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

 

Eduardo Coronel | Computer Science | Best Researcher Award

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Dr. Eduardo Coronel | Computer Science | Best Researcher Award

M.Sc. Eng. at Facultad Politécnica,  Paraguay

Eduardo Damián Coronel Torales, born on March 5, 1991, in Asunción, Paraguay, is a distinguished researcher and engineer specializing in electrical engineering, automation, and artificial intelligence applications. He has actively contributed to academia, industry, and international conferences, earning recognition for his innovative work in energy distribution and automation systems. His professional journey has taken him from academic research to practical implementations in one of the world’s largest hydroelectric plants, Itaipu Binacional. With a strong foundation in engineering and computational intelligence, Coronel Torales has made significant contributions to optimizing power distribution and developing automation solutions. His research extends beyond Paraguay, reaching international platforms and collaborations. He continues to push the boundaries of technology by integrating advanced optimization techniques, machine learning, and smart grid systems, positioning himself as a leader in his field.

Professional Profile

Education

Coronel Torales holds a Master’s degree in Electrical Engineering with an emphasis on Energy Systems Planning from the Facultad Politécnica of the Universidad Nacional del Este, obtained in 2021. His postgraduate research focused on optimizing power distribution using computational intelligence. He completed his undergraduate degree in Electronics Engineering with a specialization in Mechatronics at the Universidad Nacional de Asunción in 2017. During his academic career, he demonstrated exceptional analytical and problem-solving skills, engaging in multiple research projects related to automation, robotics, and energy systems. His academic journey reflects a strong commitment to technological advancements and interdisciplinary research. The combination of these degrees has provided him with a robust foundation in both theoretical and practical aspects of energy optimization, artificial intelligence, and industrial automation, equipping him with the expertise to tackle complex engineering challenges at both research and industrial levels.

Professional Experience

With extensive experience in academia and industry, Coronel Torales has worked as a research engineer at Itaipu Binacional, contributing to the modernization of automation systems. His expertise in failure analysis using PI tools and machine learning models has been instrumental in enhancing the reliability of large-scale energy infrastructure. He has also served as a postgraduate lecturer at the Universidad Nacional del Este, teaching heuristic optimization methods. Additionally, he has worked as an instructor at the Paraguay-Korea Advanced Technology Center (SNPP-KOICA), where he trained professionals in digital electronics and industrial automation. His work experience blends research, teaching, and industry applications, allowing him to bridge the gap between theory and practice. Through his diverse roles, he has been actively involved in developing intelligent systems, optimizing automation processes, and mentoring students and professionals in engineering disciplines.

Research Interests

Coronel Torales’ research interests lie at the intersection of power systems optimization, automation, and artificial intelligence. He has extensively explored the use of metaheuristic and multi-objective optimization techniques for enhancing the efficiency of electrical power distribution systems. His research also focuses on computer vision, machine learning, and control systems, particularly for applications in autonomous vehicles, industrial automation, and smart grids. Additionally, he is interested in the integration of AI-driven fault detection and predictive maintenance in large-scale energy infrastructures. His work contributes to improving the reliability and efficiency of energy management systems through data-driven solutions. By combining engineering principles with computational intelligence, he aims to develop sustainable and intelligent solutions for modern energy challenges. His forward-thinking research aligns with global trends in smart energy systems, IoT-enabled automation, and digital transformation in power distribution networks.

Awards and Honors

Coronel Torales has received international recognition for his research contributions, including multiple conference presentations at IEEE and other prestigious platforms. His work on remote-controlled switch optimization in power distribution systems has been published in IEEE Latin America Transactions and presented at international computing and engineering conferences such as CLEI, ICDIM, and INTERCON. He has been acknowledged for his contributions to automation failure analysis at Itaipu Binacional, influencing modernization decisions in one of the world’s largest hydroelectric plants. Additionally, his early research in autonomous vehicle navigation and fuzzy logic control earned him invitations to research symposiums in Argentina, Peru, South Korea, and the United States. His ability to translate research into practical applications has cemented his reputation as an emerging leader in electrical engineering and computational intelligence. His continued contributions are setting a benchmark for innovation in energy systems and industrial automation.

Conclusion

Eduardo Damián Coronel Torales has a strong research background with impactful contributions in energy systems optimization, automation, and AI applications. His publications, international recognition, and industry collaboration make him a strong candidate for the Best Researcher Award. However, to further strengthen his candidacy, he should aim for higher-impact journal publications, more independent research leadership, and broader contributions in emerging fields.

Publications Top Noted

  • Coronel, E., Barán, B., & Gardel, P. (2025). A Survey on Data Mining for Data-Driven Industrial Assets Maintenance Technologies. Journal article. DOI: 10.3390/technologies13020067.
  • Coronel Torales, E. D. (2024). Leveraging Machine Learning for Multi-Step Failure Forecasting in RTU Analog Modules and Estimating Key Performance Indicators to Support Management Decision-Making. CIGRE Paris Session 2024, Conference poster.
  • Coronel, E., Barán, B., & Gardel, P. (2022). Optimal Placement of Remote Controlled Switches in Electric Power Distribution Systems with a Meta-heuristic Approach. IEEE Latin America Transactions. DOI: 10.1109/TLA.2022.9675464.
  • Coronel Torales, E. D. (2021). Optimal Placement of Remote Controlled Switches in Electric Power Distribution Systems with a Multi-Objective Approach. 2021 XLVII Latin American Computing Conference (CLEI). DOI: 10.1109/clei53233.2021.9639970.
  • Coronel Torales, E. D. (2020). Optimización en la Ubicación de Seccionadores Tele-comandados en Sistemas de Distribución de Energía Eléctrica con enfoque meta-heurístico y soporte de decisión multi-criterio. Edited book. DOI: 10.13140/RG.2.2.32305.92002.
  • Coronel Torales, E. D. (2017). Estimación de disponibilidad de energía eléctrica de la Central Hidroeléctrica Itaipú y del crecimiento de la energía cedida al Paraguay hasta el 2023. Facultad Politécnica – Universidad Nacional del Este. DOI: 10.13140/RG.2.2.11838.79685.
  • Coronel Torales, E. D. (2015). Reliable navigation-path extraction system for an autonomous mobile vehicle. 2015 Tenth International Conference on Digital Information Management (ICDIM). DOI: 10.1109/icdim.2015.7381882.
  • Coronel Torales, E. D. (2015). PROTOTIPO DE VEHÍCULO AUTÓNOMO CON RNA Y VISIÓN POR COMPUTADORA. Simposio Argentino de Sistema Embebidos (SASE), Conference poster.
  • Coronel Torales, E. D. (2015). SISTEMA DE ALGORITMOS DE VISIÓN POR COMPUTADOR, APRENDIZAJE DE MÁQUINA, LOCALIZACIÓN Y NAVEGACIÓN DESARROLLADOS EN MATLAB, CON IMPLEMENTACIÓN EN VEHÍCULOS TERRESTRES PARA AUTO-CONDUCCIÓN. XXII Congreso Internacional de Ingeniería Eléctrica, Electrónica, Computación y Afines INTERCON 2015, Conference paper.
  • Coronel Torales, E. D. (2014). STABILITY COMMAND OF A TILT-ROTOR VEHICLE WITH A FUZZY LOGIC CONTROLLER. 3rd Conference of Computational Interdisciplinary Sciences – CCIS 2014, Conference poster. ISBN: 978-85-68888-00-1.
  • Coronel Torales, E. D. (2014). BALANCEADOR AERODINÁMICO CON LÓGICA DIFUSA. XXI Congreso Internacional de Ingeniería Electrónica, Eléctrica y Computación INTERCON 2014, Conference poster.

 

 

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.