XinYing Chew | Computer Science | Young Scientist Award

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

 

Rishabh Anand | Computer Science | Best Researcher Award

Dr. Rishabh Anand | Computer Science | Best Researcher Award

Associate Vice President at India

Dr. Rishabh Anand is a distinguished professional with over 19 years of experience spanning technology, business management, and academia. His expertise lies in program and delivery management, strategic leadership, and digital transformation, with a strong foundation in IT and education. As a thought leader, he has successfully integrated academic theories with real-world business applications, fostering innovation and excellence. His global experience across the USA, UK, India, Denmark, France, the Middle East, and ASEAN has given him a unique perspective on technology and business evolution. Dr. Anand is known for his mentorship and coaching abilities, shaping the next generation of professionals and students through his academic and industry engagements. His ability to drive strategic initiatives, coupled with his passion for education and research, has positioned him as a leader in the fields of artificial intelligence, machine learning, and digital transformation.

Professional Profile

Education

Dr. Rishabh Anand has an impressive academic background with multiple degrees spanning technology, management, and psychology. He earned his B.E. in Electronics and Communication Engineering from Dronacharya College of Engineering, MDU, in 2006. His passion for advanced technical research led him to pursue an M.Tech in Electronics and Communication Engineering from the Indian Institute of Technology (IIT), Delhi, in 2010. Expanding his expertise into business and finance, he completed an MBA in Finance from New York University (NYU) in 2014. Understanding the significance of human behavior in technology and business, he pursued an MS in Psychology from the University of Texas at Dallas in 2016. His dedication to research culminated in a Ph.D. in Computer Science from the University of Bristol, UK, in 2020. Further solidifying his expertise, he completed a dual postdoctoral degree in Artificial Intelligence and Machine Learning from São Paulo State University, Brazil, in 2024.

Professional Experience

Dr. Anand has an extensive professional career, demonstrating expertise in global technology, business strategy, and academic leadership. He has been a key figure at Google India Private Limited since 2006, leading strategic initiatives, managing multi-million-dollar IT projects, and driving digital transformation across various industries. As a Program and Delivery Manager, he has played a pivotal role in managing large-scale engineering teams, ensuring efficiency, innovation, and profitability. His work spans industries such as airlines, pharmaceuticals, financial services, FMCG, tourism, logistics, and technology. He has successfully transitioned over 350-400 roles globally, demonstrating his expertise in workforce transformation and leadership. In academia, he has mentored students and professionals, bridging the gap between theoretical learning and industry expectations. His extensive experience working with C-suite executives and leading digital initiatives has established him as a global thought leader in technology-driven business solutions.

Research Interest

Dr. Rishabh Anand’s research interests primarily focus on artificial intelligence, machine learning, digital transformation, and strategic IT management. His work revolves around integrating cutting-edge AI and ML technologies into business strategies to enhance efficiency, automation, and customer experience. He is deeply invested in enterprise IT strategies, cybersecurity, cloud computing, and predictive analytics, ensuring that businesses stay ahead in the digital era. His interest in digital transformation includes process automation, technology adoption in organizations, and data-driven decision-making frameworks. With his background in psychology, he also explores human-computer interaction, cognitive computing, and behavioral AI. Through his published case studies and academic collaborations, Dr. Anand continues to contribute valuable insights into how AI and digital solutions can drive innovation and economic growth. His research aims to bridge the gap between academia and industry, ensuring that emerging technologies align with real-world business challenges.

Awards and Honors

Dr. Rishabh Anand has received multiple awards and recognitions for his contributions to technology, research, and academia. He was recognized for his excellence in digital transformation and IT strategy at Google India, where he led high-impact projects, driving profitability and innovation. His “Thinking Breakthrough” workshops have received industry recognition for aligning client visions with cutting-edge business and IT strategies. As a dedicated mentor, he has been honored for his contributions to student career development and academic excellence. His research publications on AI, digital transformation, and strategic IT management have been acknowledged in international conferences and journals. Dr. Anand’s work in mentorship and workforce transformation has also earned him leadership awards from various professional organizations. With a stellar career spanning technology, business, and academia, he continues to be an influential figure in shaping the future of AI, machine learning, and enterprise IT solutions.

Conclusion

Dr. Rishabh Anand is a strong contender for the Best Researcher Award, given his significant contributions to research, industry-academia collaboration, and leadership in digital transformation. Strengthening his publication record and patents could further solidify his case as an outstanding researcher.

Publications Top Noted

Industry 4.0 Technologies

Author: Dr. Rishabh Anand (2025)
Publisher: S Chand and Company Ltd

Smart Factories for Industry 5.0 Transformation (Industry 5.0 Transformation Applications)

Authors: Dr. Rishabh Anand, R. Nidhya, Manish Kumar, S. Karthik, S. Balamurugan (2025)
Publisher: Wiley-Scrivener

Foundation Course in Universal Human Values and Professional Ethics

Author: Dr. Rishabh Anand (2025)
Publisher: CBS Publishers and Distributors Pvt. Ltd.

Blockchain Technology

Author: Dr. Rishabh Anand (2023)
Publisher: Khanna Publishers

Computer Organization and Architecture (Designing for Performance)

Authors: Dr. Rishabh Anand, R.S. Salaria (2023)
Publisher: Khanna Publishers

Digital Signal Processing: An Introduction

Author: Dr. Rishabh Anand (2022)
Publisher: Mercury Learning & Information

Wireless Communication

Author: Dr. Rishabh Anand (2022)
Publisher: S Chand And Company Ltd

An Integrated Approach to Software Engineering

Author: Dr. Rishabh Anand (2021)
Publisher: Khanna Publishers

Digital Signal Processing

Author: Dr. Rishabh Anand (2021)
Publisher: Khanna Publishers

Object-Oriented Programming using C++

Author: Dr. Rishabh Anand (2021)
Publisher: Khanna Publishers

Optical Fiber Communications

Author: Dr. Rishabh Anand (2021)
Publisher: Khanna Publishers

Satellite Communications

Author: Dr. Rishabh Anand (2021)
Publisher: Khanna Publishers

Nanotechnology

Author: Dr. Rishabh Anand (2020)
Publisher: Khanna Publishers

Digital Electronics

Author: Dr. Rishabh Anand (2019)
Publisher: Khanna Book Publishing Company

Signals and Systems

Author: Dr. Rishabh Anand (2018)
Publisher: Khanna Book Publishing Company

Mobile Computing

Author: Dr. Rishabh Anand (2017)
Publisher: Khanna Publishers

Computer Networks

Author: Dr. Rishabh Anand (2016)
Publisher: Satya Prakashan

Linear Integrated Circuits

Author: Dr. Rishabh Anand (2014)
Publisher: Khanna Book Publishing Company

Electromagnetic Field Theory

Author: Dr. Rishabh Anand (2013)
Publisher: Khanna Book Publishing Company

Computer Graphics

Author: Dr. Rishabh Anand (2013)
Publisher: Khanna Book Publishing Company

Digital System Design Using VHDL

Author: Dr. Rishabh Anand (2013)
Publisher: Khanna Book Publishing Company

Intelligent Instrumentation for Engineers

Author: Dr. Rishabh Anand (2013)
Publisher: Khanna Book Publishing Company

Software Project Management

Author: Dr. Rishabh Anand (2013)
Publisher: S K Kataria and Sons

Wireless and Mobile Computing

Author: Dr. Rishabh Anand (2013)
Publisher: S K Kataria and Sons

Network Management

Author: Dr. Rishabh Anand (2012)
Publisher: Not Specified

Neural Networks

Author: Dr. Rishabh Anand (2012)
Publisher: Satya Prakashan

Communication Systems: Analog and Digital

Author: Dr. Rishabh Anand (2011)
Publisher: Khanna Book Publishing Company

 

Xiaolin Yang | Machine learning | Best Researcher Award

Dr. Xiaolin Yang | Machine learning | Best Researcher Award

China university of mining and technology, China

📈 Xiaolin Yang is a highly skilled Business Analyst with a Ph.D. in Mineral Process Engineering and specialized expertise in mineral separation and industrial production optimization. Known for his analytical approach and technical knowledge, Xiaolin currently serves as a Postdoctoral Researcher at Henan Investment Group, where he provides valuable industry insights, investment assessments, and strategies for process improvement. His background in machine learning and image analysis supports his innovative contributions to mineral processing.

Publication Profile

ORCID

Education

🎓 Xiaolin Yang completed his Bachelor’s degree in Mineral Process Engineering at China University of Mining and Technology (2015-2019) and later earned a Doctorate in the same field from the same institution (2019-2024). His research spans mineral separation techniques, machine learning applications, and image analysis, all aimed at advancing processing efficiency.

Experience

💼 Xiaolin is currently a Postdoctoral Researcher at Henan Investment Group, where he contributes to industry research, investment evaluation, and production optimization. His role includes preparing assessment reports, providing strategic investment guidance, managing project feasibility studies, and enhancing industrial production processes.

Research Focus

🔬 Xiaolin’s research focuses on mineral processing, applying machine learning and image analysis to improve separation processes and equipment. His studies advance understanding of mineral properties and optimization techniques, contributing to the field’s progression toward smarter, data-driven methodologies.

Awards and Honors

🏅 Xiaolin has been recognized for his contributions to mineral process engineering, having published in prominent journals like Journal of Materials Research and Technology and Expert Systems with Applications. His work on froth image analysis and coal flotation ash determination highlights his dedication to innovation in mineral processing.

Publication Highlights

A comparative study on the influence of mono, di, and trivalent cations on chalcopyrite and pyrite flotation (2021). Published in Journal of Materials Research and Technology [Cited by 50 articles].

Ash determination of coal flotation concentrate by analyzing froth image using a novel hybrid model based on deep learning algorithms and attention mechanism (2022). Published in Energy [Cited by 35 articles].

Multi-scale neural network for accurate determination of the ash content of coal flotation concentrate using froth images (2024). Published in Expert Systems with Applications [Cited by 20 articles].

Arunabh Bora | Machine Learning | Best Researcher Award

Mr. Arunabh Bora | Machine Learning | Best Researcher Award

AI Engineer, UTAP Tech, United Kingdom

🌟 Arunabh Bora is an innovative Artificial Intelligence Engineer currently at UTAP Tech, Louth, United Kingdom, specializing in cutting-edge computer vision and machine learning solutions. With a background in electronics, robotics, and autonomous systems, he brings a unique skill set to AI-driven problem-solving in agricultural and medical domains. His passion for tech is reflected in his hands-on experience with deep learning models and reinforcement learning for various applications. 💻🔬

Publication Profile

Google Scholar

Education

🎓 Arunabh holds a Master of Science in Robotics and Autonomous Systems (Distinction) from the University of Lincoln, UK, where he earned 95% on his dissertation exploring Large Language Models for medical chatbot applications. He also completed a Bachelor of Technology in Electronics and Communication Engineering from Gauhati University, India, where he published two research papers on IoT and machine learning for agriculture. 📚🌾

Experience

💼 As an Artificial Intelligence Engineer at UTAP Tech, Arunabh is leading the development of a computer vision-based cattle weight prediction system. He also gained research experience as a Research Assistant at the University of Lincoln, contributing to net zero strategy reviews and machine learning model optimizations for industrial processes under Dr. Pouriya H. Niknam’s supervision. 🤖🌍

Research Focus

🔍 Arunabh’s research interests lie in the integration of artificial intelligence with robotics and healthcare. His current focus is on applying deep learning, retrieval-augmented generation (RAG), and large language models (LLMs) for medical chatbots, computer vision applications in agriculture, and reinforcement learning for robotics. 🚜🏥

Awards and Honors

🏆 Arunabh’s excellence in academia is highlighted by his distinction in his master’s degree. He has also contributed to multiple impactful research projects and received recognition for his innovative work in AI, IoT, and machine learning. 🥇✨

Publications

📝 Arunabh has published research on various AI-driven applications. His notable works include:

“Systematic Analysis of Retrieval-Augmented Generation-Based LLMs for Medical Chatbot Applications” published in Machine Learning and Knowledge Extraction (2024), https://doi.org/10.3390/make6040116 cited by 10 articles.

“Monitoring and Control of Water Requirements as Part of an Agricultural Management System using IoT” presented at the 7th International Conference on Mathematics and Computers in Sciences and Industry (MCSI) in 2022, https://doi.org/10.1109/MCSI55933.2022.00025 cited by 15 articles.

 

 

Changqing Xia | Computer Science | Best Researcher Award

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.