Camille Charette | Information Science | Best Researcher Award

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Ms. Camille Charette | Information Science | Best Researcher Award

California State Polytechnic University, Humboldt Library | United States

Camille Charette, MA, MLIS is an interdisciplinary researcher and emerging scholar in library and information science whose work bridges the fields of information retrieval, human–AI interaction, critical information literacy, and inclusive pedagogy. With a strong foundation in philosophy, literature, and information science, she focuses on creating accessible, user-centered information environments that promote equity, inclusion, and ethical engagement in digital ecosystems. Her academic and professional practice reflect a decade of experience in applied and theoretical research, instructional design, and the development of open educational resources that support diverse learners and communities. Camille’s research integrates human-centered design, critical theory, and evidence-based methodologies to examine how evolving technologies influence access to information and participation in knowledge systems. As a graduate researcher and instructor at San José State University’s School of Information, she has co-developed the Human-Centered Artificial Intelligence Certificate program, designed courses such as Responsible Human-AI Interaction and Introduction to Human-Centered Artificial Intelligence, and collaborated on the American Library Association’s eLearning Advanced eCourse Introduction to AI. Her contributions extend to authoring curricular materials, designing accessibility-first learning environments, and conducting user research to enhance digital literacy and usability. Through her work on projects such as Design Concepts in Information Retrieval: Creating User-Centered Systems, Search Engines, and Sites, she advances the understanding of how human values, learning psychology, and inclusive design shape information technologies. Camille’s commitment to critical information literacy and equitable learning underscores her vision of a future where digital systems and educational practices are both socially responsible and human-centered.

Profile: Orcid 

Featured Publications:

Micheal Arowolo | Machine Learning | Best Researcher Award

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Dr. Micheal Arowolo | Machine Learning | Best Researcher Award

Assistant Professor | Xavier University of Louisiana | United States

Dr. Micheal Olaolu Arowolo is an accomplished scholar, researcher, and educator in the field of computer science, with expertise in machine learning, health informatics, and bioinformatics. He currently serves as an Assistant Professor of Health Informatics at Xavier University of Louisiana, where he teaches master’s students in areas such as population health, statistics in health sciences, and healthcare quality. He earned his Ph.D. in Computer Science from Landmark University in Nigeria, building on a Master’s degree in Computer Science from Kwara State University and a Bachelor’s degree from Al-Hikmah University. He later advanced his academic career as a Post-doctoral Research Scholar at the University of Missouri’s Bond Life Sciences Center, where he contributed to the development of deep learning and machine learning models aimed at predicting relevant gene names in pathway figures for health practitioners. Dr. Arowolo’s teaching and research experience spans institutions in both the United States and Nigeria, where he has lectured and supervised students across a broad range of subjects, including artificial intelligence, data communication and networking, object-oriented programming, and computational theory. His research efforts have produced impactful publications in reputable journals indexed by Elsevier, IEEE, ISI, and Web of Science. He has also developed applied solutions for the United Nations Sustainable Development Goals, particularly SDG 11, by applying machine learning models to domains such as healthcare, telecommunications, and banking. His contributions to academic excellence helped Landmark University improve its global ranking significantly. An active member of the global research community, Dr. Arowolo belongs to several professional organizations, including IEEE, ACM, ISCB, and IAENG. He also serves as a reviewer and editorial board member for internationally recognized journals such as Heliyon, IEEE Access, and Journal of Big Data. His dedication to academic mentorship is reflected in his supervision of numerous graduate and undergraduate projects, guiding students to adopt innovative approaches to machine learning and computational methods. Recognized among the top 500 scholars in Nigeria by SciVal-Scopus, Dr. Arowolo has received certifications in SQL, Linux, Oracle, project management, and network administration. Through a blend of research, teaching, and leadership, he continues to contribute to knowledge creation, innovation, and the advancement of computational science and health informatics worldwide.

Profile:  Scopus | ORCID | Google Scholar

Featured Publications:

Arowolo, M. O., & co-authors. (n.d.). Enhancing cyber threat detection with an improved artificial neural network model. Data Science and Management.

Arowolo, M. O., & co-authors. (n.d.). Computational intelligence in big data analytics. In Book chapter.

Arowolo, M. O., & co-authors. (n.d.). A comprehensive evaluation of large language models in mining gene relations and pathway knowledge. Quantitative Biology.

Arowolo, M. O., & co-authors. (n.d.). Internet of things (IoT): Concepts, protocols, and applications. In Book chapter.

Arowolo, M. O., & co-authors. (n.d.). Adsorptive removal of synthetic food dyes using low-cost biochar: Efficiency prediction, kinetics and desorption index evaluation. Bioresource Technology Reports.

Arowolo, M. O., & co-authors. (n.d.). Gene name recognition in gene pathway figures using Siamese networks. In Conference proceedings.

Arowolo, M. O., & co-authors. (n.d.). Enhancing healthcare data security: An intrusion detection system for web applications with SVM and decision tree algorithms.

Tatiana Solovey | Deep Learning | Best Researcher Award

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Prof. Tatiana Solovey | Deep Learning | Best Researcher Award

Polish Geological Institute | Poland

Dr. Tatiana Solovey is a Polish hydrogeologist and Associate Professor at the Polish Geological Institute – National Research Institute. With over two decades of academic and research experience, she has specialized in groundwater hydrology, environmental geology, and sustainable water resource management. She began her career as an Assistant Lecturer and later Assistant Professor at Chernivtsi National University, Ukraine, before moving to Poland, where she advanced from Senior Researcher to Head of the Department of Hydrogeology. Her international collaborations span internships and research stays in Latvia, Estonia, Norway, Ukraine, and the United States. A dedicated educator and mentor, she has taught hydrogeology, environmental monitoring, and water resource assessment, while also supervising young researchers in European-funded projects. Dr. Solovey is widely recognized for her contributions to transboundary groundwater management and the use of satellite data for hydrological monitoring. She also serves as editor for several leading geoscience journals.

Professional Profile

Scopus

Education

Tatiana Solovey holds advanced degrees in geography and Earth sciences with a specialization in hydrology. She earned her M.Sc. in Geography with a focus on Hydrology from Chernivtsi National University, Ukraine, followed by a Ph.D. in Earth and Environmental Sciences from the same university. Building on this foundation, she achieved her habilitation in Earth and Environmental Sciences (Hydrology) at Taras Shevchenko National University of Kyiv, a credential later nostrified at Nicolaus Copernicus University in Toruń, Poland. Throughout her academic journey, she enriched her expertise through international research internships, including at Taras Shevchenko National University of Kyiv, the University of Latvia, the Estonian Geological Survey, the Geological Survey of Norway, and the San Diego Supercomputer Center. These academic and research experiences shaped her as a leading expert in groundwater sustainability, transboundary aquifers, and hydro-environmental monitoring.

Experience

Dr. Solovey’s professional career reflects a steady progression in academia and research. She began as an Assistant Lecturer and later Assistant Professor at Chernivtsi National University, She then joined the Institute of Technology and Life Sciences, Falenty, Poland, where she served as Senior Researcher she has been affiliated with the Polish Geological Institute – National Research Institute, where her roles have included Senior Researcher, Assistant Professor, and Associate Professor. She has also held leadership positions, such as Head of the Department of Hydrogeology and Deputy Head of the Department of Hydrogeology and Environmental Geology. In addition to her administrative and teaching responsibilities, she has actively contributed to European and international research collaborations and delivered invited lectures across Poland, Ukraine, and international scientific forums. She continues to mentor young researchers, lead hydrology-focused projects, and strengthen international cooperation in water resource sustainability.

Awards and Honors

Dr. Solovey’s research focuses on hydrogeology, groundwater resources, and transboundary water systems. She investigates the hydrological and hydrochemical regimes of wetlands, groundwater exchange processes in transboundary aquifers, and the effects of climate change on water resources. A significant aspect of her work is the integration of remote sensing and GRACE satellite data to monitor groundwater level fluctuations and storage changes. Her studies aim to improve sustainable groundwater management, particularly in cross-border basins such as the Bug River Basin shared by Poland, Ukraine, and Belarus. She also explores hydrogeological models for aquifers, groundwater pollution hazards, and climate-induced water resource variability. By combining field hydrology, geospatial monitoring, and environmental modeling, her work bridges science and policy, offering solutions for water security and environmental resilience. Her research has a strong applied dimension, supporting sustainable development and international cooperation in managing shared water resources across borders.

Research Focus

Dr. Solovey’s distinguished career is marked by academic recognition, memberships, and leadership roles in prominent scientific organizations. She has been an Expert of the Integrated Monitoring of the Natural Environment Commission at the Polish Ministry of the Environment and a member of the Geological Committee of the Polish Academy of Sciences. She is also an active member of several professional associations, including the Ukrainian Geographical Society, the Polish Geological Society, EuroGeoSurveys Working Group on Geohazards, and the International Association of Hydrogeologists. Her expertise has been acknowledged internationally through invited lectures and conference presentations at UNESCO ISARM, the International Association of Hydrogeologists Congress, and the EGU General Assembly. Beyond scientific recognition, she holds key editorial roles as Editor of Geological Quarterly and Przegląd Geologiczny, Deputy Editor-in-Chief of Meteorology, Hydrology, Environmental Monitoring, and Editor of Geology and Geochemistry of Combustible Minerals, reflecting her outstanding contribution to Earth sciences.

Publication Top Notes 

Groundwater pollution risks assessment in Ukraine-Poland transboundary aquifers
Year: 2024

Assessment of the Effectiveness of GRACE Observations in Monitoring Groundwater Storage in Poland
Year: 2025

Conclusion

Tatiana Solovey’s impressive research experience, leadership roles, and editorial contributions make her a strong candidate for the Best Researcher Award. With further development of interdisciplinary research, global impact, and research translation, Solovey could solidify her position as a leading researcher in hydrogeology and environmental geology.

Dr. Zhiwei Zuo | Machine Learning | Best Researcher Award Lecturer

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Dr. Zhiwei Zuo | Machine Learning | Best Researcher Award

Lecturer | Hunan University | China

Dr. Zhiwei Zuo is a researcher specializing in machine learning, artificial intelligence, and machine unlearning. He earned his Ph.D. in Computer Science from Hunan University, China, under the supervision of Prof. Zhuo Tang, where his research explored machine unlearning, adversarial robustness, and efficient deep learning methods. He also gained international research experience as a visiting student at Nanyang Technological University, Singapore, under the mentorship of Prof. Anwitaman Datta, further expanding his expertise in trustworthy AI. Dr. Zuo is currently a lecturer at the Faculty of Artificial Intelligence in Education, Central China Normal University, where he continues to focus on designing algorithms that address data privacy, security, and robustness challenges in artificial intelligence systems. He has published in prestigious journals and conferences such as IEEE Transactions on Knowledge and Data Engineering, ICASSP, and Information Sciences. His work contributes to advancing trustworthy AI while ensuring ethical and responsible deployment of machine learning technologies.

Professional Profile

Scopus

Education

Dr. Zhiwei Zuo pursued his academic journey across several prestigious institutions. He completed his Ph.D. in Computer Science at Hunan University focusing on machine learning, adversarial robustness, and machine unlearning, under the supervision of Prof. Zhuo Tang. During his doctoral studies, he broadened his international exposure as a visiting student at Nanyang Technological University, Singapore where he collaborated with Prof. Anwitaman Datta at the School of Computer Science and Engineering, working on machine unlearning algorithms and data privacy in AI systems. Prior to his doctoral research, he earned his Bachelor’s degree in Computer Science from Central China Normal University  which laid the foundation for his interest in artificial intelligence and secure computing. Building on these academic milestones, he now serves as a Lecturer at the Faculty of Artificial Intelligence in Education, Central China Normal University where he integrates his strong educational background with active research and teaching.

Experience

Dr. Zuo’s professional and research experience spans academia and international collaboration in computer science. Currently, he is a Lecturer at the Faculty of Artificial Intelligence in Education, Central China Normal University, where he engages in teaching and research on artificial intelligence and its applications in education and security. His doctoral research at Hunan University provided him with extensive experience in algorithm development, adversarial machine learning, and machine unlearning frameworks. As a visiting student at Nanyang Technological University, Singapore, he collaborated with Prof. Anwitaman Datta on advancing fine-grained approaches to machine unlearning, combining theoretical insights with practical applications. Dr. Zuo has also contributed to multiple interdisciplinary projects, focusing on robust classifiers, text adversarial attacks, and efficient algorithms for high-performance computing. His teaching and mentorship roles further reflect his dedication to cultivating the next generation of AI researchers. His career demonstrates a blend of innovative research, teaching excellence, and international collaboration.

Research Focus

Dr. Zuo’s research focuses on machine unlearning, privacy-preserving artificial intelligence, adversarial robustness, and trustworthy machine learning systems. His work seeks to address one of the emerging challenges in AI—how to efficiently remove specific data or knowledge from trained models without retraining them entirely. He has developed fine-grained parameter perturbation methods and incremental learning frameworks to advance machine unlearning. His research also explores adversarial robustness, designing models that can withstand adversarial text and image attacks, and developing generative classifiers resistant to transfer attacks. Additionally, he has contributed to efficient high-performance algorithms for Bayesian text classification in distributed environments. His interdisciplinary approach combines theory, algorithm design, and practical implementation to ensure machine learning models remain reliable, secure, and ethically aligned. Currently, his research bridges AI and education, focusing on the safe deployment of machine learning systems in sensitive domains, while addressing privacy, fairness, and accountability in artificial intelligence.

Awards and Honors

Dr. Zuo has received recognition for his academic excellence, innovative research, and contributions to the field of artificial intelligence. His publications in top-tier venues such as IEEE Transactions on Knowledge and Data Engineering, ICASSP, and Information Sciences have been well received in the research community. As a doctoral student, he earned research scholarships and support for his outstanding performance and contributions at Hunan University. His visiting research tenure at Nanyang Technological University was also supported by competitive funding, reflecting the significance of his work in machine unlearning. Additionally, his contributions to adversarial robustness and parallel algorithms have been acknowledged through conference presentations and collaborative projects. Dr. Zuo has participated in international conferences, where his work received positive recognition for originality and practical relevance. His career highlights include balancing strong theoretical research with applied solutions in secure AI systems, establishing him as a promising researcher in trustworthy and privacy-preserving AI.

Publication Top Notes 

A distributed skewed stream processing system based on scoring high-frequency key perception

Year: 2025

Conclusion

Zhiwei Zuo’s impressive research experience, innovative research, and interdisciplinary collaboration make them a strong candidate for the Best Researcher Award. With further development of their publication record, global impact, and research translation, Zuo could solidify their position as a leading researcher in machine learning.

Christian Caamaño Carrillo | Deep Learning | Best Researcher Award

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Dr. Christian Caamaño Carrillo | Deep Learning | Best Researcher Award

Docente Depto | Universidad del Bío-Bío | Chile

Dr. Christian Caamaño Carrillo is a Chilean statistician specializing in spatial statistics, semiparametric models, time series, and distribution theory. Currently serving as an Assistant Professor at the Department of Statistics, Universidad del Bío-Bío, Dr. Christian Caamaño Carrillo has built an extensive academic career combining advanced statistical theory with practical applications in environmental and economic data modeling. They hold a Ph.D. in Statistics from the Universidad de Valparaíso, where their research focused on modeling and estimating non-Gaussian random fields. With a strong background in both teaching and research,Dr. Christian Caamaño Carrillo has contributed to the training of future statisticians at undergraduate and graduate levels, delivering courses in geostatistics, linear models, and predictive modeling. Their work has been published in international journals, reflecting an ongoing commitment to methodological innovation and interdisciplinary collaboration. Dr. Christian Caamaño Carrillo continues to advance statistical methods for real-world data, particularly in environmental and spatial applications.

Professional Profile

Orcid

Scholar

Education

Dr. Christian Caamaño Carrillo earned their Ph.D. in Statistics from the Institute of Statistics, Universidad de Valparaíso, Chile, defending their thesis on the “Modeling and estimation of some non-Gaussian random fields” in May under the supervision of Dr. Moreno Bevilacqua and Dr. Carlo Gaetan. They completed an M.Sc. in Mathematics with a specialization in Statistics at the Universidad del Bío-Bío, with a thesis on estimating the Chilean Quarterly GDP Series, advised by Dr. Sergio Contreras. Prior to this, they qualified as a Statistical Engineer at the same institution in, with a thesis on panel data analysis applied to corporate strategies. Their academic journey began with a Bachelor’s degree in Statistics from Universidad del Bío-Bío. This robust educational background has provided them with expertise in statistical modeling, time series analysis, and spatial statistics, forming the foundation, research, and consulting activities.

Experience

Dr. Christian Caamaño Carrillo has been an Assistant Professor at the Department of Statistics, Universidad del Bío-Bío since August, where they teach and supervise both undergraduate and graduate students. From, they served as a Part-time Lecturer in the same department, delivering a wide range of courses in probability, statistical inference, and geostatistics. In parallel, they worked as a Part-time Lecturer at the Department of Mathematics and Applied Physics, Universidad Católica de la Santísima Concepción, focusing on foundational courses in statistics and probability. Their teaching portfolio spans undergraduate courses such as Linear Models, Random Variables, and Statistical Computing, as well as graduate-level instruction in Geostatistical Methods, Semiparametric Models, and Predictive Modeling. They have also contributed to specialized programs at Universidad Adolfo Ibáñez and Universidad de Valparaíso. Alongside their teaching, Dr. Christian Caamaño Carrillo maintains an active research agenda in spatial statistics and environmental data analysis.

Research Focus

Dr. Christian Caamaño Carrillo focuses on developing and applying advanced statistical methods to solve complex real-world problems. Their main research areas include spatial statistics, where they work on modeling spatial and spatio-temporal processes; semiparametric models, which offer flexible approaches for data with both structured and unstructured components; time series analysis, particularly in economic and environmental contexts; and distribution theory, addressing the properties and applications of probability distributions beyond standard Gaussian assumptions. A notable part of their work involves modeling environmental and geostatistical data using robust techniques that handle skewness and heavy-tailed behavior, such as skew-t processes. They are also engaged in methodological innovations for composite likelihood estimation and nearest-neighbor approaches in large spatial datasets. Through interdisciplinary collaborations, Dr. Christian Caamaño Carrillo applies these methods to areas such as environmental monitoring, mineral deposit modeling, and economic indicator estimation, bridging theory and practice in statistical science.

Awards and Honors

Dr. Christian Caamaño Carrillo has earned recognition in the academic community through sustained contributions to spatial statistics and applied statistical modeling. Their doctoral research on non-Gaussian random fields has been cited as a significant methodological advancement in environmental and geostatistical applications. As a faculty member, they have played a key role in developing and teaching specialized statistical courses, shaping the next generation of statisticians in Chile. They have been invited to collaborate with national and international researchers, leading to peer-reviewed publications in respected journals such as Environmetrics. Through graduate thesis supervision and involvement in interdisciplinary projects, Dr. Christian Caamaño Carrillo has contributed to advancing statistical applications in environmental sciences, mining, and economics. While formal awards were not listed, their academic trajectory demonstrates consistent professional excellence and recognition through publications, collaborations, and contributions to statistical education and methodology.

Publication Top Notes

Conclusion

Caamaño-Carrillo is a qualified and accomplished researcher, with a strong academic background, research experience, and teaching expertise. Their research areas are relevant and important in the field of statistics, and their publication record demonstrates their potential for making significant contributions to their field. With continued research and publication efforts, C. Caamaño-Carrillo has the potential to make a meaningful impact in their field and is a strong candidate for the Best Researcher Award.

Prof. Rita Santos Inácio | Data Science and Deep Learning | Best Researcher Award

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Prof. Rita Santos Inácio | Data Science and Deep Learning | Best Researcher Award

Professor, at Instituto Politécnico de Beja, Portugal.

Ana Rita Santos Inácio is a Quality Manager and Invited Adjunct Professor at the Polytechnic Institute of Beja. She holds a PhD in Food Science and Nutrition and has research experience in high-pressure technology applied to milk and cheese.

Professional Profile

Scopus

orcid

🎓 Education

– *PhD in Food Science and Nutrition*, Portuguese Catholic University of Porto – School of Biotechnology (2020)- *Master’s in Biotechnology – Food*, University of Aveiro (2013)- *Bachelor’s in Biotechnology*, University of Aveiro (2011)

💼 Experience

– *Quality Manager*, Sensory Laboratory, Polytechnic Institute of Beja (2023-present)- *Invited Adjunct Professor*, Department of Applied Technologies and Sciences, Polytechnic Institute of Beja (2020-present)- *Research Fellow*, University of Aveiro /QOPNA (2019-2020)

🔬 Research Interests

– *Food Science and Nutrition*: high-pressure technology, milk and cheese safety and quality- *Sensory Analysis*: sensory test sheets, sensory session planning and execution, data analysis- *Food Technology*: meat and fish technology, food safety and quality

🏆 Awards

– *”Summa Laude”*, PhD thesis (2020)- *FCT grant*, SFRH/BD/96576/2013 (2014-2019)

📚 Top Noted Publications

– Effect of high-pressure as a non-thermal pasteurisation technology for raw ewes’ milk and cheese safety and quality 🥛
– PhD thesis
– Effect of high-pressure on Serra da Estrela cheese 🧀
– Master’s thesis
– Second-generation bioethanol production: fermentation of acid sulphite liquor by free and immobilised Pichia stipitis 💡

Conclusion

Rita Santos Inácio’s research excellence, teaching experience, and professional activity make her a strong candidate for the Best Researcher Award. With further interdisciplinary collaboration and internationalization, she could further enhance the impact of her research and contribute to advancements in food science and nutrition.

Assoc. Prof. Dr Besey Ören | Structural Health Monitoring | Best Researcher Award

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Assoc. Prof. Dr Besey Ören | Structural Health Monitoring | Best Researcher Award 

Istanbul, University of health Science, Turkey

Assoc. Prof. Dr. Besey Ören is a distinguished academic and healthcare professional with a strong background in internal medicine nursing, intensive care nursing, emergency nursing, nephrology nursing, and cardiology nursing. With over three decades of experience, Ören has established herself as a leader in her field, serving as a faculty member, department head, and editor. Her dedication to nursing education and research has earned her numerous awards and honors, including the title of Associate Professor in Internal Medicine Nursing.

Profile

scopus

🎓 Education

Ören graduated with honors from Florence Nightingale School of Nursing in 1990. She completed her master’s degree in 1997 and her doctorate in 2010. Ören received the title of Assistant Professor in 2014 and Associate Professor in 2021. Her educational background has provided a solid foundation in nursing principles and prepared her for a career in research and education. Ören has also participated in various certificate programs, including Intensive Care Nursing courses in the USA.

👨‍🔬 Experience

Ören has accumulated extensive experience in nursing education, research, and practice. She has worked as a nurse, head nurse, faculty member, and department head at various institutions, including Istanbul University and Health Sciences University. Ören has served as the President of the Turkish Intensive Care Nurses Association and has been involved in numerous professional associations. Her experience has equipped her with a deep understanding of nursing principles and practices.

🔍 Research Interest

Ören’s research focus lies in internal medicine nursing, intensive care nursing, emergency nursing, nephrology nursing, and cardiology nursing. She has published numerous papers and book chapters on these topics and has presented at international and national conferences. Ören’s research aims to improve nursing practices and patient outcomes.

Awards and Honors 🏆

Ören has received numerous awards and honors for her contributions to nursing education and research. She has been recognized for her expertise in intensive care nursing and has served as an editor and scientific board member for various journals. Ören has also received scholarships for her research and has been involved in various projects and grants.

📚 Publications

“Investigation of the Effect of Sleep Hygiene Training on Obstructive Sleep Apnea Symptoms, Fatigue, and Sleep Quality In Patients With Atrial Fibrillation”

Conclusion

Assoc. Prof. Dr. Besey Ören’s extensive experience, leadership roles, research productivity, editorial and scientific contributions, and professional service make her a strong candidate for the Best Researcher Award. While there are areas for improvement, Ören’s achievements and contributions to nursing education and research demonstrate her qualifications for this award.

Assoc. Prof. Dr Chandra Mohan | Biosensors | Best Researcher Award

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Assoc. Prof. Dr Chandra Mohan | Biosensors | Best Researcher Award

Associate Professor, K R Mangalam University, Gurugram, India

As an Associate Professor of Chemistry, I possess a solid foundation in chemical sensors, transition metal chemistry, and heterocyclic complexes. With expertise in bimetallic complex synthesis and electrochemical sensor fabrication, I leverage my analytical and problem-solving skills to design and execute experiments with precision and accuracy. My passion for scientific discovery drives me to contribute to cutting-edge research in chemistry.

Profile

scholar

🎓 Education

– Ph.D. in Inorganic Chemistry: Guru Gobind Singh Indraprastha University, Delhi (2018)- M.Phil. in Inorganic Chemistry: University of Delhi (2009)- (link unavailable) in Applied Chemistry: Maharshi Dayanand Saraswati University, Ajmer (2007)- (link unavailable) in Physics, Chemistry, Maths: S P C Government College, Ajmer (2005)

👨‍🔬 Experience

– *Associate Professor*: K. R. Mangalam University, Gurugram (2023-Present)- *Assistant Professor*: K. R. Mangalam University, Gurugram (2013-2023)- *Assistant Professor*: HMRITM College, Delhi (2010-2011)

Awards and Honors 🏆

– *Research Collaborations*: Institute of Biotechnology, St. John’s University, Queens, New York, USA; Centre for Environmental Studies, Main Campus, Windhoek, Namibia; and others- Ph.D. Guidance: 5 students (3 awarded, 2 ongoing); (link unavailable) students (1); (link unavailable) students (15)

🔍 Research Interest

– *Chemical Sensors*: Synthesis and characterization of metal complexes for sensor applications- *Transition Metal Chemistry*: Bimetallic complex synthesis and applications- *Heterocyclic Complexes*: Synthesis and biological activity of heterocyclic compounds

📚 Publications 

1. Synthesis and characterization of Schiff based metal complexes and their application as chemical sensors 📚
2. Experimental and Theoretical Studies of Structural, Electronic and Optical Properties of Titanate Nanostructures 🔍
3. Synthesis, Characterization and Potential Applications of Conducting Polymer Nanocomposites 💡
4. Synthesis and Medicinal Applications of Quinazoline Derivatives 🏥
5. Degradation of Toxic Dyes from Wastewater using Chemical Methods 🌎
6. Removal of toxic pollutants using advanced oxidation processes 💧
7. Synthesis and biological activity of heterocyclic compounds as Anti-Inflammatory agents

Conclusion

Based on the provided information, the candidate exhibits a strong research background, extensive experience, and global collaborations, making them a suitable contender for the Best Researcher Award. However, quantifying research output and highlighting innovative contributions would further solidify their application ¹.

Prof. Dr. Jasenka Gajdoš Kljusurić | Data Science and Deep Learning | Best Researcher Award

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Prof. Dr. Jasenka Gajdoš Kljusurić | Data Science and Deep Learning | Best Researcher Award

Prof, Faculty of Food Technology and Biotechnology at University of Zagreb, Croatia

Sylvain S. Guillou is a Full Professor of Fluid Mechanics at the University of Caen Normandy, France. He is the Director of the Applied Science Laboratory LUSAC and has over 176 publications, 38,900 reads, and 1,692 citations. His research focuses on computational physics, fluid dynamics, and geophysics, particularly in tidal turbines and marine renewable energies ¹.

Profile

orcid

🎓 Education

– *HDR – Fluid Mechanics*, University of Caen (2004-2005)- Ph.D. in Applied Mathematics – Mechanics, University of Paris Pierre & Marie Curie (1993-1996)- (link unavailable) in Dynamics of Fluids – Numerical Modeling, Ecole Centrale de Nantes (1992-1993)

👨‍🔬 Experience

– *Full Professor*, University of Caen Normandy (2017-present)- *Associate Professor*, University of Caen Normandy (2005-2017)- *Assistant Professor*, University of Caen Normandy (1999-2005)- *Post-doctoral Researcher*, University of Caen (1996-1997)

🔍 Research Interest

– *Computational Physics*: Numerical simulations of complex fluid flows- *Fluid Dynamics*: Turbulence, sediment transport, and environmental fluid mechanics- *Geophysics*: Marine renewable energies, tidal turbines, and offshore wind energies

Awards and Honors 🏆

Although specific awards and honors are not detailed, Guillou’s editorial roles and conference organization demonstrate his recognition in the field ¹ ²: – *Associate Editor*, Energies, La Houille Blanche, and International Journal for Sediment Research- *Organizer*, International Conference on Estuaries and Coasts (ICEC-2018) and other conferences

📚 Publications 

– Numerical modeling of the effect of tidal stream turbines on the hydrodynamics and the sediment transport–Application to the Alderney Race (Raz Blanchard), France 🌊
– Modelling turbulence with an Actuator Disk representing a tidal turbine 🌟
– A two-phase numerical model for suspended-sediment transport in estuaries 🌴
– Wake field study of tidal turbines under realistic flow conditions 💨
– Tidal farm analysis using an analytical model for the flow velocity prediction in the wake of a tidal turbine with small diameter to depth ratio 🌊

Conclusion

Sylvain S. Guillou’s impressive research record, leadership roles, and editorial activities make him an excellent candidate for the Best Researcher Award. His contributions to computational physics, fluid dynamics, and geophysics have significantly advanced our understanding of these fields. With some potential for interdisciplinary collaborations and exploring emerging topics, Guillou is well-suited to receive this award ¹ ².

Dr. Seyed Abolfazl Aghili | machine learning and deep learning | Best Review Paper Award

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Dr. Seyed Abolfazl Aghili | machine learning and deep learning | Best Review Paper Award

lecturer, Siran university of science and technology, Iran

Seyed Abolfazl Aghili is a civil engineer and researcher with expertise in construction engineering and management. He holds a Ph.D. in Civil Engineering from Iran University of Science and Technology (IUST). His research focuses on machine learning, resiliency, and building information modeling (BIM). Dr. Aghili has published several papers in reputable journals and has presented his work at international conferences. He is fluent in Persian and English and has skills in various software, including Python, MS Project, and Autodesk AutoCAD.

Profile

orcid

Education 🎓

Ph.D. in Civil Engineering, Construction Engineering and Management, Iran University of Science and Technology (IUST), 2019-2024 (link unavailable) in Civil Engineering, Construction Engineering and Management, Iran University of Science and Technology (IUST), 2013-2015 (link unavailable) in Civil Engineering, Isfahan University of Technology (IUT), 2009-2013

Experience 💼 

Researcher, Iran University of Science and Technology (IUST), 2019-2024  Graduate Research Assistant, Iran University of Science and Technology (IUST), 2013-2015  Undergraduate Research Assistant, Isfahan University of Technology (IUT), 2009-2013

Awards and Honors🏆

Ranked 5th among 2200 participants in Nationwide University Entrance Exam for Ph.D. program in Iran, 2019 Ranked 2nd among all construction management students in Iran University Science and Technology, 2013-2015 Ranked 220th among 32,663 participants (Top 1%) in Nationwide University Entrance Exam for (link unavailable) program in Iran, 2013

Research Focus

Machine learning and deep learning methods  Resiliency  Building Information Modeling (BIM)  Human Resource Management (HRM)  Decision Making Systems for Project Managers

Publications 📚

1. Artificial Intelligence Approaches to Energy Management in HVAC Systems: A Systematic Review 🤖
2. Data-driven approach to fault detection for hospital HVAC system 📊
3. Feasibility Study of Using BIM in Construction Site Decision Making in Iran 🏗️
4. Review of digital imaging technology in safety management in the construction industry 📸
5. The role of insurance companies in managing the crisis after earthquake 🌪️
6. The need for a new approach to pre-crisis and post-crisis management of earthquake 🌊

Conclusion

Seyed Abolfazl Aghili is an exceptional researcher with a strong academic background, interdisciplinary research experience, and a notable publication record. His teaching and mentoring experience, as well as his technical skills, demonstrate his commitment to education and research. While there are areas for improvement, Dr. Aghili’s strengths make him a strong candidate for the Best Researcher Award.