both technically rigorous and socially relevant. Her contributions to sustainable concrete materials, structural behavior modeling, and civil engineering education highlight her as a strong candidate for the Research for Best Researcher Award. She combines domain-specific knowledge with a commitment to innovation and education in Iraq’s engineering sector.

🎓 Education

Dr. Fatimah Hameed Naser Al-Mamoori holds a distinguished academic background in civil and structural engineering. She earned her Bachelor of Science in Civil Engineering in 2008 from Babylon University, Iraq. She continued her graduate studies at the same institution, completing a Master of Science in Structural Engineering in 2011. Her academic journey culminated in a Ph.D. in Structural Engineering from Babylon University in 2015, further solidifying her expertise in the field.

💼Experience

Dr. Al-Mamoori has served as a researcher and Assistant Professor in Structural Engineering at the College of Engineering, Al-Qasim Green University, Babylon, Iraq, since October 2015. Over the years, she has contributed significantly to academia through both teaching and research. Her academic role involves mentoring students, supervising research, and advancing structural engineering knowledge with a focus on innovative materials and modeling techniques.

🔬Research Focus

Her research primarily focuses on the structural behavior of concrete systems and the use of advanced materials to enhance performance. Key themes in her work include lightweight concrete reinforced with carbon fiber-reinforced polymer (CFRP) bars, the flexural and shear behavior of concrete elements, the incorporation of local materials in structural concrete, and the application of steel and carbon fibers to improve structural integrity. She also explores innovative solutions to issues like concrete behavior in hot climates, the role of industrial and waste fibers in construction, and finite element modeling for structural optimization.

🛠️Skills

Dr. Al-Mamoori possesses a strong portfolio of technical and analytical skills in structural engineering. Her expertise includes fiber-reinforced polymers (FRP), finite element analysis, structural analysis, construction techniques, and the use of finite element modeling. She is highly skilled in civil engineering materials, concrete technologies, reinforced concrete structures, and the evaluation of flexural and shear strength. Her applied knowledge spans both experimental and analytical research methodologies.

🏆Awards

Dr. Al-Mamoori is recognized for her prolific contributions to structural engineering through numerous research publications in peer-reviewed journals and international platforms. Her work has been indexed in Scopus, Publons, Google Scholar, and ResearchGate, reflecting both impact and global visibility. Although specific awards are not listed, her sustained academic and research excellence positions her as a leading researcher in structural engineering in Iraq.

📚 Publications

Title: Torsional Behavior of Concrete-Filled Steel Tubular Members: State of the Mini Art Review
Authors: Mohammed Jassim Soudi Al-Mangoshi (M.J.S.), Ali Hameed Naser Almamoori (A.H.N.), Fatimah H. Naser (F.H.)

Title: Load Capacity of RC Members Subjected to Marine Environment and Rehabilitated with FRP: State of the Art Review
Authors: Mohammed Karar Hadi (M.K.), Ali Hameed Naser Almamoori (A.H.N.), Fatimah H. Naser (F.H.)

Conclusion:

Prof. Dr. Fatimah Hameed Naser is suitable for the Research for Best Researcher Award. Her blend of academic leadership, applied research excellence, and technical innovation aligns well with the award’s objectives. With strategic enhancements in research impact visibility and international recognition, she can further solidify her standing as one of the leading researchers in her field.

Habte Tadesse LIKASSA | Data Science | Best Academic Researcher Award

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Dr. Habte Tadesse LIKASSA | Data Science | Best Academic Researcher Award

Dr. Habte Tadesse Likassa, Arizona State University, United States

Dr. Habte Tadesse Likassa is a versatile and accomplished academic researcher whose work bridges critical areas of biostatistics, medical imaging, and econometrics. He has made notable contributions to methodological innovation and has demonstrated leadership in education and research policy. His career is marked by a commitment to excellence, interdisciplinary collaboration, and applied impact.

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Summary:

Dr. Habte Tadesse Likassa is an accomplished statistician and researcher with strong credentials in applied and theoretical domains. His work is interdisciplinary, spanning healthcare, economics, and statistical methodologies, and is marked by real-world relevance and academic rigor. His leadership roles, technical skills, and international collaborations reinforce his profile as a high-potential researcher. However, strategic focus on publishing in higher-impact journals and increasing citation metrics would strengthen his global scholarly presence.

🎓 Education

Habte T. Likassa holds a PhD in Statistics from the National Taiwan University of Science and Technology, Taiwan, awarded in July 2019. His doctoral research focused on developing new robust methods for outlier and heavy sparse noise detection in high-dimensional images, earning him an A+ grade. He also holds an MSc in Statistics from Addis Ababa University, Ethiopia, where his thesis involved spatial and count regression models for analyzing tuberculosis incidence in North Shoa Zone. He earned his BSc in Statistics from the University of Gondar, Ethiopia, with a research focus on time series modeling for traffic data forecasting. Additionally, he obtained a Higher Diploma in Teaching at Higher Education from Debre Birhan University in 2013.

💼Experience

Dr. Likassa is currently serving as a Postdoctoral Research Scholar at the Department of Biostatistics, College of Health Solutions, Arizona State University, USA, since 2024. His work involves both methodological advancements in biostatistics and applied analysis using high-dimensional datasets. Previously, he held academic appointments across several Ethiopian universities including Addis Ababa University, Ambo University, and Debre Birhan University, serving in various capacities such as Assistant Professor, Lecturer, and Graduate Assistant between 2008 and 2023.

🔬Research Focus

Dr. Likassa’s research interests are diverse and interdisciplinary. His work primarily focuses on the development of robust statistical methods for medical imaging and anomaly detection in high-dimensional data. He is also engaged in survival analysis for heart failure, COVID-19, and cancer patients, as well as econometric modeling of inflation volatility using multivariate GARCH techniques. His research interests include machine learning, deep robust methods, low-rank sparse decomposition such as RPCA and Tensor RPCA, optimization techniques, artificial intelligence, and applied statistical modeling including logistic regression, multivariate analysis, spatial analysis, medical image analysis, and time series forecasting.

🛠️Skills

Dr. Likassa has extensive expertise in data management and advanced statistical modeling. His skills span big data analytics, management of economic and survey claim data, spatial exploratory data analysis, and high-dimensional health and image data analysis. He is proficient in various statistical software including LaTeX, SPSS, SAS, Stata, R, GIS, MATLAB, and Python. He has also delivered numerous training sessions to researchers, postgraduate students, and government professionals on research ethics, statistical methods, and data analysis techniques.

🏆Awards

Dr. Likassa has received several awards for his contributions to research and presentations. In 2024, he delivered a talk at the Arizona Alzheimer’s Consortium. He has received multiple Best Presenter Certificates at international conferences, including a Best Presenter Award in Taiwan, Republic of China.

📚 Publications

  • Title: A Multivariate GARCH Model with Time-Varying Correlations: What Do Inflation Data Show in Ethiopia
    Authors: Likassa, Habte Tadesse; Chen, Dinggeng; Nadarajah, Saralees; Temesgen, Shibru; Gotu, Butte
    Year: 2025
    Journal: Computational Economics

  • Title: Building a Sustainable Future: Investigating the Role and Contributions of Higher Education Institutions Instructors in Promoting Social Sustainability—Empirical Evidence from Ethiopia
    Authors: Tafese, Mestawot Beyene; Kopp, Erika; Likassa, Habte Tadesse
    Year: 2024
    Journal: Education Sciences

Conclusion:

Dr. Likassa is highly suitable for the Best Academic Researcher Award. His breadth of expertise, research innovation, and dedication to academic service make him a commendable choice. Addressing the noted areas for improvement could further enhance his candidacy, but his current achievements already position him as an impactful and deserving researcher on an international scale

Zhiyong Zhang | Data Science | Best Researcher Award

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Dr. Zhiyong Zhang | Data Science | Best Researcher Award

Dr. Zhiyong Zhang, Tianjin university of traditional Chinese medicine, China

Dr. Zhiyong Zhang is a Ph.D. candidate at Tianjin University of Traditional Chinese Medicine, China. His research focuses on the integration of modern analytical techniques and artificial intelligence to enhance quality evaluation and control in Traditional Chinese Medicine (TCM). With expertise in LC/GC-MS, ICP-MS, NIR, and LIBS, he has contributed to over 20 peer-reviewed publications, including 12 SCI-indexed papers as first or co-first author. His work advances real-time, data-driven approaches for TCM manufacturing and herbal product authentication.

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Summary:

Dr. Zhiyong Zhang is a rising star in the field of Traditional Chinese Medicine research, demonstrating excellence in combining classical medical knowledge with state-of-the-art analytical and computational techniques. His research is not only scientifically rigorous but also highly relevant to real-world applications in medicine production, safety, and quality assurance. With a growing list of impactful publications and innovative methodologies, he exemplifies the type of interdisciplinary thinker the Research for Best Researcher Award aims to recognize.

🎓 Education

Zhiyong Zhang, born in September 1997 in Huaibei, Anhui, China, is currently a Ph.D. candidate in Traditional Chinese Medicine at the Tianjin University of Traditional Chinese Medicine, under the supervision of Researcher Wenlong Li. He began his doctoral studies in September 2022. Prior to this, he participated in a joint master’s training program at the First Institute of Oceanography, Ministry of Natural Resources, from September 2021 to June 2022, where he worked with Researcher Junhui Chen. Zhang completed his Master of Science in Traditional Chinese Medicine at the Tianjin University of Traditional Chinese Medicine from September 2020 to June 2021. His academic journey began with a Bachelor of Science in Traditional Chinese Medicine Pharmaceutical at the same university, completed between 2015 and 2019.

💼Experience

Dr. Zhiyong Zhang has extensive academic and research experience in the field of Traditional Chinese Medicine (TCM). He is currently pursuing his Ph.D. at Tianjin University of Traditional Chinese Medicine, where he focuses on quality assessment and control of TCM using advanced analytical technologies and artificial intelligence. He previously participated in a joint master’s training program at the First Institute of Oceanography, Ministry of Natural Resources, where he gained interdisciplinary experience in TCM analysis and data integration. He also completed both his Master’s and Bachelor’s degrees in Traditional Chinese Medicine and Pharmaceutical Sciences at Tianjin University of Traditional Chinese Medicine. Over the years, Dr. Zhang has developed strong expertise in applying chemometrics, metabolomics, and spectroscopy-based techniques to improve the reliability and efficiency of TCM research and manufacturing.

🔬Research Focus

Zhiyong Zhang’s research centers on advancing the quality evaluation and control of Traditional Chinese Medicine (TCM) through modern analytical and computational techniques. His interests include machine learning-based quality analysis of TCM using multimodal data, rapid on-site quality control of Chinese herbal materials and processed products, and the development of multidimensional quality evaluation systems integrating metabolomics, elementalomics, and chemometrics. He also focuses on the application of Process Analytical Technology (PAT) for real-time monitoring of critical quality attributes in TCM manufacturing.

🛠️Skills

He is proficient in a wide range of analytical techniques, including Liquid/Gas Chromatography-Mass Spectrometry (LC/GC-MS), Inductively Coupled Plasma Mass Spectrometry (ICP-MS), Near-Infrared Spectroscopy (NIR), and Laser-Induced Breakdown Spectroscopy (LIBS). His expertise spans both laboratory-based and field-deployable technologies, enabling high-throughput and real-time analysis of complex herbal matrices.

🏆Awards

Zhiyong Zhang has made significant contributions to the field with over 20 peer-reviewed publications, including 12 SCI-indexed papers where he served as the first author or co-first author. He has also filed three patent applications related to his research innovations in TCM quality control and evaluation technologies.

📚 Publications

1. Journal of Food Composition and Analysis (2025)

Title: Investigating the impact of geographical origin and harvesting season on the quality of Hypericum perforatum L. using LC-MS, GC-MS, and ICP-MS technologies in conjunction with random forest model
Authors: Zhang Zhiyong, Qian Jiahe, Fang Guangpu, Chen Jingchao, Li Wenlong

2. Phytochemical Analysis (2025)

Title: A Machine Learning-Based Approach for the Prediction of Anticoagulant Activity of Hypericum perforatum L. and Evaluation of Compound Activity
Authors: Zhang Zhiyong, Nie Wennan, Zhang Yijing, Zhang Shule, Li Wenlong

Conclusion:

Dr. Zhiyong Zhang is highly suitable for the Research for Best Researcher Award. His achievements to date already place him among the most promising young researchers in the field of TCM. With continued support and opportunities to expand his global and practical influence, he is poised to make even greater contributions to science and society.

Hongchao Li | Data Science | Best Researcher Award

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Mr. Hongchao Li | Data Science | Best Researcher Award

Mr. Hongchao Li, Kunming University of Science and Technology, China

Mr. Hongchao Li is an Associate Professor at Kunming University of Science and Technology, China. He holds a Ph.D. in Rock Engineering from China University of Mining and Technology (Beijing). His research focuses on rock blasting theory and technology, including the dynamic performance of rocks and concrete, numerical simulation of blasting fragmentation damage, and controlled blasting techniques. With experience in both academia and industry, he has worked as a Project Deputy Manager at Beijing Zhongda Explosion Engineering Co., Ltd. and as an Assistant Lecturer at Kunming Industrial Vocational and Technical College. His expertise includes numerical simulation, rock mechanics, and blasting engineering.

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Summary:

Mr. Hongchao Li is a dedicated researcher with expertise in rock engineering and blasting technology. His ability to combine numerical modeling with experimental research makes him a strong candidate for the Best Researcher Award. His contributions to machine learning applications in engineering also highlight his forward-thinking approach.

🎓 Education

Li Hongchao obtained his Bachelor of Engineering degree in Mining Engineering from Kunming University of Science and Technology in 2008. He then pursued a Master of Engineering in Mining Engineering at the same institution, completing it in 2010. Continuing his academic journey, he earned a Ph.D. in Rock Engineering from China University of Mining and Technology (Beijing) in 2016.

💼Experience

Li Hongchao began his professional career as a Project Deputy Manager at Beijing Zhongda Explosion Engineering Co., Ltd. from 2010 to 2012. He then transitioned into academia, serving as an Assistant Lecturer in Mining Engineering at Kunming Industrial Vocational and Technical College from 2012 to 2013. Since 2016, he has been an Associate Professor at Kunming University of Science and Technology, School of Urban Construction, where he focuses on research and teaching related to rock blasting and engineering.

🔬Research Focus

His research primarily revolves around rock blasting theory and technology, with an emphasis on the dynamic performance and structural relationship of rocks and concrete. His work includes numerical simulation research on rock blasting fragmentation damage models and advancements in controlled blasting theory and technology.

🛠️Skills

Li Hongchao specializes in numerical simulation, rock blasting analysis, structural damage modeling, and controlled blasting techniques. His expertise extends to practical applications in the mining and construction industries, as well as academic research in rock mechanics and engineering.

🏆Awards

Li Hongchao has made significant contributions to the field of rock engineering and blasting, earning recognition for his research and professional achievements. His work has been acknowledged in both academic and industrial settings.

📚 Publications

Title: Dimensionless Machine Learning: Dimensional Analysis to Improve LSSVM and ANN Models and Predict Bearing Capacity of Circular Foundations
Author: H. Li, S.H. Hosseini, B. Gordan, J. Zhou, S. Ullah
Year: 2025
Journal: Artificial Intelligence Review

Conclusion:

Mr. Hongchao Li is a strong contender for the Best Researcher Award. However, increasing international collaborations and citation impact could further solidify his position as a leading researcher in his field.

Aqsa Zafar Abbasi | Data Science | Women Researcher Award

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Ms. Aqsa Zafar Abbasi | Data Science | Women Researcher Award

Ms. Aqsa Zafar Abbasi, Institute of Space Technology, Pakistan

Ms. Aqsa Zafar Abbasi is a PhD candidate in Mathematics at the Institute of Space Technology, Pakistan, specializing in group theory, cryptography, and mathematical modeling. Her research focuses on the parametric exploration of homomorphisms of modular groups for finite generalized triangle groups, with applications in image encryption, substitution box design, and neural network-based cryptographic security. With six years of teaching experience, she has served as a visiting lecturer at multiple institutions, teaching courses in differential equations, discrete mathematics, graph theory, and engineering mathematics. She has published extensively in high-impact journals, contributing to research in cryptography, fuzzy algebra, and numerical simulations. Aqsa is proficient in MATLAB, Python, R, and computational intelligence techniques, making her a dedicated researcher in the fields of mathematics and data security.

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Summary:

Ms. Aqsa Zafar Abbasi is an exceptional researcher in mathematical cryptography, data security, and computational mathematics. Her significant contributions to encryption techniques, strong publication record, and interdisciplinary expertise make her a strong candidate for the Research for Women Researcher Award. While she already has an impressive academic and research background, expanding collaborations, engaging in industry applications, and securing research funding could further elevate her contributions.

 

🎓 Education

Aqsa Zafar Abbasi is currently pursuing a PhD in Mathematics at the Institute of Space Technology, Islamabad, Pakistan, with an expected completion date in February 2025. Her research focuses on the parametric exploration of homomorphisms of modular groups for finite generalized triangle groups, with applications in cryptography and neural network-based encryption. She holds an MS in Mathematics from the same institution, completed in 2021, where she explored algebraic characteristics of bipolar-valued fuzzy subgroups and their applications in decision-making and S-box analysis. She also earned an MSc in Mathematics from PMAS Arid Agriculture University, Rawalpindi, with an excellent academic record.

 

💼Experience

With six years of teaching experience, Aqsa has served as a visiting lecturer at prestigious institutions, including Pir Mehr Ali Shah Arid Agriculture University, National Defence University, Shaheed Zulfiqar Ali Bhutto Institute of Science and Technology (SZABIST), and the Institute of Space Technology, Islamabad. She has taught differential equations, discrete mathematics, graph theory, real analysis, linear algebra, and engineering mathematics to students in mathematics, software engineering, and computer science programs.

 

🔬Research Focus

Aqsa’s research expertise includes group theory, cryptography, algebraic geometry, numerical solutions of PDEs, and machine learning applications in mathematical modeling. She specializes in highly secure substitution box construction for encryption, particularly for image encryption and watermarking, using parameterized homomorphisms of modular groups. Additionally, she integrates neural networks with encryption schemes to enhance data security. Her research also extends to bipolar-valued fuzzy set theory, focusing on its applications in decision-making and cryptographic analysis.

Awards

Aqsa has gained recognition for her contributions to cryptography, algebraic structures, and numerical analysis, with publications in renowned scientific journals. Her research on mathematical modeling and encryption techniques has positioned her as a dedicated scholar in her field.

Skills

Aqsa possesses a diverse skill set, including mathematical modeling, computational intelligence, programming (C++, Python, MATLAB, R, Wolfram Mathematica), research writing, editing, and proofreading. She is also skilled in seminar organization, event management, leadership, and teamwork, making her a well-rounded academic professional.

 

Publications

  • Publication: A digital audio data protection method using parametric action of generalised triangle group on GF(28)
    Authors: A.Z. Abbasi (Aqsa Zafar Abbasi), A. Rafiq (Ayesha Rafiq), B.M. Alshammari (Badr Mesned)
    Journal: Ain Shams Engineering Journal
    Year: 2025

 

Conclusion:

Ms. Aqsa Zafar Abbasi is a highly qualified and deserving candidate for the Research for Women Researcher Award. Her expertise in mathematical cryptography, interdisciplinary research, and teaching makes her a valuable asset to the academic community. With continued research, international collaborations, and industry engagement, she has the potential to make even greater contributions to her field.

Diana Feliciano | Science Integration | Best Scholar Award

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Prof. Dr. Diana Feliciano | Science Integration | Best Scholar Award

Prof. Dr. Diana Feliciano, Teesside University, United Kingdom

Prof. Dr. Diana Feliciano is a Professor of Climate Change and Sustainable Economic Development at Teesside University, United Kingdom. She holds a PhD in Geography from the University of Aberdeen, an MSc in Economics from the Portuguese Catholic University, and a BEng Hons in Engineering from the University of Lisbon. Her research focuses on climate change mitigation, sustainable land use, carbon sequestration, and agricultural policy. With extensive experience in academia and policy advisory roles, she has worked with institutions like the Committee on Climate Change, UNESCO, and the University of Aberdeen. She has secured prestigious research grants from UKRI, EU Horizon Europe, and the Wellcome Trust, leading projects on greenhouse gas emissions, sustainable food systems, and environmental policy integration.

Profile

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Summary:

Prof. Dr. Diana Feliciano is a highly accomplished researcher in climate change and sustainability, with extensive contributions to academia, policy, and global environmental initiatives. Her ability to secure competitive funding, collaborate internationally, and influence policy decisions makes her a strong candidate for the Research for Best Scholar Award.

 

🎓 Education

Professor Diana Feliciano holds a PhD in Geography from the University of Aberdeen, Scotland, where she researched the contribution of rural land uses to greenhouse gas-neutral regions. She earned an MSc in Economics from the Portuguese Catholic University, focusing on the effectiveness of forest owners’ associations in Portugal. She also holds a BEng Hons in Engineering, specializing in forestry and natural resource management, from the University of Lisbon.

💼Experience

Professor Feliciano is currently a Professor of Climate Change and Sustainable Economic Development at Teesside University International Business School. She is also a Defra R&D Fellow working on embedding evidence in the Environmental Improvement Plan. Previously, she was a transdisciplinary scientist at the University of Aberdeen, a senior analyst for the Committee on Climate Change in London, and a researcher at UNESCO’s International Social Science Council in Paris. She has also worked as a research assistant and teaching assistant in Portugal and Scotland.

🔬Research Focus

Her research spans climate change mitigation, sustainable land use, and socio-economic aspects of environmental policy. She has extensively studied carbon sequestration, greenhouse gas emissions, and sustainable agricultural practices. Her work integrates economic and environmental sciences to develop policies supporting climate resilience, sustainable food systems, and land-use management.

Awards

She has secured numerous prestigious grants, including funding from UKRI, EU Horizon Europe, Wellcome Trust, and the World Bank. She has led and participated in projects on carbon capture, sustainable food systems, and agricultural policy. She has also held leadership roles in international research collaborations, including COST Action FP1201 and NERC-funded projects.

Publications

Environmental, Social and Economic Perceptions of Local Food Production: A Case Study of Aberdeenshire Farmers’ Markets

Authors: Wardle, J.M., Sorathia, A., Smith, P., & Feliciano, D.M.S.
Year: 2024
Citations: 1
Journal: Scottish Geographical Journal

Assessing the Area of Suitable Land for Climate Change Mitigation with Sitka Spruce (Picea sitchensis) in Scotland

Authors: Abimbola, I., & Feliciano, D.M.S.
Year: 2022
Citations: 1
Journal: Land

Stakeholders’ Perceptions of Factors Influencing Climate Change Risk in a Central America Hotspot

Authors: Feliciano, D.M.S., & Sobenes, A.
Year: 2022
Citations: 6
Journal: Regional Environmental Change

 

Conclusion:

Prof. Dr. Diana Feliciano is highly suitable for the Research for Best Scholar Award, given her exceptional academic achievements, research impact, and policy contributions. While she could further enhance her influence through increased citations, high-impact publications, and expanded public engagement, her current standing in the scientific community makes her a strong contender for this prestigious recognition.