Arnobio Palacios Gutiérrez | Data analysis and climatology | Best Researcher Award

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Mr. Arnobio Palacios Gutiérrez | Data analysis and climatology | Best Researcher Award

Complutense University of Madrid | Spain

Publication Profile

Orcid

📘 Education & Experience

Arnobio Palacios Gutiérrez is a dedicated academic and researcher with a strong interdisciplinary background in mathematics, physics, and statistics. He earned his Bachelor’s degree in Mathematics and Physics from the Technological University of Chocó (Colombia), followed by a Master’s degree in Engineering Data Analysis, Process Improvement, and Decision-Making from the Polytechnic University of Valencia (Spain). Currently, he is pursuing a PhD in Data Analysis at the Complutense University of Madrid, focusing on climate change pattern recognition through time series clustering. With over a decade of professional experience, Arnobio has served as a university professor and researcher at UTCH, contributing significantly to curriculum design, institutional planning, and data-driven development initiatives.

✅ Suitability Summary

Arnobio combines academic rigor with practical field experience, making him highly suitable for roles in data science, research, and public policy innovation. His ability to model complex problems, analyze multidimensional data, and generate decision-support frameworks positions him as a valuable asset in both academic and applied research contexts. His teaching portfolio includes courses in calculus, differential equations, physics, and advanced statistics, complemented by experience in strategic planning, consulting, and public innovation at the national level in Colombia. He is a collaborative leader who thrives in multidisciplinary environments and maintains a strong commitment to social impact and educational excellence.

🎓 Professional Development

Throughout his career, Arnobio has pursued continuous professional growth. He was awarded the prestigious Young Researcher Fellowship by the Colombian Ministry of Science and actively engages in national development projects. His technical proficiency includes R programming, database management, statistical analysis, and scientific writing. As a consultant and planner, he has developed strategic indicators and improvement plans for institutions and contributed to the design of public innovation strategies. His leadership in academia and his ability to manage complex projects reflect his organizational and analytical strengths.

🔬 Research Focus

Arnobio’s research centers on the development of new methodologies for identifying climate change patterns using time series clustering with dimensionality reduction techniques. His doctoral work aims to enhance understanding of environmental change through data science, while his Master’s thesis applied multivariate analysis to explore socio-demographic and development indicators across more than a thousand Colombian municipalities. His interests extend to public sector innovation, production systems management, and biodiversity valuation—areas where he integrates statistical modeling with sustainable development goals.

🏆 Honors & Awards

Among Arnobio’s recognitions is the Young Researcher Award from the Colombian Ministry of Science, highlighting his early promise in scientific investigation. He has also been honored as a Multiplier Leader by Future Colombia for his active role in social initiatives and cultural heritage projects. His leadership in regional innovation, environmental analysis, and educational advancement continues to shape policy and academic discussions both in Colombia and internationally.

📚 Top Notes Publication

Title: Quantifying Impact of Geographical Variables on Climate Change Patterns over Spain by Time Series Clustering

    • Authors: Arnobio Palacios-Gutiérrez; Jose Luis Valencia-Delfa; María Villeta

    • Journal: Earth Systems and Environment

    • Year: 2025

Title: Identification of extreme temperature and precipitation patterns in Spain based on multiscale analysis of time series

    • Authors: Arnobio Palacios-Gutiérrez; Jose Luis Valencia-Delfa; María Villeta

    • Journal: Natural Hazards

    • Year: 2025

Title: Time series clustering using trend, seasonal and autoregressive components to identify maximum temperature patterns in the Iberian Peninsula

    • Authors: Arnobio Palacios Gutiérrez; Jose Luis Valencia Delfa; María Villeta López

    • Journal: Environmental and Ecological Statistics

    • Year: 2023

Title: Identification of precipitation and maximum temperature patterns in Spain during 1951 to 2021 using clustering based on multiscale analysis of time series

    • Authors: Arnobio Palacios Gutiérrez; Jose Luis Valencia Delfa

    • Journal: Preprint (EGU General Assembly)

    • Year: 2023

Title: Time Series Clustering using Trend, Seasonal and Autoregressive Components: Patterns of Change of Maximum Temperature in Iberian Peninsula

    • Authors: Arnobio Palacios Gutiérrez; Jose Luis Valencia Delfa

    • Journal: Publications of the Institute of Geophysics, Polish Academy of Sciences; Geophysical Data Bases, Processing and Instrumentation

    • Year: 2022

Weiyang Chen | image processing | Best Researcher Award

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Dr. Weiyang Chen | image processing | Best Researcher Award

Qufu Normal University | China

Publication Profile

Scopus

🎓 EARLY ACADEMIC PURSUITS

Dr. Weiyang Chen began his academic journey with a strong foundation in science and technology, culminating in a Ph.D. from the Chinese Academy of Sciences in 2015. His early academic work laid the groundwork for his future focus on image processing, data analysis, and bioinformatics.

💼 PROFESSIONAL ENDEAVORS

Currently an Associate Professor at the School of Cyber Science and Engineering, Qufu Normal University, Dr. Chen has significantly contributed to both teaching and research. He has participated in 5 consultancy or industry-sponsored projects and holds key roles, such as Deputy Secretary General of the Cloud Computing and Big Data Committee and Bentham Ambassador.

🔬 CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Chen’s research spans bioinformatics, video and image processing, and algorithm development. He has authored over 50 publications, holds 12 patents, and developed several software applications. He has completed or is currently conducting 8 research projects, reflecting his leadership and innovation.

🌍 IMPACT AND INFLUENCE

His research has been featured in international media including TIME, The Guardian, NewScientist, Science News, and Daily Mail. With an h-index of 16 on ResearchGate, his work has a strong academic footprint and public engagement.

📚 ACADEMIC CITES AND RECOGNITION

Dr. Chen has published 38 articles in SCI and Scopus-indexed journals. He has served on 6 academic conference committees and contributes to scientific discourse through his profiles at ResearchGate and his university homepage.

🤝 COLLABORATIONS AND NETWORKS

He collaborates with distinguished scholars like Professor Jingdong Han (Peking University) and Dr. Yi Pan, a Fellow of numerous international academies and engineering institutes. These partnerships enhance the quality and visibility of his research.

🏆 LEGACY AND FUTURE CONTRIBUTIONS

Dr. Chen aims to further explore bioinformatics and artificial intelligence, with a focus on real-world applications. His work in software development, interdisciplinary research, and professional service ensures his lasting academic legacy and continuing innovation.

🥇 AWARD PREFERENCE

For his outstanding achievements and global impact, Dr. Weiyang Chen is a strong nominee for the Best Researcher Award.

📚 TOP NOTES PUBLICATIONS

📄 1. A high precision method of segmenting complex postures in Caenorhabditis elegans and deep phenotyping to analyze lifespan

  • Authors: Bingyue Dong, Weiyang Chen

  • Journal: Scientific Reports

  • Year: 2025

📄 2. Exploring the relationship among Alzheimer’s disease, aging and cognitive scores through neuroimaging-based approach

  • Authors: Jinhui Sun, Jingdong Jackie Han, Weiyang Chen

  • Journal: Scientific Reports

  • Year: 2024

📄 3. An automatic measurement method for the response of Caenorhabditis elegans to chemicals

  • Authors: Nan Zhang, Yanmin Nie, Bingyue Dong, Weiyang Chen, Shan Gao

  • Journal: Technology and Health Care
    (Official Journal of the European Society for Engineering and Medicine)

  • Year: 2024

📄 4. Automated recognition and analysis of body bending behavior in C. elegans

  • Authors: Hui Zhang, Weiyang Chen

  • Journal: BMC Bioinformatics

  • Year: 2023

Kwang-Sig Lee | Artificial Intelligence | Excellence in Research

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Dr. Kwang-Sig Lee | Artificial Intelligence | Excellence in Research

Korea University Anam Hospital AI Center | South Korea

Publication Profile

Scopus

Google Scholar

INTRODUCTION 🧑‍🎓

Dr. Kwang-Sig Lee is a distinguished academician, research leader, and innovator specializing in the integration of medical and social informatics. Currently serving as Vice Center Chief at the AI Center of Korea University Anam Hospital, Dr. Lee’s groundbreaking research combines artificial intelligence with diverse datasets, such as genetic, image, numeric, and text data. His expertise in AI-driven systems has led to revolutionary work in healthcare, focusing on predictive AI models and multimodal machine learning. His work has earned significant recognition, influencing both academic circles and real-world medical applications.

EARLY ACADEMIC PURSUITS 🎓

Dr. Lee’s academic journey began at Kon Kuk University in Seoul, South Korea, where he earned a Bachelor’s degree in Economics and Physics (1994-1999), with a GPA of 3.52/4.00. He furthered his studies at Iowa State University (1999-2004), earning dual Master’s degrees in Economics and Sociology, graduating with a GPA of 3.69/4.00. Dr. Lee’s pursuit of advanced studies led him to Johns Hopkins University, where he obtained his Ph.D./MSE in Sociology and Applied Mathematics with a focus on health systems, securing a GPA of 3.63/4.00.

PROFESSIONAL ENDEAVORS 💼

Dr. Lee’s professional career spans across multiple prestigious institutions. At present, he holds the role of Vice Center Chief at Korea University’s AI Center in the Medical School. His previous roles include serving as a Research Associate Professor at the same institution, and Senior Research Fellow positions at various research agencies, including Acorn, Enliple, Agilesoda, and National Health Insurance Service. Dr. Lee has also worked as an Assistant Professor at Yonsei University and Sungkyunkwan University, contributing his expertise in preventive medicine and biostatistics.

CONTRIBUTIONS AND RESEARCH FOCUS ON ARTIFICIAL INTELLIGENCE 🧬

Dr. Lee’s contributions to the field of medical and social informatics are vast and impactful. His research primarily focuses on the application of artificial intelligence (AI) in healthcare, especially through the use of machine learning models, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformer models. His work explores the integration of genetic, image, numeric, and text data, thereby providing a more holistic approach to solving complex health-related challenges. Dr. Lee is known for his expertise in “Wide & Deep Learning,” a method that synthesizes multiple AI approaches to offer more powerful insights and predictive models.

IMPACT AND INFLUENCE 🌍

Dr. Lee’s innovative research has earned significant recognition both in academic and industrial circles. His work has been published in over 45 SCIE-indexed journals with a combined impact factor of 168. His Field-Weighted Citation Impact is 1.76, surpassing the average citation impact of KAIST in 2021. His expertise is frequently sought in both teaching and consultation, with Dr. Lee being an influential member of various academic committees. His ability to mentor graduate students and lead multidisciplinary research projects has significantly shaped the landscape of AI and healthcare.

ACADEMIC CITATIONS AND PUBLICATIONS 📚

Dr. Lee’s extensive publication record spans notable journals such as Cancers, European Radiology, International Journal of Surgery, and Journal of Medical Systems. His contributions have greatly impacted the scientific community, with a robust body of work related to medical AI, health informatics, and predictive modeling. In addition to his research articles, Dr. Lee has served as a guest editor for journals like Frontiers in Bioscience and Applied Sciences, as well as a reviewer for top-tier publications such as Nature Communications and Journal of Big Data.

HONORS & AWARDS 🏆

Throughout his academic career, Dr. Lee has been the recipient of numerous accolades, including full financial support during his tenure at Johns Hopkins University and Iowa State University. Additionally, he has been awarded for his academic excellence during his undergraduate studies at Kon-Kuk University. Dr. Lee’s consistent recognition for research excellence is evident from his impactful publications and active participation in the academic community, including his involvement in major research projects funded by government agencies.

FINAL NOTE ✨

Dr. Kwang-Sig Lee’s career is a testament to his dedication to advancing AI in medicine and social sciences. His expertise in combining machine learning with healthcare applications has paved the way for new innovations in predictive medicine, offering vital contributions to global healthcare systems. As he continues to lead research projects at the AI Center at Korea University, Dr. Lee’s legacy will be defined by his commitment to improving public health through cutting-edge technology and interdisciplinary research.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Dr. Lee’s future endeavors are poised to have a lasting impact on the fields of AI and healthcare. As the Vice Center Chief at one of the top medical schools, his work is expected to advance predictive healthcare models, fostering the development of more personalized and efficient healthcare solutions. With his expertise in “Wide & Deep Learning,” Dr. Lee is likely to continue influencing both the academic community and industry, shaping the future of AI-driven healthcare innovations.

TOP NOTES PUBLICATIONS 📚

Article: Graph Machine Learning With Systematic Hyper-Parameter Selection on Hidden Networks and Mental Health Conditions in the Middle-Aged and Old
  • Authors: K. Lee, Kwang-sig; B. Ham, Byung-joo
    Journal: Psychiatry Investigation
    Year: 2024
Article: A Machine Learning-Based Decision Support System for the Prognostication of Neurological Outcomes in Successfully Resuscitated Out-of-Hospital Cardiac Arrest Patients
  • Authors: S. Lee, Sijin; K. Lee, Kwang-sig; S. Park, Sang-hyun; S. Lee, Sung-woo; S. Kim, Sujin
    Journal: Journal of Clinical Medicine
    Year: 2024
Article: Clinical and Dental Predictors of Preterm Birth Using Machine Learning Methods: The MOHEPI Study
  • Authors: J. Park, Jung-soo; K. Lee, Kwang-sig; J. Heo, Ju-sun; K. Ahn, Ki-hoon
    Journal: Scientific Reports
    Year: 2024
Article: Explainable Artificial Intelligence on Safe Balance and Its Major Determinants in Stroke Patients
  • Authors: S. Lee, Sekwang; E. Lee, Eunyoung; K. Lee, Kwang-sig; S.B. Pyun, Sung Bom
    Journal: Scientific Reports
    Year: 2024

Biying Fu | Machine Learning Applications | Best Researcher Award

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Dr. Biying Fu | Machine Learning Applications | Best Researcher Award

Hochschule RheinMain, Germany

Professional Profile👨‍🎓

Early Academic Pursuits 📚

Dr. Biying Fu’s academic journey began with her primary and secondary education in Shanghai, China, where she developed a strong foundation in subjects like mathematics, German, English, physics, and chemistry. Her academic excellence continued through high school, culminating in an outstanding Abitur score of 1.1. She pursued a Bachelor’s degree in Electrical Engineering and Information Technology at Karlsruhe Institute of Technology (KIT), Germany, followed by a Master’s degree with a focus on Communications and Information Technology. Dr. Fu’s academic pursuits further advanced with a Ph.D. from the Technical University of Darmstadt (TUda), where she specialized in sensor applications for human activity recognition in smart environments.

Professional Endeavors 💼

Dr. Fu’s professional career began at the Fraunhofer Institute for Integrated Circuits (IGD), where she contributed significantly to the Sensing and Perception group. Over time, she expanded her expertise into the Smart Living and Biometric Technologies department, becoming a scientific employee and project leader. Her roles included innovative work on smart environments, human activity recognition, and biometric technologies. Dr. Fu has been instrumental in creating real-world applications for sensor technologies and machine learning algorithms, with notable contributions to the Smart Floor project, which focuses on indoor localization and emergency detection in ambient assisted living environments.

Contributions and Research Focus 🔬

Dr. Fu’s research has been centered around smart environments, sensor systems, and human activity recognition. Her dissertation, titled “Sensor Applications for Human Activity Recognition in Smart Environments,” examined multimodal sensor systems, including capacitive sensors, accelerometers, and smartphone microphones, for tracking physical activities and indoor localization. Her work merges signal processing, neural networks, and data generation techniques to enhance the interaction between people and machines. Her ongoing research continues to explore the intersection of artificial intelligence and explainability, contributing to the development of transparent and interpretable machine learning models.

Impact and Influence 🌍

Dr. Fu’s research in smart technologies has far-reaching implications for assistive technologies, healthcare, and the development of intuitive human-machine interactions. Her contributions to the field of human activity recognition have improved how we use sensors to monitor and analyze daily activities in smart homes and health environments. Furthermore, her involvement in interdisciplinary projects, such as optical quality control and optical medication detection, has enhanced industrial applications of computer vision and machine learning.

Academic Cites and Recognition 📖

Dr. Fu has earned recognition in both academia and industry. Her dissertation, publications, and research projects have attracted attention in top conferences and journals. Her participation in global programs like the Summer School of Deep Learning and Reinforcement Learning at the University of Alberta further emphasizes her standing in the scientific community. Additionally, Dr. Fu has been an active participant in various educational and research initiatives, such as the REQUAS project, and she continues to serve as a professor at Hochschule RheinMain, where she focuses on the emerging field of Explainable AI.

Technical Skills ⚙️

Dr. Fu possesses advanced technical skills in various programming languages, including C/C++, Java, and Python. She is highly proficient in machine learning libraries such as Scikit-Learn, TensorFlow, Keras, and PyTorch, and has hands-on experience with simulation tools like Matlab/Simulink and CST Microwave Studio. Her expertise extends to signal processing, computer vision, and the use of embedded systems for smart applications. Additionally, Dr. Fu has a strong command of version control tools like GIT and SVN, as well as project management platforms such as JIRA and SCRUM.

Teaching Experience 👩‍🏫

Dr. Fu has contributed to the academic development of students through various teaching roles. She has served as a tutor for subjects like digital technology and wave theory during her time at KIT. As a professor at Hochschule RheinMain, she currently teaches courses in smart environments, with a focus on advanced topics in Explainable AI. Her ability to communicate complex concepts clearly and her passion for fostering intellectual curiosity have made her a respected educator in her field.

Legacy and Future Contributions 🌟

Dr. Fu’s work continues to shape the future of smart environments, human-machine interactions, and explainable AI. Her research on sensor technologies and machine learning has paved the way for smarter and more intuitive technologies in healthcare, industry, and everyday life. As she continues to contribute to both academic and industry advancements, Dr. Fu’s legacy will be marked by her dedication to the development of technologies that improve human well-being and promote transparency in artificial intelligence systems. Her ongoing contributions will continue to inspire the next generation of researchers and engineers.

📖Top Noted Publications

A Survey on Drowsiness Detection – Modern Applications and Methods

Authors: Biying Fu, Fadi Boutros, Chin-Teng Lin, Naser Damer

Journal: IEEE Transactions on Intelligent Vehicles

Year: 2024

Generative AI in the context of assistive technologies: Trends, limitations and future directions

Authors: Biying Fu, Abdenour Hadid, Naser Damer

Journal: Image and Vision Computing

Year: 2024

Biometric Recognition in 3D Medical Images: A Survey

Authors: Biying Fu, Naser Damer

Journal: IEEE Access

Year: 2023

Face morphing attacks and face image quality: The effect of morphing and the unsupervised attack detection by quality

Authors: Biying Fu, Naser Damer

Journal: IET Biometrics

Year: 2022

Generalization of Fitness Exercise Recognition from Doppler Measurements by Domain-Adaption and Few-Shot Learning

Authors: Biying Fu, Naser Damer, Florian Kirchbuchner, Arjan Kuijper

Journal: Book chapter

Year: 2021