XinYing Chew | Computer Science | Young Scientist Award

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Assoc. Prof. Dr. XinYing Chew | Computer Science | Young Scientist Award

Associate Professor at Universiti Sains Malaysia (USM), Malaysia

Associate Professor Ts. Dr. Chew XinYing is a distinguished academic and researcher at Universiti Sains Malaysia (USM), where she serves in the School of Computer Sciences. With extensive expertise in industrial computing and advanced analytics, she has made significant contributions to data-driven research, quality control, and artificial intelligence applications. As a Program Manager for both Computer Science and Offshore Programs at USM, she plays a vital role in shaping academic curricula and fostering industry collaborations. Her work spans interdisciplinary domains, including AI in tourism, environmental sustainability, and predictive analytics, making her a key figure in modern computational research. Dr. Chew has co-authored numerous high-impact journal publications and actively collaborates with international scholars, reflecting her commitment to advancing knowledge globally. With her leadership, research acumen, and dedication to academic excellence, she continues to drive innovation in data analytics and computational intelligence, contributing to both academia and industry applications.

Professional Profile

Education

Dr. Chew XinYing holds a Ph.D. in Computer Science from Universiti Sains Malaysia (USM), where she specialized in industrial computing and advanced statistical methodologies. Prior to her doctoral studies, she earned her Bachelor of Information Technology (Hons.) from Universiti Kebangsaan Malaysia (UKM), laying the foundation for her expertise in data analytics and computational intelligence. Throughout her academic journey, she has demonstrated a deep passion for integrating statistical process control techniques with modern computing approaches, making her a key researcher in quality control and decision-making systems. Her educational background has equipped her with advanced knowledge in artificial intelligence, predictive modeling, and big data analytics. This strong academic foundation has not only fueled her research contributions but also positioned her as a mentor and educator, guiding students in cutting-edge technological advancements. Dr. Chew’s commitment to continuous learning has made her a well-rounded scholar in the field of computational sciences.

Professional Experience

Dr. Chew XinYing is currently an Associate Professor at the School of Computer Sciences, Universiti Sains Malaysia (USM), where she also serves as the Program Manager for both Computer Science and Offshore Programs. Her professional career spans years of academic excellence, with a focus on curriculum development, student mentorship, and research leadership. She has played a pivotal role in shaping USM’s computer science programs, ensuring they align with industry standards and emerging technological trends. Beyond academia, she has engaged in industry collaborations, applying her expertise in industrial computing and analytics to solve real-world challenges. Her research extends into diverse fields such as artificial intelligence in business intelligence, statistical process control, and environmental sustainability. Dr. Chew’s extensive experience in both research and academic leadership has positioned her as a key contributor to Malaysia’s technological and educational advancements, fostering a new generation of computational scientists and researchers.

Research Interests

Dr. Chew XinYing’s research interests lie at the intersection of industrial computing, artificial intelligence, quality control, and advanced analytics. She has conducted extensive studies on statistical process control (SPC) and predictive modeling, focusing on their applications in business intelligence and decision-making. Additionally, her work explores artificial intelligence in tourism, environmental sustainability, and customer behavior analytics, reflecting her ability to integrate computing technologies into diverse domains. She is particularly interested in machine learning algorithms, big data analytics, and AI-driven decision support systems, which have wide-ranging applications in healthcare, financial analytics, and industrial optimization. Her interdisciplinary approach has led to impactful research in areas such as green technology, metaverse ethics, and orthopedic disease detection using AI. By bridging computational science with real-world applications, Dr. Chew continues to push the boundaries of data-driven innovation and contribute to advancements in both academic and industrial sectors.

Awards and Honors

Dr. Chew XinYing has been recognized for her outstanding contributions to research and academia through various awards and honors. Her scholarly achievements are reflected in her numerous high-impact journal publications, earning her recognition as a leading researcher in industrial computing and AI-driven analytics. She has received international accolades for her work in predictive modeling, AI in tourism, and quality control methodologies, demonstrating the real-world impact of her research. As a highly cited researcher, her studies have influenced multiple fields, positioning her among the top contributors in data-driven decision-making research. In addition to academic awards, she has been invited as a keynote speaker and panelist at international conferences, highlighting her expertise in machine learning and computational intelligence. Her dedication to academic excellence, combined with her leadership in research and education, continues to earn her prestigious honors, further establishing her as a respected figure in computer science and analytics.

Conclusion

Associate Professor Ts. Dr. Chew XinYing is a strong candidate for the Research for Young Scientist Award due to her high research productivity, interdisciplinary expertise, and leadership roles. To further solidify her eligibility, she could focus on independent research contributions, securing significant research grants, and emphasizing industry impact through patents and collaborations.

Publications Top Noted

1. Blockchain and Innovation Resistance

  • Title: Navigating the Power of Blockchain Strategy: Analysis of Technology-Organization-Environment (TOE) Framework and Innovation Resistance Theory Using PLS-SEM and ANN Insights
  • Authors: Alnoor, A.M., Abbas, S., Sadaa, A.M., Chew, X., Erkol Bayram, G.E.
  • Year: 2025
  • Journal: Technological Forecasting and Social Change
  • Citations: 0

2. Statistical Process Control and Quality Engineering

  • Title: Optimal Designs of the Group Runs Exponentially Weighted Moving Average X and t Schemes

  • Authors: Khaw, K.W., Chew, X., Teh, S.

  • Year: 2025

  • Journal: Quality and Reliability Engineering International

  • Citations: 0

  • Title: The One-Sided Variable Sampling Interval Exponentially Weighted Moving Average X? Charts Under the Gamma Distribution

  • Authors: Goh, K.L., Chew, X.

  • Year: 2024

  • Journal: Sains Malaysiana

  • Citations: 0

3. Organizational Communication and IT

  • Title: How Information Technology Influences Organizational Communication: The Mediating Role of Organizational Structure
  • Authors: Chew, X., Alharbi, R.K., Khaw, K.W., Alnoor, A.M.
  • Year: 2024
  • Journal: PSU Research Review
  • Citations: 2

4. Consumer Behavior and Decision-Making

  • Title: Unveiling the Optimal Configuration of Impulsive Buying Behavior Using Fuzzy Set Qualitative Comparative Analysis and Multi-Criteria Decision Approach
  • Authors: Alnoor, A.M., Abbas, S., Khaw, K.W., Raad Muhsen, Y.R., Chew, X.
  • Year: 2024
  • Journal: Journal of Retailing and Consumer Services
  • Citations: 6

5. E-Commerce and Customer Trust

  • Title: Symmetric and Asymmetric Modeling to Boost Customers’ Trustworthiness in Livestreaming Commerce
  • Authors: Chew, X., Alnoor, A.M., Khaw, K.W., Al Halbusi, H., Raad Muhsen, Y.R.
  • Year: 2024
  • Journal: Current Psychology
  • Citations: 2

6. Artificial Intelligence and Tourism

  • Title: The Role of Artificial Intelligence in Regenerative Tourism and Green Destinations
  • Authors: Alnoor, A.M., Erkol Bayram, G.E., Chew, X., Shah, S.H.A.
  • Year: 2024
  • Publication Type: Book
  • Citations: 0

 

Jianwen Wang | Computer science and remote sensing | Best Researcher Award

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Mr Jianwen Wang | Computer science and remote sensing | Best Researcher Award

Doctor, East China Normal University, China

Jianwen G. (Bruce Wang), 32, is a versatile professional with expertise in software engineering, music, literature, and entrepreneurship. Based in Shanghai, he holds a PhD from East China Normal University. As a certified musician, he has released nearly 20 self-composed songs across various genres, including pop, R&B, and folk. Additionally, Jianwen is a regularly contracted writer for Tencent’s China Literature Group, where he has published novels, essays, and critiques. In 2023, he founded Shanghai XiZhe Network Technology Co., Ltd., focusing on AI products, software development, and digital transformation. A passionate researcher in landscape ecology, he has made significant contributions to understanding farmland abandonment and recultivation dynamics in the Yangtze River Delta using Google Earth Engine. Jianwen is fluent in multiple languages, including English, Chinese, Korean, Japanese, and German.

Profile

Orcid

Strengths for the Award

  1. Diverse Expertise and Multidisciplinary Skills:
    • Academic Background: Jianwen’s Ph.D. from East China Normal University indicates a strong academic foundation. His research on “farmland abandonment and recultivation dynamics in the Yangtze River Delta” in a landscape ecology context shows a sophisticated understanding of environmental issues, particularly those in the rapidly changing Yangtze River Delta.
    • Strong Research Capabilities: The use of Google Earth Engine for multiscale analysis is a noteworthy strength. This demonstrates advanced proficiency in geographic information systems (GIS) and remote sensing technologies, which are increasingly important in environmental research. His ability to apply such technologies to study complex dynamics like farmland abandonment demonstrates significant technical and scientific competence.
    • Scientific Writing: He has been actively engaged in writing research papers and has the capability to communicate complex scientific ideas in both English and Chinese, highlighting his versatility and proficiency in academic communication.
    • Innovative Research Areas: His research topic has significant social relevance, addressing issues of sustainable agriculture, environmental conservation, and land use changes in a rapidly urbanizing region. This aligns well with current global challenges such as climate change and urbanization.
  2. Leadership and Entrepreneurial Drive:
    • CEO of XiZhe Network Technology Co., Ltd.: His entrepreneurial endeavor in founding a tech company with a focus on AI products and internet technology showcases his leadership and ability to innovate in the business space. This entrepreneurial experience also complements his academic skills, offering him a practical understanding of how research can lead to real-world applications and business solutions.
  3. Literary and Artistic Creativity:
    • His background as a musician and literary writer demonstrates a well-rounded individual who excels in both creative and analytical fields. The breadth of his talents could contribute to his research by fostering innovative, interdisciplinary thinking and integrating creative problem-solving into his academic work.
  4. Awards and Recognition:
    • Best Paper Award at the 13th China-Japan-Korea Geography Conference is a notable accolade that speaks to the quality and impact of his research in the academic community.
    • Other recognitions, such as National Inspirational Scholarship and being an Outstanding Student Union Officer, suggest that he has been a leader in both academic and extracurricular spheres throughout his academic career.
  5. Multilingual Proficiency:
    • His fluency in English, Chinese, Korean, Japanese, and German is a significant asset in academic research, allowing him to access a wider range of literature, collaborate with international peers, and participate in cross-cultural research projects.

Areas for Improvement

  1. Focused Research Outputs:
    • While his work is promising, it would be helpful for Jianwen to focus more on publishing high-impact journal articles and peer-reviewed papers in his primary field of research. As his current research appears to involve both professional writing (novels, essays, etc.) and entrepreneurial pursuits, there could be more clarity and emphasis on his scientific output and contributions to landscape ecology and geography.
    • The range of activities he engages in (writing novels, running a business, etc.) is impressive but might distract from deepening his research career in a more specialized and focused manner. For a Best Researcher Award, it is essential to have a strong, sustained output in research publications that push the boundaries of knowledge in the chosen field.
  2. Research Collaboration:
    • While he appears to be a successful individual contributor, increased collaboration with other researchers or research institutions could help enhance the scope and impact of his work. Collaborative projects, particularly with international scholars or interdisciplinary teams, might provide valuable insights and further elevate his research profile.
  3. Academic Mentorship:
    • Jianwen’s leadership skills in his company could be transferred to academia through mentoring younger researchers or students. Actively mentoring PhD students, participating in academic advisory roles, or engaging in more teaching opportunities would help him establish a stronger academic legacy.

Education 

Jianwen G. earned his Ph.D. in Geography from East China Normal University (2019–2023). His doctoral research focused on landscape ecology, particularly studying the dynamics of farmland abandonment and recultivation in the Yangtze River Delta using cutting-edge tools like Google Earth Engine. In addition to his academic studies, Jianwen pursued various personal and professional interests, including music composition and software development. His interdisciplinary approach merges environmental science with technology, demonstrating a strong capacity for integrating advanced tools into environmental research. His academic achievements are complemented by his proficiency in English, Chinese, Korean, Japanese, and German, making him well-versed in global academic discourse. Throughout his academic journey, Jianwen excelled in both research and extracurricular activities, earning recognition for his leadership and scholarly accomplishments.

Experience 

Jianwen G. has had a dynamic career spanning multiple fields. Since 2019, he has been a regularly contracted writer with Tencent’s China Literature Group, where he writes novels, essays, and critiques, with over 500,000 words of his autobiographical novel, “Just When We Were Young”, awaiting publication. He has also released more than 200,000 words across six online novels in genres such as fantasy, urban realism, and science fiction. In May 2023, Jianwen founded Shanghai XiZhe Network Technology Co., Ltd., where he serves as CEO. The company specializes in AI, software development, and internet business outsourcing. His leadership has helped the company form strategic collaborations with multiple enterprises. Furthermore, Jianwen has been recognized for his contributions to landscape ecology and technology. His unique combination of scientific research, creative writing, and entrepreneurial skills showcases his diverse expertise and vision for the future.

Awards and Honors 

Jianwen G. has received multiple prestigious accolades throughout his academic and professional career. He was honored with the Best Paper Award at the 13th China-Japan-Korea Geography Conference for his research in landscape ecology and Google Earth Engine. As a doctoral student, Jianwen was awarded the National Inspirational Scholarship for academic excellence and his outstanding contributions to research. He was also recognized as the Excellent League Member of the Year and awarded the title of Outstanding Student Union Officer at the School of Science. His achievements reflect his leadership, dedication, and passion for knowledge. Jianwen’s ability to balance academic rigor with creative pursuits—such as his music career—has further distinguished him, and he continues to make significant contributions in both the academic and entrepreneurial spaces.

Research Focus 

Jianwen G.’s research focuses on the intersection of landscape ecology and digital technology, particularly in the context of farmland abandonment and recultivation dynamics in the Yangtze River Delta, China. His doctoral thesis employs a multiscale analysis using Google Earth Engine, a cutting-edge platform for geospatial analysis, to study the changes in land use and their environmental impacts. His research aims to understand the complex processes of land abandonment and the potential for sustainable land restoration in one of China’s most economically dynamic and ecologically sensitive regions. Jianwen’s work combines traditional ecological concepts with modern technology, providing new insights into how remote sensing and GIS technologies can inform land management strategies. His focus on sustainability, digital tools, and environmental science positions him as a leader in the emerging field of landscape ecology applied to real-world challenges in the face of rapid urbanization.

Publications 

  • “An In-Depth Multiscale Analysis of Farmland Abandonment and Recultivation Dynamics in the Yangtze River Delta, China” 🌱📡
  • “Utilizing Google Earth Engine to Assess Land Use Changes in the Yangtze River Delta” 🌍🌾
  • “Exploring the Role of Remote Sensing in Landscape Ecology: A Case Study from the Yangtze River Delta” 🌐🔬
  • “Sustainable Land Management in China’s Urbanizing Regions: Challenges and Solutions” 🏙️🌍
  • “The Impact of Farmland Abandonment on Local Ecosystems and Economy” 🌿💡
  • “A Comparative Study of Eastern and Western Ecological Restoration Methods” 🌳🌍

Conclusion

Jianwen G. (Bruce Wang) demonstrates a unique and impressive combination of skills that position him as a strong candidate for the Best Researcher Award. His research on farmland abandonment in the Yangtze River Delta, leveraging advanced tools like Google Earth Engine, is scientifically significant and relevant to critical global issues. His entrepreneurial experience and leadership in technology and AI further add to his qualifications, showing his ability to translate research into real-world applications.To further strengthen his candidacy, he could focus more on publishing high-impact, peer-reviewed research, engage in collaborative research projects, and contribute more to academic mentorship. Nonetheless, his innovative interdisciplinary approach, technical expertise, and passion for research make him a very strong contender for the award.With the right focus on academic output and sustained collaboration, Jianwen could emerge as a leader in the field of landscape ecology and sustainability while continuing to leverage his diverse talents and experiences in technology, business, and the arts.

 

Raoudha Ben Djemaa | Computer science | Best Scholar Award

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Prof. Raoudha Ben Djemaa | Computer science | Best Scholar Award

ISITCOM, university of sousse, Tunisia

Raoudha Ben Djemaa, born on March 6, 1976, in Sfax, Tunisia, is a prominent computer science educator and researcher. She is currently a Maître de Conférences (Associate Professor) at the Department of Networks and Multimedia, ISITCOM, University of Sousse, Tunisia. She has extensive experience in computer science education and research, particularly in the areas of web service adaptation, cloud computing, and context-aware systems. Throughout her career, she has also been dedicated to guiding students at various academic levels and contributing to international conferences and journals. 📚💻

Profile

Google Scholar

Education

Raoudha Ben Djemaa’s educational journey began with her Baccalaureate in Experimental Sciences from Lycée secondaire 15 novembre 1959, Sfax, Tunisia, in 1994. She completed her Maîtrise in Computer Science from the Faculty of Economic Sciences and Management of Sfax in 1998 with honors. She later obtained a Master’s degree in Information Systems and New Technologies in 2004 (with distinction, major of her class). She earned her PhD in Computer Science in 2009, with the highest distinction, under the supervision of Prof. Abdelmajid Ben Hamadou. In 2019, she completed her Habilitation Universitaire in Computer Science at the same faculty. 🎓

Experience

Raoudha has held various teaching positions over the years. She has been a Maître de Conférences at ISITCOM since 2020, where she has contributed to the development of curricula in the areas of distributed systems and web programming. Previously, she served as a Maître Assistante (Assistant Professor) and an assistant in several Tunisian institutions. Her earlier career includes teaching secondary school mathematics and computer science. She has also supervised numerous PhD and master’s students, demonstrating her leadership in academic mentorship. 👩‍🏫

Research Interests

Raoudha’s primary research interests include context-sensitive systems, adaptation in web applications, cloud computing, and pervasive computing. She is particularly focused on enhancing web services through semantic similarity measures and self-adaptation techniques for distributed systems. Her work often integrates cloud technologies and the Internet of Things (IoT), with an emphasis on the development of efficient middleware solutions for self-adaptive systems. Her research aims to create smarter, more responsive computing environments. 🌐🔍

Awards

Raoudha has been recognized for her outstanding contributions to computer science education and research. Notably, she has received the distinction of leading several successful doctoral and master’s research projects. Her research on cloud service discovery and self-adaptation in web services has been published in high-impact journals and has garnered international attention. 🏆

Publications Top Notes

Raoudha Ben Djemaa has published several significant articles in prominent journals. Some of her notable publications include:

Finding Internet of Things Resources: A State-of-the-Art Study, Data & Knowledge Engineering, 2022, DOI: 10.1016/j.datak.2022.102025.

Description, Discovery, and Recommendation of Cloud Services: A Survey, Service Oriented Computing and Applications, 2022.

Cloud Services Description Ontology Used for Service Selection, Service Oriented Computing and Applications, 2022.

A Survey of Middlewares for Self-Adaptation and Context-Aware in Cloud of Things Environment, Procedia Computer Science, 2022, DOI: 10.1016/j.procs.2022.09.338.

Enhanced Semantic Similarity Measure Based on Two-Level Retrieval Model, Journal of Concurrency and Computation: Practice and Experience, 2019.

Reflective Approach to Improve Self-Adaptation of Web Service Compositions, International Journal of Pervasive Computing and Communication, 2019.

Efficient Cloud Service Discovery Approach Based on LDA Topic Modeling, Journal of Systems and Software, 2018.

Ali Reza ALAEI | Computer Science | Interdisciplinary Research Excellence Award

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Assist Prof Dr. Ali Reza ALAEI | Computer Science | Interdisciplinary Research Excellence Award

Faculty of Science and Engineering at Southern Cross University, Australia

Dr. Ali Reza Alaei is a PhD graduate specializing in computer science, focusing on Big Data analysis, sentiment extraction, image processing, and biometric systems. With a strong research background and extensive teaching experience, he is currently a Senior Lecturer at Southern Cross University, where he aims to lead impactful research projects and academic initiatives.

Profile 

Scopus profile

Education 🎓

Dr. Alaei obtained his PhD in Computer Science from the University of Mysore, India, in 2012, where his thesis focused on the “Automatic Segmentation of Persian Handwritten Texts Enabling Accurate Recognition.” He also earned a Master’s degree in Computer Science from the same institution in 2007, where he researched the “Recognition of Persian/Arabic Numerals Using Feature Reduction and Distance Measure.”

Experience 🧑‍🏫

With over 20 years of academic experience, Dr. Alaei has held various positions, including Senior Lecturer at Southern Cross University since January 2023 and Lecturer at the same institution from October 2018 to December 2022. His previous roles include Research Fellow at Griffith University, Postdoctoral Research Fellow at LI-RFAI in France, and PhD Scholar at the University of Mysore. His career has been marked by significant contributions to both teaching and research.

Research Interests 🔍

Dr. Alaei’s research interests encompass Big Data analysis, statistical data modeling, human perception modeling, image processing, document image analysis and recognition, and biometric authentication. He aspires to further explore sentiment analysis, human perception understanding, and intelligent technologies through machine learning and vision applications.

Awards 🏆

Dr. Alaei has received several academic honors, including ranking 113th in the national examination of Iranian Universities for B.Sc. entrance and achieving the second rank in his M.Sc. program. He was awarded the best paper award at the International Conference on Cognition and Recognition in 2008 and received accolades for his outstanding performance as a graduate student in India.

Publications 📚

Dr. Alaei has an extensive publication record with 29 journal articles, 39 conference papers, and a total of 70 publications. Some notable peer-reviewed articles include:

  1. Document Image Quality Assessment: A Survey – ACM Computing Survey, 2024. Cited by: 2432.
  2. Review of age and gender detection methods based on handwriting analysis – Neural Computing & Applications, 2023.
  3. Sentiment analysis in tourism: Capitalising on Big Data – Journal of Travel Research, 2019. Cited by: 564.
  4. Revisiting Tourism Destination Image: A Holistic Measurement Framework Using Big Data – Journal of Travel Research, 2022.

Conclusion ✅

Dr. Ali Reza Alaei is an accomplished researcher and educator, dedicated to advancing the fields of Big Data analysis, image processing, and biometrics. With a robust track record of research and teaching, he continues to contribute significantly to academia and the broader scientific community.

Sun Park | Computer Science | Best Research Article Award

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Dr. Sun Park | Computer Science | Best Research Article Award

Research Associate Professor at, Gwangju Institute of Science and Technology, South Korea

Sun Park is a Research Associate Professor at the Graduate School of AI at Gwangju Institute of Science and Technology, a position held since 2013. Her research focuses on data mining, information retrieval, information summarization, convergent marine ICT, smart farming, and IoT-cloud & AI computing. Prior to this role, she served as a Research Professor at Mokpo National University’s Information Industry Research Institute from 2010 to 2013. She also worked as a Full-time Lecturer at Honam University from 2008 to 2010 and as an Adjunct Professor at Hanseo University from 2002 to 2007. Sun Park holds a Ph.D. in Computer Information Engineering from Inha University (2007), a Master’s degree in Information and Communication Engineering from Hannam University (2001), and a Bachelor’s degree in Computer Science from Jeonju University (1996). References are available upon request.

Publication Profile

Strengths for the Award

  1. Extensive Experience in Research and Teaching: Sun Park has over a decade of research and teaching experience, with key positions at prestigious institutions like the Gwangju Institute of Science and Technology, Mokpo National University, Honam University, and Hanseo University. This variety of roles highlights a significant breadth and depth of expertise in the field of Computer Science and Engineering.
  2. Specialized Research Focus: Their research areas, including Data Mining, Information Retrieval, Convergent Marine ICT, IoT-Cloud & AI Computing, and Smart Farm, align well with current and emerging technological trends. This suggests that Sun Park is contributing to forward-thinking, impactful research.
  3. AI and Converging Technologies: As a Research Associate Professor at the Graduate School of AI, Sun Park is in a prime position to lead interdisciplinary projects, bringing together fields like AI, IoT, and smart technologies. These areas are critical for innovation, making their work relevant for contemporary challenges.
  4. Strong Academic Background: Holding a Ph.D. in Computer Information Engineering and advanced degrees in Information and Communication Engineering, Sun Park’s academic credentials demonstrate a high level of expertise. The progression from a Bachelor’s to a Ph.D. showcases a long-standing commitment to the field.
  5. Institutional Impact: Serving in high-ranking academic roles implies that Sun Park has contributed to shaping research strategies, mentoring students, and advancing their institution’s academic reputation, which is a critical factor for awards that recognize leadership in research.

Areas for Improvement

  1. Lack of Specific Research Achievements: The provided profile does not detail significant publications, patents, or specific innovations. A more robust record of high-impact publications or citations would strengthen Sun Park’s candidacy for the Best Researcher Award. Highlighting specific projects or research grants won would also add weight.
  2. Global Collaboration and Visibility: While the candidate is clearly well-established in South Korea, a stronger record of international collaborations, keynote speeches, or participation in global conferences would further elevate their profile. Visibility in international research communities is often crucial for award considerations.
  3. Applied Outcomes or Industry Impact: While the research areas are impressive, the profile does not specify applied outcomes or how these research fields have impacted industries or society. Showcasing tangible applications of research (e.g., how IoT solutions have benefited smart farms or marine industries) would demonstrate real-world influence.

Education:

Sun Park holds a Ph.D. in Computer Information Engineering from Inha University, earned between 2002 and 2007, which forms the foundation of their advanced expertise in computer science. Prior to this, they completed a Master’s degree in Information and Communication Engineering at Hannam University from 1997 to 2001. This followed a Bachelor’s degree in Computer Science from Jeonju University, obtained between 1992 and 1996. This strong academic background, progressing from undergraduate to doctoral levels, demonstrates a deep and comprehensive education in computing and engineering disciplines.

Experience:

Sun Park has over two decades of academic and research experience, spanning various prestigious roles in South Korea. Currently serving as a Research Associate Professor at the Graduate School of AI at Gwangju Institute of Science and Technology, they focus on cutting-edge research in areas like Data Mining, Information Retrieval, Convergent Marine ICT, IoT-Cloud & AI Computing, and Smart Farm technologies. Previously, they held positions as a Research Professor at Mokpo National University and a Full-time Lecturer at Honam University. Sun Park’s academic journey, from earning a Ph.D. in Computer Information Engineering to holding multiple teaching and research roles, reflects a deep and broad expertise in computer science, with a strong commitment to innovation in AI and emerging technologies.

Research Focus:

Sun Park’s research focuses on several cutting-edge fields, including Data Mining, Information Retrieval, Information Summarization, Convergent Marine ICT, Smart Farming, and IoT-Cloud & AI Computing. This diverse range of interests demonstrates a commitment to advancing both theoretical and practical applications in technology. Their work bridges multiple domains, with a particular emphasis on integrating AI and IoT for innovative solutions in areas like agriculture and marine industries. By focusing on emerging technologies and their real-world implications, Sun Park’s research contributes to solving contemporary challenges in information management and intelligent systems.

Awards and Honors:

Sun Park’s awards and honors are not specifically listed in the provided profile. However, their notable academic positions, such as Research Associate Professor at the Graduate School of AI, Gwangju Institute of Science and Technology, and past roles at Mokpo National University and Honam University, suggest recognition of their expertise and leadership in their field. These roles reflect a high level of academic and research achievement, although further details on specific awards, honors, or recognitions would provide a clearer understanding of their accolades. Highlighting any formal awards or distinctions would strengthen their profile for the Best Researcher Award.

Publication Top Notes:

  • Design of Vessel Data Lakehouse with Big Data and AI Analysis Technology for Vessel Monitoring System
    • Authors: Park, S., Yang, C.-S., Kim, J.
    • Year: 2023
    • Citations: 6
  • Design and Implementation of Data Concentrator Unit supported with Multiple Synchronized Cameras for Object-Detection
    • Authors: Anvarjon, Y., Park, S., Kim, J.
    • Year: 2023
    • Citations: 0
  • Concept Design of Intelligent BoP Based on Slot-/Rack-type Fuel Cell for Integrated Management of Hydrogen Fuel Cells
    • Authors: Park, S., Chung, B.-J., Kim, J.
    • Year: 2023
    • Citations: 1
  • Correction to: Design of containerized marine knowledge system based on IoT-Cloud and LoRaWAN
    • Authors: Park, S., Ling, T.C., Cha, B.R., Kim, J.W.
    • Year: 2022
    • Citations: 1
  • Design of containerized marine knowledge system based on IoT-Cloud and LoRaWAN
    • Authors: Park, S., Ling, T.C., Cha, B.R., Kim, J.W.
    • Year: 2022
    • Citations: 3

Conclusion:

Sun Park’s extensive academic experience, specialized focus in key technological areas, and position within a prominent research institution make them a strong candidate for a research award. However, to be highly competitive for a Best Researcher Award, it would be beneficial for them to highlight specific high-impact research achievements, international collaborations, and real-world applications of their work. These additions would showcase a broader influence in both academic and industrial sectors, further solidifying their candidacy for this prestigious recognition.

Alex Mirugwe | Computer Science | Young Scientist Award

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Mr. Alex Mirugwe | Computer Science | Young Scientist Award

Data Scientist at Makerere University, School of Public Health, Uganda

Alex Mirugwe is a highly skilled Data Scientist with over 4 years of experience, specializing in applying machine learning and AI to healthcare challenges, particularly in HIV, cancer, and tuberculosis diagnostics. He has a proven track record of developing data-driven solutions that improve patient outcomes in resource-constrained settings. His research has been published in several peer-reviewed journals, and he is proficient in a wide range of data science tools and methodologies. Alex also contributes to academia as an Assistant Lecturer and is involved in curriculum development and student mentoring in computer science.

Profile:

Strengths for the Award:

  1. Specialized Expertise in Healthcare Data Science: Alex Mirugwe has developed machine learning models and AI tools to solve critical health challenges, such as HIV patient care and cervical cancer detection. His work is not only technically sound but has made tangible impacts on healthcare delivery in resource-constrained environments.
  2. Research Contributions and Publications: Alex has authored multiple peer-reviewed journal articles on healthcare applications of AI, including sentiment analysis of public health data, tuberculosis detection, and cancer screening. These publications demonstrate his commitment to advancing the application of AI in public health and data science.
  3. Experience in Machine Learning and AI: His technical expertise spans a range of relevant tools and techniques, including deep learning, transfer learning, and predictive modeling, which are crucial for impactful healthcare interventions. His experience in both teaching and research also ensures that his knowledge is applied and shared within the academic community.
  4. Proven Success in Real-World Applications: Alex’s work on reducing HIV patient data duplication, predicting HIV patient outcomes, and improving cervical cancer screening speaks to his practical problem-solving skills in high-stakes environments. The use of AI to improve healthcare decision-making is well-aligned with global trends toward technology-driven health solutions.
  5. Cross-Disciplinary and Global Approach: Alex’s education, spanning institutions in Uganda and South Africa, and his research interests in global health issues, reflect his broad outlook. His involvement with international collaborators highlights his ability to bridge different disciplines and apply his knowledge across borders.

Areas for Improvement:

  1. More Diverse Research Focus: While Alex has concentrated on significant healthcare issues, expanding his research beyond HIV, cancer, and tuberculosis may enhance his portfolio. Including more work in diverse fields, such as environmental health or genomics, would add breadth to his achievements.
  2. Leadership in Research Projects: Alex has demonstrated technical prowess and teaching capabilities, but more emphasis on leadership roles in large-scale research projects or interdisciplinary initiatives could elevate his profile. Leading a significant multi-institutional study or directing larger research teams may help solidify his standing.
  3. Policy and Implementation Impact: Though Alex has made practical contributions, more evidence of his work leading to large-scale policy changes or national-level healthcare implementations could further strengthen his application. This would demonstrate how his AI models or algorithms scale to influence public health strategies at a systemic level.
  4. International Research Collaborations: Although his work is impactful within Uganda, expanding collaborations with more international research institutes or global health organizations could further enhance his visibility and contribution to global health initiatives.

 

Education:

Alex Mirugwe holds an MSc in Data Science from the University of Cape Town, South Africa, completed in 2021, where he conducted research on automated bird detection using machine learning. His academic performance was strong, with a GPA of 74.52%. Prior to this, he earned a BSc in Computer Engineering from Makerere University, Uganda, in 2019, graduating with a CGPA of 4.18/5.0. His undergraduate dissertation focused on developing a low-cost wireless TV audio transceiver, reflecting his early interest in applying engineering principles to real-world problems. His educational background combines technical proficiency in computer science with a strong emphasis on data science and machine learning applications.

Experience:

Alex Mirugwe is a highly skilled data scientist with over four years of experience applying machine learning and AI to healthcare challenges, particularly in diagnosing HIV, cancer, and tuberculosis. He has successfully developed predictive models to improve patient care and outcomes in resource-limited settings, such as creating algorithms for cervical cancer screening and reducing HIV patient data duplication. His work spans both practical implementation and academic research, with multiple publications on AI-driven health interventions. In addition to his research, Alex is an experienced educator, teaching data science and machine learning courses at the university level.

Research Focus:

Alex Mirugwe’s research focuses on leveraging data science and machine learning to address critical healthcare challenges, particularly in resource-constrained settings. His work encompasses developing predictive models for patient care in HIV treatment, enhancing cervical cancer screening accuracy through AI algorithms, and analyzing public sentiment during health crises, such as the Ebola outbreak. Additionally, he explores various applications of AI in public health, including improving tuberculosis detection and reducing data duplication in electronic medical records. Overall, his research aims to harness advanced data analytics to improve patient outcomes and inform public health strategies, making significant contributions to the field of healthcare data science.

Publications Top Notes:

  • Automating Bird Detection Based on Webcam Captured Images Using Deep Learning
    • Authors: A. Mirugwe, J. Nyirenda, E. Dufourq
    • Year: 2022
    • Citations: Not specified in the provided information.
  • Restaurant Tipping Linear Regression Model
    • Author: A. Mirugwe
    • Year: 2020
    • Citations: Not specified in the provided information.
    • Link: SSRNPaper
  • Sentiment Analysis of Social Media Data on Ebola Outbreak Using Deep Learning Classifiers
    • Authors: A. Mirugwe, C. Ashaba, A. Namale, E. Akello, E. Bichetero, E. Kansiime, J. Nyirenda
    • Year: 2024
    • Citations: Not specified in the provided information.
    • Journal: Life, 14(6), 708.
  • Adoption of Artificial Intelligence in the Ugandan Health Sector: A Review of Literature
    • Author: A. Mirugwe
    • Year: 2024
    • Citations: Not specified in the provided information.
    • Link: Available at SSRN 4735326.

Conclusion:

Alex Mirugwe presents an impressive and well-rounded portfolio, with extensive experience in applying machine learning and AI to tackle critical healthcare challenges. His achievements, particularly in HIV care and cancer screening, demonstrate his ability to leverage data science for real-world health outcomes. While he has a strong research and technical background, focusing on leadership, broadening his research scope, and contributing to systemic policy changes could bolster his case further. He is a strong candidate for the Best Researcher Award, especially within the domain of AI-driven healthcare solutions in resource-constrained settings.

Miin-Shen Yang | Computer Science | Best Researcher Award

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Prof Dr. Miin-Shen Yang | Computer Science | Best Researcher Award

Distinguished Professor,Chung Yuan Christian University, Taiwan

👨‍🏫 Miin-Shen Yang is a distinguished scholar and professor specializing in applied mathematics and artificial intelligence. He has made significant contributions to fuzzy clustering, machine learning, and soft computing. Currently serving as a Life Distinguished Professor at Chung Yuan Christian University (CYCU), Taiwan, Dr. Yang is highly regarded in the scientific community for his innovative research. He is also recognized among the top 0.5% of scholars globally by ScholarGPS and Stanford University’s Top 2% Scientists.

Publication Profile

ORCID

Strengths for the Award:

  1. Extensive Academic Background: Miin-Shen Yang has earned degrees in mathematics and statistics from prestigious institutions, with a Ph.D. from the University of South Carolina, USA. His long-standing association with Chung Yuan Christian University (CYCU), Taiwan, adds to his academic credibility.
  2. Research Impact: His research areas—statistics, clustering algorithms, fuzzy clustering, soft computing, pattern recognition, and machine learning—are crucial in modern scientific and technological advancements, especially in the AI-driven era.
  3. Global Recognition: Miin-Shen Yang’s inclusion in Stanford University’s Top 2% Scientists and ScholarGPS’s global top 0.5% demonstrates the international recognition of his work and significant contributions to artificial intelligence, image processing, and related fields.
  4. Editorial Roles: He served as an Associate Editor for IEEE Transactions on Fuzzy Systems and remains on the Editorial Board of Electronics (MDPI). These roles show his influence in shaping scientific discourse in his fields of expertise.
  5. Leadership in Academia: As a Distinguished Professor and previous Chairperson and Dean of the College of Science at CYCU, he has demonstrated not only research expertise but also leadership in academic governance.

Areas for Improvement:

  1. Broader Collaborations: While Miin-Shen Yang’s contributions are notable in the fields of applied mathematics and artificial intelligence, there could be a stronger emphasis on collaborative projects across interdisciplinary fields such as biostatistics or environmental data science, which are becoming increasingly critical for global research challenges.
  2. Applied Research and Industry Connections: Strengthening connections between his academic research and real-world industrial applications could further enhance the societal impact of his work, especially in sectors like healthcare, energy, or environmental sustainability where AI and machine learning are emerging as transformative tools.
  3. Public Engagement and Outreach: Additional efforts to disseminate his research through public engagement activities, workshops, or conferences that target both academic and non-academic audiences could raise the visibility and practical applicability of his findings.

Education

🎓 Miin-Shen Yang holds a B.S. in Mathematics from Chung Yuan Christian University (1977), an M.S. in Applied Mathematics from National Chiao-Tung University (1980), and a Ph.D. in Statistics from the University of South Carolina, Columbia, USA (1989).

Experience

💼 Dr. Yang joined CYCU in 1989 and became a Professor in 1994. He has held several key positions, including Department Chair, Director of the Chaplain’s Office, and Dean of the College of Science. He also served as a Visiting Professor at the University of Washington from 1997 to 1998.

Research Focus

🔬 Dr. Yang’s research interests span applications of statistics, fuzzy clustering, machine learning, soft computing, pattern recognition, and artificial intelligence. His contributions have significantly advanced clustering algorithms and AI-related technologies.

Awards and Honors

🏅 Dr. Yang has been recognized among Stanford University’s Top 2% Scientists and listed among ScholarGPS global top 0.5% scholars. He has also served as an Associate Editor for IEEE Transactions on Fuzzy Systems and is currently an Editorial Board Member for the journal Electronics.

Publications (Top Notes)

📚 Dr. Yang has published extensively on fuzzy clustering and artificial intelligence in leading journals. His works have been widely cited, marking his influence in the field.

“Fuzzy Clustering Algorithms and Applications” – Published in 2015 in Pattern Recognition Letters. Cited by 100+ articles

Conclusion:

Miin-Shen Yang is an exceptional candidate for the Research for Best Research Award, with a strong and diversified research portfolio in applied mathematics, artificial intelligence, and machine learning. His global recognition, academic leadership, and editorial contributions demonstrate his significant impact on the scientific community. While further strengthening his research collaborations across broader disciplines and emphasizing real-world applications could enhance his overall impact, his current achievements make him a highly competitive and deserving nominee for the award.

Changqing Xia | Computer Science | Best Researcher Award

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Prof. Changqing Xia | Computer Science | Best Researcher Award

Researcher, Shen Zi Institute, Chinese Academy of Sciences, China

Dr. Changqing Xia is a leading researcher in the fields of cyber–physical systems, artificial intelligence (AI), and network computation. He has focused his career on advancing the integration of computing, communication, and control in smart manufacturing systems. Dr. Xia’s expertise lies in developing AI-driven solutions that optimize resource allocation, network scheduling, and real-time data management in industrial environments. With numerous publications in prestigious journals, Dr. Xia is at the forefront of intelligent system design and advanced production technologies.

Profile

Orcid

Strengths for the Award

Dr. Changqing Xia demonstrates outstanding contributions to the fields of cyber–physical systems (CPS), artificial intelligence, and network scheduling, particularly with a focus on industrial applications. His recent works such as Deterministic Network–Computation–Manufacturing Interaction Mechanism for AI-Driven Cyber–Physical Production Systems and Co-Design of Control, Computation, and Network Scheduling Based on Reinforcement Learning illustrate his innovative approach to merging computation with physical manufacturing environments. His expertise in using AI, reinforcement learning, and computational intelligence to improve production systems and real-time scheduling significantly advances the field. Moreover, his research on 5G-based positioning and data scheduling under mixed-criticality scenarios provides solutions to current industrial challenges, making him a forward-looking researcher whose work is at the cutting edge of smart manufacturing and industrial automation. His ability to integrate multiple domains such as control, communication, and computing positions him as a highly versatile and impactful researcher.

Areas for Improvement

While Dr. Xia’s research portfolio is robust, focusing on a broader application of his methodologies across different industries, outside of cyber-physical production systems, could further expand the impact of his work. His publications heavily concentrate on industrial environments, but applying his AI-driven methods to fields like healthcare, smart cities, or autonomous systems could diversify his research impact. Additionally, greater collaboration with other interdisciplinary fields could bring fresh perspectives and opportunities for expanding his work into more novel, groundbreaking areas. Another area of improvement could be increasing public engagement or educational outreach, which would help communicate his research more broadly to a non-specialist audience.

Publications Top Notes:

  1. Deterministic Network–Computation–Manufacturing Interaction Mechanism for AI-Driven Cyber–Physical Production Systems
    IEEE Internet of Things Journal (2024-05-15)
    DOI: 10.1109/JIOT.2024.3367350
  2. Co-Design of Control, Computation, and Network Scheduling Based on Reinforcement Learning
    IEEE Internet of Things Journal (2024-02-01)
    DOI: 10.1109/JIOT.2023.3305708
  3. A Self-Triggered Approach for Co-Design of MPC and Computing Resource Allocation
    IEEE Internet of Things Journal (2024)
    DOI: 10.1109/JIOT.2024.3392563
  4. Computational-Intelligence-Based Scheduling with Edge Computing in Cyber–Physical Production Systems
    Entropy (2023-12)
    DOI: 10.3390/e25121640
  5. Control–Communication–Computing Co-Design in Cyber–Physical Production System
    IEEE Internet of Things Journal (2023-03-15)
    DOI: 10.1109/JIOT.2022.3221932
  6. Indoor Fingerprint Positioning Method Based on Real 5G Signals
    Conference Paper (2023-01-05)
    DOI: 10.1145/3583788.3583819
  7. Mixed-Criticality Industrial Data Scheduling on 5G NR
    IEEE Internet of Things Journal (2022-06-15)
    DOI: 10.1109/JIOT.2021.3121251
  8. Real-Time Scheduling of Massive Data in Time Sensitive Networks With a Limited Number of Schedule Entries
    IEEE Access (2020)
    DOI: 10.1109/ACCESS.2020.2964690

Conclusion

Dr. Changqing Xia is a strong candidate for the “Best Researcher Award” due to his significant contributions to the fields of AI, network computation, and industrial CPS. His research innovations in optimizing industrial systems through cutting-edge computational and network scheduling methods provide solutions to contemporary challenges in smart manufacturing and data-intensive environments. With minor refinements in expanding his interdisciplinary reach and public engagement, Dr. Xia’s already impactful work could lead to even broader recognition in both the academic and industrial spheres. His achievements reflect not only technical depth but also practical applicability, making him highly deserving of this prestigious award.