Hongzhen Cui | Computer Science | Best Researcher Award

Posted on 08/02/202508/02/2025 by Book of Award

Dr. Hongzhen Cui | Computer Science | Best Researcher Award

University of Science and Technology Beijing | China

Author Profile

🚀 Early Academic Pursuits

Dr. Hongzhen Cui embarked on his academic journey in computer science with a Bachelor's degree from Zaozhuang University, where he built a solid foundation in computational principles. His passion for technology and problem-solving led him to pursue a Master's degree at Harbin Engineering University, refining his expertise in advanced computing methodologies. Currently, he is a Ph.D. candidate at the University of Science and Technology Beijing, where he specializes in cutting-edge fields such as Natural Language Processing (NLP), Knowledge Graphs, and Deep Learning, with a strong focus on cardiovascular disease research.

💼 Professional Endeavors

Dr. Cui's career has been marked by a blend of research and practical experience. As a System R&D Engineer at Meituan, he contributed to large-scale distributed systems, optimizing performance and collaborating with cross-functional teams to drive technological advancements. His passion for academia led him to a teaching position at Zaozhuang University, where he inspired students in subjects such as Data Structures, Algorithm Design, and Software Engineering. Through these roles, he has seamlessly combined industry expertise with academic mentorship.

🔬 Contributions and Research Focus

Dr. Cui’s research delves deep into the intersection of artificial intelligence and healthcare. His work in Natural Language Processing and Knowledge Graphs plays a pivotal role in extracting meaningful insights from medical data. With a keen interest in cardiovascular disease feature mining, he develops AI-driven models for disease prediction and analysis, aiding in early diagnosis and medical decision-making. His interdisciplinary approach bridges the gap between engineering and medicine, contributing to the evolution of intelligent healthcare solutions.

🏆 Accolades and Recognition

Dr. Cui’s dedication to research and academia has earned him recognition in both scientific and professional communities. His contributions to NLP and deep learning applications in healthcare have been acknowledged through publications, conference presentations, and collaborative projects. His role as a mentor and lecturer has also been praised for shaping future generations of computer scientists.

🌍 Impact and Influence

Through his research, Dr. Cui has made significant strides in the application of AI to medical diagnostics. His work on disease information extraction and prediction not only enhances medical research but also paves the way for AI-assisted healthcare innovations. As an educator, he has influenced countless students, guiding them towards research excellence and industry preparedness.

🔮 Legacy and Future Contributions

Dr. Cui's future aspirations involve furthering AI’s role in medical advancements, refining predictive models for cardiovascular diseases, and expanding the capabilities of knowledge graphs in healthcare applications. His interdisciplinary research continues to break barriers, promising a future where AI-driven solutions revolutionize disease prevention and treatment.

Publications

📄ECG Signal Classification Using Interpretable KAN: Towards Predictive Diagnosis of Arrhythmias
Author(s): Hongzhen Cui, Shenhui Ning, Shichao Wang, Wei Zhang, Yunfeng Peng
Journal: Algorithms
Year: 2025

Junwei Du | Computer Science | Best Researcher Award

Posted on 17/12/202417/12/2024 by Book of Award

Prof. Junwei Du | Computer Science | Best Researcher Award

Qingdao University of Science and Technology | China

Author Profile

Scopus

Orcid

Early Academic Pursuits 🎓

Prof. Junwei Du embarked on his academic journey with a strong foundation in computer science. He earned his Ph.D. in Computer Software and Theory from Tongji University in 2010. His thirst for international exposure led him to become a Visiting Scholar at Arizona State University, USA, in 2014. Further enriching his skills, Prof. Du attended the AI Training Workshop for Young Backbone hosted by the University of Queensland and the University of Technology, Sydney, Australia, in September 2018.

Professional Endeavors 💼

Prof. Junwei Du is currently Executive Vice Dean of the School of Data Science at Qingdao University of Science and Technology. His professional affiliations include being a Distinguished Member of CCF and holding memberships in prestigious committees like the China Computer Society's Software Engineering Specialised Committee and the China Automation Society's Network Information Service Committee. Additionally, he serves as a Director of the Shandong Artificial Intelligence Society, underscoring his leadership in the field.

Contributions and Research Focus 🔬

Prof. Du's research focuses on cutting-edge areas like intelligent software engineering, graph representation learning, and recommendation algorithms. He has led numerous high-impact projects, including a National Natural Science Foundation of China top-level project, two provincial funds, and a key R&D project in Shandong Province. His work has also extended to over 10 national vertical projects and nine enterprise-driven horizontal projects. Prof. Du has published more than 60 academic papers in renowned journals such as Information Sciences, Software Journal, and Expert Systems with Applications. His research has significantly contributed to software fault prediction, cross-domain recommendation systems, and privacy-preserving algorithms in IoT.

Accolades and Recognition 🏆

Prof. Junwei Du’s achievements have earned him notable accolades. As a key participant, he received the Third Prize of Shandong Provincial Scientific and Technological Progress and the Third Prize of Shandong Provincial Teaching Achievement. He has also guided his students to excel in prestigious competitions, leading them to win over 20 national awards in software design and testing.

Impact and Influence 🌍

Through his extensive contributions, Prof. Junwei Du has shaped the landscape of intelligent software systems and data science education. His leadership in research and teaching has inspired countless students to pursue innovation. Prof. Du’s work on ensemble learning, recommendation algorithms, and software fault prediction holds significant implications for industries ranging from IT to industrial IoT, enhancing technological efficiency and reliability.

Legacy and Future Contributions 🔮

Prof. Junwei Du continues to build a legacy of excellence, bridging academia and industry with transformative research and mentorship. His focus on emerging areas like graph representation learning and cross-domain recommendation systems will pave the way for smarter AI applications. By fostering collaboration and innovation, he is set to make lasting contributions to data science and software engineering, empowering the next generation of researchers and professionals.

Publications

📄 Improving Bug Triage with the Bug Personalized Tossing Relationship
Authors: Wei Wei, Haojie Li, Xinshuang Ren, Feng Jiang, Xu Yu, Xingyu Gao, Junwei Du
Journal: Information and Software Technology
Year: 2025

📄 A Privacy-Preserving Cross-Domain Recommendation Algorithm for Industrial IoT Devices
Authors: Yu X., Peng Q., Lv H., Du J., Gong D.
Journal: IEEE Transactions on Consumer Electronics
Year: 2024

📄 Research on Efficient Data Warehouse Construction Methods for Big Data Applications
Authors: Zhao C., Du J., Wang F., Li H.
Journal: Applied Mathematics and Nonlinear Sciences
Year: 2024

📄 A Cross-Domain Intrusion Detection Method Based on Nonlinear Augmented Explicit Features
Authors: Yu X., Lu Y., Jiang F., Du J., Gong D.
Journal: IEEE Transactions on Network and Service Management
Year: 2024

📄 A Multi-Behavior Recommendation Based on Disentangled Graph Convolutional Networks and Contrastive Learning
Authors: Yu J., Jiang F., Du J.W., Yu X.
Journal/Proceedings: Communications in Computer and Information Science
Year: 2024

Luis Cavique | Computer Science | Best Research Award

Posted on 06/11/202406/11/2024 by Book of Award

Prof. Luis Cavique | Computer Science | Best Research Award

Universidade Aberta | Portugal

Author Profile

Scopus

Orcid

Early Academic Pursuits 🎓

Prof. Luís Cavique began his academic journey with a strong foundation in Computer Science, earning a degree in Computer Science Engineering in 1988 from the Faculty of Science and Technology at the New University of Lisbon. His pursuit of advanced knowledge continued with a Master’s in Operational Research and Systems Engineering in 1994 from the Instituto Superior Técnico, Technical University of Lisbon, where he focused on complex problems like crew scheduling. His academic commitment culminated in 2002 with a PhD in Engineering Systems, where he explored meta-heuristics for the Maximum Clique Problem, emphasizing applications in market basket analysis. This robust educational background set the stage for a career marked by analytical depth and academic rigor.

Professional Endeavors 👨‍🏫

Prof. Cavique’s teaching career spans several decades, beginning in 1991 in the Polytechnic Education System in Portugal, where he held adjunct positions at Setúbal and Lisbon Polytechnic Institutes until 2008. Since then, he has served as an Assistant Professor with tenure at the Universidade Aberta, focusing on computer science within the Department of Sciences and Technology. His dedication to fostering knowledge extends to graduate and doctoral levels, where he teaches courses such as Data Mining, Social Network Analysis, and Optimization. Beyond academia, Prof. Cavique also gained hands-on experience in the banking sector as a Systems Engineer at Banco Pinto & Sotto Mayor and through internships at prominent institutions like Banco Espírito Santo and the National Laboratory of Civil Engineering.

Contributions and Research Focus 🔍

With a strong interdisciplinary approach, Prof. Cavique’s research bridges Computer Science and Engineering Systems, focusing primarily on heuristic optimization and data mining. His work has addressed three core data mining challenges: classification, association, and segmentation. Notable publications include groundbreaking algorithms and tools, such as the LAID algorithm for classification, Ramex for association in financial product analysis, and ComDetection for community detection in social networks. These contributions have positioned Prof. Cavique at the forefront of data-driven research, and his methods are applied widely in sectors requiring complex data analysis.

Accolades and Recognition 🏆

Prof. Cavique's scholarly work has been recognized internationally, with several of his papers published in prestigious journals. His 1999 paper on crew scheduling received the IFORS-Lisbon Prize in 2000 from the Association of Operational Research in Portugal (APDIO). Many of his publications are highly cited, with articles featured in Q1-ranked journals, illustrating the high impact and quality of his research. His dedication to advancing data mining and optimization has earned him both peer recognition and a strong citation record, showcasing his influence in these fields.

Impact and Influence 🌍

Throughout his career, Prof. Cavique has made a lasting impact on the fields of data mining and heuristic optimization. His research has influenced approaches in financial analytics, community detection in social networks, and data reduction techniques, providing foundational tools and algorithms that are utilized in academia and industry alike. His methodologies have empowered researchers and practitioners in various domains to make informed, data-driven decisions, underscoring his role as a pioneer in computational research.

Legacy and Future Contributions 🌟

As a leading academic and researcher, Prof. Cavique’s legacy is defined by his contributions to both knowledge and education in computer science. His focus on heuristic optimization and data mining continues to inspire new research, particularly in emerging fields such as bioinformatics and social network analysis. His commitment to teaching and mentoring the next generation of scientists ensures that his impact will extend well into the future, enriching the scientific community and driving innovation in computational methods.

Publications

📝 Mitigating false negatives in imbalanced datasets: An ensemble approach
Authors: Marcelo Vasconcelos; Luís Cavique
Journal: Expert Systems with Applications
Year: 2024

📝 Assessment in Collaborative Learning
Authors: Luis Cavique; M. Rosário Ramos
Journal: Revista de Educación a Distancia (RED)
Year: 2024

Anastasios Liapakis | Computer Science | Best Researcher Award

Posted on 27/08/202427/08/2024 by Book of Award

Assist Prof Dr. Anastasios Liapakis | Computer Science | Best Researcher Award

University of West Attica | Greece

Author Profile

Orcid

Google Scholar

Early Academic Pursuits 📚

Dr. Anastasios Liapakis embarked on his academic journey with a strong foundation in Agricultural Engineering at the Agricultural University of Athens, where he completed his B(Eng) with a commendable grade of 7.27/10. Driven by a passion for data and analytics, he pursued a Master of Business Administration (MBA) specializing in Data Analytics at the same institution. His dedication and academic excellence earned him a top grade of 8.59/10. Dr. Liapakis continued his pursuit of knowledge by obtaining a PhD in Informatics, focusing on Big Data Analytics in Agricultural Digital Markets. His research in this area, completed with an "Excellent" grade, laid the groundwork for his future contributions to the field.

Professional Endeavors 🚀

Dr. Liapakis has held several key academic positions that have shaped his career. He is currently an Adjunct Assistant Professor at the University of West Attica, where he teaches modules on E-governance and Databases. His experience spans various institutions, including the University of Peloponnese, where he taught Programming II, and the National & Kapodistrian University of Athens, where he delivered courses on Object-Oriented Programming, Software Systems Design, and e-Government Systems. As the Academic Head of the Informatics Department at New York College, Athens, he managed programs in Computing, Software Engineering, and Data Analytics, showcasing his leadership and expertise in the field.

Contributions and Research Focus 🔬

Dr. Liapakis' research interests lie at the intersection of Artificial Intelligence (AI), Big Data Analytics, and Cultural Heritage Information Management. He has made significant contributions to the understanding and application of AI in various domains, particularly in opinion mining and big data analytics. His work has been instrumental in developing innovative solutions for the agricultural sector, including automated monitoring and control systems against pests in the Mediterranean region. His research projects, funded by the EU, have had a profound impact on the industry, highlighting his ability to bridge the gap between academia and real-world applications.

Accolades and Recognition 🏆

Throughout his career, Dr. Liapakis has been recognized for his outstanding academic performance and research contributions. He received multiple scholarships and financial awards, including one from the Agricultural University of Athens for his exceptional performance in the MBA program and another from the Greek State Scholarships Foundation during his undergraduate studies. His research has also garnered accolades, including a Best Paper Award at the International Journal of Computational Linguistics in 2020, solidifying his reputation as a leading researcher in his field.

Impact and Influence 🌍

Dr. Liapakis' work has had a significant impact on the academic community and beyond. His research in big data analytics and AI has influenced how these technologies are applied in various sectors, particularly in agriculture and food industries. His contributions to sentiment analysis, particularly in the context of the Greek language, have provided valuable insights for both academia and industry. Additionally, his involvement in PhD supervision and as a reviewer for various research journals demonstrates his commitment to shaping the future of research in his field.

Legacy and Future Contributions 🌟

As Dr. Liapakis continues to advance his research in AI and big data, his legacy is one of innovation and dedication to the application of cutting-edge technologies in solving real-world problems. His ongoing work in cultural heritage information management and his leadership in academic programs ensure that his contributions will continue to influence future generations of researchers and practitioners. Dr. Liapakis' vision for integrating AI into various sectors, coupled with his extensive experience and accolades, positions him as a thought leader poised to make lasting contributions to both academia and industry.

Publications

📝A Sentiment Analysis Approach for Exploring Customer Reviews of Online Food Delivery Services: A Greek Case
Authors: Fragkos, N.; Liapakis, A.; Ntaliani, M.; Ntalianis, F.; Costopoulou, C.
Journal: Preprints 2024, 2024041203
Year: 2024

📝Ethical Use of Artificial Intelligence and New Technologies in Education 5.0
Authors: Liapakis, A., Smyrnaiou, Z., & Bougia, A.
Journal: International Journal of Artificial Intelligence, Machine Learning and Data Science
Year: 2023

📝Big Data, Sentiment Analysis, and Examples during the COVID-19 Pandemic
Authors: Diareme, K. C., Liapakis, A., & Efthymiou, I.
Journal: HAPSc Policy Briefs Series
Year: 2022

📝An Aspect-Based Sentiment Analysis System to Analyze Customers’ Reviews from Food and Beverage Opinion and Review Webpages: The Greek Case
Authors: Liapakis, A., Tsiligiridis, T., Yialouris, C., & Costopoulou, C., Diareme, K.C.
Journal: Information (Accepted for publication)
Year: 2021

📝A Corpus-Driven, Aspect-Based Sentiment Analysis to Evaluate in Almost Real-Time, a Large Volume of Online Food & Beverage Reviews
Authors: Liapakis, A., Tsiligiridis, T., Yialouris, C., & Maliappis, M.
Journal: International Journal of Computational Linguistics (IJCL)
Year: 2020

Ruichao Yang | Computer Science | Best Researcher Award

Posted on 05/04/202405/04/2024 by Book of Award

Ms. Ruichao Yang | Computer Science | Best Researcher Award

Hong Kong Baptist University | Hong Kong

Author Profile

Scopus

Early Academic Pursuits

Ruichao Yang commenced their academic journey at Jilin University, where they systematically delved into computer science courses and participated in various competitions. Notably, they secured the third prize in the 5th "Certification Cup" National College Students Mathematical Modeling Network Challenge. Their undergraduate experience laid a robust foundation in data structure, algorithm design, and analytical skills, setting the stage for their future endeavors.

Professional Endeavors

Ruichao Yang's professional journey commenced with internships and later full-time roles at Microsoft China, where they showcased their prowess in software engineering and natural language processing. They contributed significantly to projects aimed at enhancing online keyword matching systems, filtering advertisements, and improving revenue through innovative approaches. Their expertise in programming languages, data structures, and algorithms proved instrumental in restructuring and optimizing advertising business systems.

Contributions and Research Focus

Ruichao Yang's academic background, coupled with their industry experience, fueled their research focus on improving the efficiency of computing systems, particularly cache optimization and deep learning network acceleration. Their contributions to building domain knowledge graphs and anomaly detection models underscore their commitment to advancing technology's practical applications, particularly in the realm of advertising and revenue optimization.

Accolades and Recognition

Throughout their academic and professional journey, Ruichao Yang garnered numerous accolades and awards, including academic scholarships, merit distinctions, and recognition for their leadership and volunteerism. Their consistent pursuit of excellence and dedication to their field have been acknowledged both within academia and the industry.

Impact and Influence

Ruichao Yang's work at Microsoft China and academic research endeavors have left a significant impact on the domains of software engineering and computer science. Their innovative approaches to problem-solving and contributions to optimizing advertising systems have not only enhanced user experiences but also contributed to revenue growth and operational efficiency.

Legacy and Future Contributions

As Ruichao Yang continues to navigate their career path, their legacy lies in their contributions to advancing technology's frontiers, particularly in software engineering, natural language processing, and computational optimization. Their future contributions are poised to further propel innovation, shape industry standards, and inspire the next generation of computer scientists and engineers.

Notable Publications

CoTea: Collaborative teaching for low-resource named entity recognition with a divide-and-conquer strategy 2024
Towards low-resource rumor detection: Unified contrastive transfer with propagation structure 2024
Reinforcement Subgraph Reasoning for Fake News Detection 2022 (29)

A Weakly Supervised Propagation Model for Rumor Verification and Stance Detection with Multiple Instance Learning 2022 (20)

Towards Fine-Grained Reasoning for Fake News Detection 2022 (35)

Nam-Phuong Tran | Computer Science | Best Researcher Award

Posted on 22/03/202426/03/2024 by Book of Award

Mr. Nam-Phuong Tran | Computer Science | Best Researcher Award

Chung-Ang University | South Korea

Author Profile

Scopus

Google Scholar

Early Academic Pursuits

Mr. Nam-Phuong Tran began his academic journey at Hanoi University of Science and Technology, Vietnam, where he pursued a Bachelor of Engineering in Computer Science, completing it from August 2015 to June 2020. His thesis, "Spatio-Temporal Dynamics of the Labor Market," showcased his early dedication to research. Subsequently, he pursued an MSc of Science in Computer Science at Chung-Ang University, Seoul, Korea, focusing on QoE Management for Video Streaming Systems over IRS-aided RSMA Networks under the guidance of Professor Sungrae Cho.

Professional Endeavors

Tran has diversified professional experience, ranging from software engineering to research roles. He worked as a Software Engineer at Viettel Digital Service and as a Graduate Research Assistant at the Ultra-Intelligent Computing/Communication Lab, Chung-Ang University. Additionally, he has served as a Software Developer, Data Scientist Intern, and Undergraduate Research Assistant, gaining exposure to various facets of computer science and engineering.

Contributions and Research Focus

Tran's research primarily revolves around improving Quality of Experience (QoE) in communication networks, focusing on topics such as wireless resource allocation, bitrate adaptation, and low-latency protocols. His expertise spans intelligent reflecting surfaces, rate-splitting multiple access, IoT, deep learning, reinforcement learning, federated learning, and multimedia over wireless networks. He has also delved into big data analytics, including data crawling, mining, visualization, and predictive analytics.

Accolades and Recognition

Tran's dedication to academia has been acknowledged through numerous awards and scholarships, including the Chung-Ang University Young Scientist Scholarship, Brain Korea 21 Graduate School Research Scholarship, Daewoong AI Big Data Scholarship, and the Shinhan Bank Scholarship. He has also received recognition for his programming skills and outstanding thesis presentation.

Impact and Influence

Tran's research contributions, particularly in the realm of improving QoE in communication systems, have the potential to influence the development of more efficient and user-centric network protocols. His work in wireless resource allocation, bitrate adaptation, and low-latency protocols could lead to significant advancements in multimedia streaming, IoT, and metaverse applications, shaping the future of communication technologies.

Legacy and Future Contributions

Tran's legacy may lie in his interdisciplinary approach to addressing challenges in communication networks and big data analytics. His research outputs and professional endeavors are poised to contribute to advancements in wireless communication, machine learning applications, and data-driven decision-making. With his demonstrated commitment to excellence and innovation, he is likely to continue making notable contributions to the field of computer science and engineering, both in academia and industry.

Notable Publications

Privacy-Preserving Traffic Flow Prediction: A Split Learning Approach 2023

Delay-constrained quality maximization in RSMA-based video streaming networks 2022

A Survey on Intelligent Reflecting Surface-aided Non-Orthogonal Multiple Access Networks 2022

A Survey on Passive Beamforming using Statistical State Information in Intelligent Reflecting Surface Assisted Networks 2022

Jingjing Cao | Computer Science | Best Researcher Award

Posted on 16/03/202416/03/2024 by Book of Award

Dr. Jingjing Cao | Computer Science | Best Researcher Award

School of Transportation and Logistics Engineering | China

Author Profile

Scopus

Orcid

Early Academic Pursuits

Dr. Jingjing Cao's academic journey commenced with a Bachelor of Engineering in Information and Computing Science from Dalian Maritime University. Subsequently, she pursued a Master of Science in Applied Mathematics before earning her Ph.D. from the Department of Computer Science at City University of Hong Kong.

Professional Endeavors

Dr. Cao's professional journey has been marked by significant contributions. She served as a Research Associate at Dalian Maritime University and later assumed roles as Assistant Professor and now Tenure Track Associate Professor at Wuhan University of Technology.

Contributions and Research Focus

With a focus on Machine Learning and its applications in transportation and logistics, Dr. Cao has made remarkable contributions. Her research spans various domains, including ensemble learning, deep learning, and optimization algorithms, as evidenced by her prolific publication record in reputable journals and conferences.

Accolades and Recognition

Dr. Cao's impactful research has garnered widespread recognition, exemplified by her receipt of the prestigious Best Researcher Award. Her publications in renowned journals and conferences underscore her standing as a leading figure in the field of Computer Science and Machine Learning.

Impact and Influence

Dr. Cao's work has left a lasting impact on the academic community and industry alike. Her research has not only advanced the theoretical understanding of Machine Learning but has also found practical applications in domains such as transportation, logistics, and industrial informatics.

Legacy and Future Contributions

As Dr. Cao continues her academic journey, her legacy is defined by a commitment to excellence in research and education. With ongoing projects and professional services, she remains dedicated to shaping the future of Computer Science and Machine Learning, leaving an indelible mark on the field.

Notable Publication

A two-stage model for forecasting consumers’ intention to purchase with e-coupons 2021 (15)

RtDS: real-time distributed strategy for multi-period task offloading in vehicular edge computing environment 2021 (14)