Yin Fei Xu | Deep Learning | Excellence in Research Award

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Assoc. Prof. Dr. Yin Fei Xu | Deep Learning | Excellence in Research Award 

Associate Professor | Southeast University  | China

Yinfei Xu is an Associate Researcher in the Department of Signal Processing, School of Information Science and Engineering at Southeast University, a master’s and doctoral supervisor and a Zhishan Young Scholar of Southeast University. He received his PhD in signal and information processing from Southeast University and carried out research as a research assistant and postdoctoral fellow at the Chinese University of Hong Kong and as a visiting PhD scholar at McMaster University in Canada. His research is deeply rooted in statistical signal processing, information theory, machine-learning-driven algorithmic design, optimization for real-world scenarios, statistical data analysis, and the development of artificial-intelligence models for image, speech, and multimodal applications. He has led or participated in more than ten national, provincial, industrial, and laboratory research projects and has published over seventy academic papers in high-impact international journals. As first author he has contributed to a number of influential publications including New Proofs of Gaussian Extremal Inequalities With Applications in IEEE Transactions on Information Theory, Information Embedding With Stegotext Reconstruction in IEEE Transactions on Information Forensics and Security, Secret Key Generation From Vector Gaussian Sources With Public and Private Communications in IEEE Transactions on Information Theory, Vector Gaussian Successive Refinement With Degraded Side Information in IEEE Transactions on Information Theory, Asymptotical Optimality of Change Point Detection With Unknown Discrete Post-Change Distributions in IEEE Signal Processing Letters, The Sum Rate of Vector Gaussian Multiple Description Coding with Tree-Structured Covariance Distortion Constraints in IEEE Transactions on Information Theory.

Profile: Orcid

Featured Publications:

Zhang, J., Xu, H., Zheng, A., Cao, D., Xu, Y., & Lin, C. (2025). Transmitting status updates on infinite capacity systems with eavesdropper: Freshness advantage of legitimate receiver. Entropy.

Zhang, J., & Xu, Y. (2022). Age analysis of status updating system with probabilistic packet preemption. Entropy.

Xu, Y., Zu, Y., & Zhang, H. (2021). Optimal inter-organization control of collaborative advertising with myopic and far-sighted behaviors. Entropy.

Zhang, J., & Xu, Y. Age analysis of status updating system with probabilistic packet preemption.

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.

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.

Mr. Oussama El Othmani | Data Science and Deep Learning | Excellence in Research

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Mr. Oussama El Othmani | Data Science and Deep Learning | Excellence in Research

Computer Engineering, Tunisia Polytechnic School, Tunisia

This individual is a promising researcher and software engineer with a strong background in computer science. Currently pursuing a PhD in ETIC at Tunisia Polytechnic School, University of Carthage La Marsa, they have a solid foundation in computer engineering from the Tunisian Military Academy. With experience as a software engineer at the Tunisian Ministry of National Defense, they have developed expertise in software development, collaboration, and problem-solving. Their research interests lie at the intersection of technology and innovation, with potential applications in various fields.

Profile

orcid

🎓 Education

– *PhD in ETIC*: Tunisia Polytechnic School, University of Carthage La Marsa, Tunis (2024 – Present)- *Computer Engineering*: Tunisian Military Academy, Fondik Jdid (2020-2023)- *Preparatory Mathematics-Physics*: Tunisian Military Academy, Fondik Jdid (2018-2020)- *Relevant Coursework*: Advanced Learning Algorithms, Artificial Intelligence, Computer Architecture, Database Management, Software Methodology, Project Management Fundamentals

👨‍🔬 Experience

– *Software Engineer*: Tunisian Ministry of National Defense (August 2023 – Present) – Participated in the full software development lifecycle – Collaborated with system engineers, hardware designers, and integration/test engineers – Developed optimized code for specific hardware platforms – Applied Agile development methodologies and object-oriented architectures

🔍 Research Interest

The individual’s research focus is not explicitly stated, but based on their education and experience, they may be interested in exploring topics related to artificial intelligence, computer architecture, and software methodology. Potential research areas could include machine learning, data science, and software engineering.

Awards and Honors🏆

No information is available on awards and honors received by the individual.

📚 Publications 

Rough Set Theory and Soft Computing Methods for Building Explainable and Interpretable AI/ML Models

Développement d’un système de détection des anomalies des cellules sanguines et son utilisation en télémédecine

BloodScan

Conclusion

The candidate shows promise for the Best Researcher Award with their relevant education, professional experience, and technical skills. However, additional research experience, interdisciplinary knowledge, and a stronger publication record would significantly enhance their application. With focused effort in these areas, the candidate could become a strong contender for the award.