Hisham AbouGrad | Artificial intelligence | Best Academic Researcher Award

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Dr. Hisham AbouGrad | Artificial intelligence | Best Academic Researcher Award

Dr. Hisham AbouGrad , Senior Lecturer , University of East London – UEL , United Kingdom.

Dr. Hisham AbouGrad is a dynamic academic and industry expert in computer science and digital technologies. Currently a Senior Lecturer at the University of East London, he brings over two decades of experience in higher education and IT. Known for bridging theory with practice, he has supervised innovative projects in AI, FinTech, and mobile app development. Dr. AbouGrad also leads international academic collaborations and contributes to top-tier journals. He is a Fellow of the Higher Education Academy and an active member of the British Computer Society, with a passion for enhancing digital learning, scientific problem-solving, and sustainable technology.

Publication Profile

Scopus

ORCID

Google scholar

🎓 Education Background

Dr. Hisham AbouGrad earned his Doctorate in Professional Studies (DProf) from London South Bank University, focusing on Workflow Information Systems Performance using BPM methodologies. He also holds a Master of Science (MSc) in Software Engineering from the University of Bradford and a Master of Business Administration (MBA) in Management from the University of Lincoln. Additionally, he completed a Postgraduate Certificate in Higher Education Practice (PGCHEP) from the University of Plymouth. His academic credentials are enhanced by certifications in project management and IT, including CITP from BCS and PMP qualifications, reinforcing his foundation in both pedagogy and technical leadership.

💼 Professional Experience

Dr. AbouGrad’s career spans prestigious academic institutions and industry roles. Since 2021, he has served as a Senior Lecturer at the University of East London, where he also fosters international collaborations. Previously, he held teaching and leadership roles at ICON College, QA Higher Education, GSM London, and the University of Plymouth. From 2011 to 2019, he was a doctoral researcher at London South Bank University. With vast teaching experience in computing, business management, and information systems, Dr. AbouGrad has mentored numerous PhD and DProf students while shaping curricula aligned with technological advancements and practical industry applications.

🏆 Awards and Honors

Dr. Hisham AbouGrad has been recognized for his commitment to academic excellence and professional contribution. He is a Fellow of the UK Higher Education Academy (FHEA), a Certified IT Professional (CITP) with the British Computer Society (BCS), and has received qualifications in IT Quality Management (ITQM). He is a founding member of UEL’s FinTech Centre and contributes actively to academic committees and journal editorial boards. As a reviewer for reputed journals like IEEE TCE, SAGE, Elsevier, and Emerald, he consistently upholds research quality, earning professional credibility and trust in the global academic and scientific communities.

🔬 Research Focus

Dr. AbouGrad’s research integrates Artificial Intelligence, FinTech, Machine Learning, Information Security, and Multi-Criteria Decision Making (MCDM) with Business Process Management (BPM) and Workflow Systems. His work aims to create scalable, secure, and intelligent digital solutions. Projects under his supervision include AI-based financial prediction systems, eCommerce fraud detection using neural networks, and mobile payment technologies. His recent studies explore AI-driven stock prediction, sentiment analysis, and fake review detection—highlighting his goal to solve real-world problems through data science, machine learning, and performance analysis. He also researches Decision Support Systems (DSS), ECM, GIS, and user-centered eCommerce design.

🔚 Conclusion

Dr. Hisham AbouGrad is a passionate educator, strategic researcher, and technology advocate whose career is marked by innovation, collaboration, and impact. His multifaceted expertise across academia and industry supports students, institutions, and global communities in adapting to digital transformation. Through research, mentorship, and leadership, he contributes to solving complex challenges in AI, FinTech, and Information Systems. With a forward-thinking mindset, he continues to influence academic practices, elevate IT performance, and foster global academic relationships. His legacy reflects both the rigor of scholarly inquiry and the relevance of applied science in the 21st century.

📚 Top Publications with Details

  1. AI-Framework to Detect eCommerce Fake Reviews: A Hybrid Neural Network Machine Learning Model
    Published: 2024, Book: Artificial Intelligence and Computational Technologies
    Cited by: 1

  2. Financial Decision-Making AI-Framework to Predict Stock Price Using LSTM Algorithm and NLP-Driven Sentiment Analysis Model
    Published: 2025, Conference: Annual International Congress on Computer Science
    Cited by: 1

  3. Decision Making by Applying Machine Learning Techniques to Mitigate Spam SMS Attacks
    Published: 2023, Conference: International Conference on Deep Learning, Artificial Intelligence and Robotics
    Cited by: 5

  4. Developing the Business Process Management Performance of an Information System Using the Delphi Study Technique
    Published: 2019, Conference: EAI International Conference on Technology, Innovation, Entrepreneurship and Education
    Cited by: 5

  5. Applying the Delphi Method to Measure Enterprise Content Management Workflow System Performance
    Published: 2022, Journal: Lecture Notes in Networks and Systems (Springer)
    Cited by: 1

  6. The Impact of Business Process Management Values on Enterprise Content Management Workflow Systems Performance
    Published: 2020, Thesis: London South Bank University
    Cited by: 1

  7. Intelligent Computing, Proceedings of the 2022 Computing Conference
    Published: 2022, Publisher: Springer International Publishing
    Cited by: 23

  8. Key Digital Trends in Artificial Intelligence and Robotics: Proceedings of ICDLAIR 2022
    Published: 2023, Publisher: Springer International Publishing
    Cited by: 1

 

Ms. Yin ZiJuan | artificial intelligence | Best Researcher Award

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Ms. Yin ZiJuan | artificial intelligence | Best Researcher Award

Ms. Yin ZiJuan, graduate student, Shanghai University of Engineering Science, China.

Yin Zijuan is a dedicated graduate researcher at the School of Materials Science and Engineering, Shanghai University of Engineering Science. She has cultivated a unique interdisciplinary expertise that bridges materials science with artificial intelligence. Her notable work centers around intelligent surface defect detection using deep learning models. Yin gained international recognition for developing the BBW YOLO algorithm, which improves defect detection accuracy in aluminum profile manufacturing. With a passion for integrating AI into industrial applications, Yin exemplifies the new generation of scholars who are redefining engineering research through innovation, precision, and automation.

Publication Profile

Scopus

🎓 Education Background

Yin Zijuan is currently pursuing her graduate studies at the Shanghai University of Engineering Science, within the School of Materials Science and Engineering. Her academic focus lies in fusing materials engineering with advanced computational methods. During her studies, she developed specialized knowledge in deep learning, computer vision, and image processing as they relate to quality control in industrial materials. Her academic journey is marked by excellence, with her research earning publication in reputable international journals. Yin’s education reflects a strong foundation in both traditional materials science and cutting-edge AI methodologies.

🧪 Professional Experience

As a graduate researcher, Yin Zijuan has contributed to high-impact research projects focused on AI-driven defect detection in industrial materials. Her most distinguished project involved the development and implementation of the BBW YOLO algorithm, which blends Bidirectional Feature Pyramid Networks and attention mechanisms for enhanced image recognition. She has collaborated with institutions like Harbin Institute of Technology and participated in interdisciplinary studies that bridge academia and industry. Through her ongoing work, she aims to revolutionize quality assurance processes in manufacturing by deploying real-time and lightweight neural network systems.

🏆 Awards and Honors

Yin Zijuan has earned increasing recognition in the field of intelligent detection systems. Her research achievements culminated in a significant journal publication in Coatings, a Scopus and SCI-indexed journal, in 2025. This milestone established her as a rising scholar with contributions relevant to both academic and industrial domains. Her work on BBW YOLO has been lauded for its innovation, performance efficiency, and potential impact on industrial automation. Yin is also a nominee for prestigious awards including the Best Scholar Award, Outstanding Innovation Award, and Best Paper Award, all reflecting the excellence of her work.

🔬 Research Focus

Yin Zijuan’s research encompasses a wide spectrum of interdisciplinary themes including materials science, deep learning, and computer vision. Her primary focus is on developing intelligent detection algorithms for identifying surface defects in aluminum profiles. She has pioneered the BBW YOLO model, which integrates BiFPN and BiFormer attention mechanisms with a Wise-IoU v3 loss function. Her innovations improve defect detection accuracy while maintaining high processing speeds and model efficiency. Yin’s work supports the evolution of smart manufacturing and industrial automation, positioning her as a key contributor to the fusion of AI and engineering.

📌 Conclusion

Yin Zijuan exemplifies the future of smart materials research through her fusion of artificial intelligence and industrial materials science. Her work is not only academically rigorous but also practically relevant, addressing real-world problems in manufacturing. From algorithmic innovation to high-impact publication and inter-institutional collaboration, she has demonstrated exceptional promise as a research scholar. With her continued contributions, Yin is poised to lead transformative advancements in intelligent quality control systems. She stands as a worthy nominee for multiple academic honors and awards recognizing innovation, research excellence, and scholarly distinction.

📄 Top Publications Notes

  1. BBW YOLO: Intelligent Detection Algorithms for Aluminium Profile Material Surface Defects

  2. Thermal deformation behavior and microstructural evolution of the rapidly-solidified Al–Zn–Mg–Cu alloy in hot isostatic pressing state

 

 

 

 

 

Ms. ANKITA MANOHAR WALAWALKAR | Artificial Intelligence | Best Researcher Award

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Ms. ANKITA MANOHAR WALAWALKAR | Artificial Intelligence | Best Researcher Award

PhD, ASIA UNIVERSITY, TAIWAN

Ankita Manohar Walawalkar is an accomplished legal and academic professional from India, currently pursuing her Ph.D. in Business Administration at Asia University, Taiwan, with a strong focus on Artificial Intelligence, Corporate Governance, Human Resource Management, and Supply Chain. With a unique blend of legal expertise and international business experience, Ankita has spent over two decades navigating corporate procurement, translation, teaching, and research. Fluent in English, Hindi, and Chinese, she bridges cultural and linguistic gaps, making her a versatile contributor in academia and international business diplomacy. Her academic versatility, fieldwork experience, and multilingual proficiency make her a standout scholar and practitioner on global platforms.

Publication Profile

🎓 Education Background

Ankita is presently enrolled in a Ph.D. program in Business Administration at Asia University, Taiwan (2023–Present), focusing on interdisciplinary support areas such as AI, corporate governance, and HR. She holds a Master of Laws (LL.M.) in Corporate and Commercial Law from Amity University, Mumbai (2020–2021), where she deepened her expertise in IP, company law, and securities. Her foundational legal education was completed with a BLS-LLB from KES Jayantilal H. Patel Law College, University of Mumbai (2014–2020). Additionally, she completed a one-year Chinese Language Training at Zhengzhou University, China (2017–2018) under the prestigious Confucius Institute Scholarship.

💼 Professional Experience

Ankita’s dynamic professional career spans corporate sourcing and academia. From 2021 to 2023, she worked as a Sourcing Specialist at Algol Chemicals India Pvt. Ltd., New Delhi, specializing in Chinese supplier coordination, procurement, and logistics compliance. She has over five years of experience as a Freelance Interpreter and Translator, working with companies like VOXCO Pigments, Podar Enterprise, and Kohinoor Group, and participating in over 15 international exhibitions and conferences including the China-India Economic and Trade Conference. At Asia University, she serves as an EMI Teaching Assistant, TA for the Rural AI Bilingual Program, and works with the IC OIA office while volunteering at the INGO Research Centre. Her freelance work includes judicial interpretations, educational instruction for YCT/HSK levels, and market research projects for global clients.

🏆 Awards and Honors

Ankita was awarded the Confucius Institute Scholarship for a year-long language training program at Zhengzhou University, China (2017–2018), a testament to her dedication to language proficiency and cross-cultural studies. Her consistent participation in high-impact conferences and scholarly publications with global collaborators is a reflection of her ongoing academic recognition.

🔬 Research Focus

Ankita’s research interests are deeply rooted in AI Ethics, Corporate Governance, Human-AI Interaction, and Blockchain in HR, as reflected in her recent contributions to IGI Global book chapters and international conferences. She is actively involved in interdisciplinary explorations, combining law, ethics, and technology, with a notable focus on Human-AI collaboration in corporate decision-making, DEI challenges in hospital management, and the use of AI in education and language preservation.

📌 Conclusion

Ankita Manohar Walawalkar  stands at the unique intersection of law, language, and artificial intelligence, bringing over 20 years of diverse administrative, academic, and international experience to her work. Her contributions across education, corporate sourcing, and AI ethics research demonstrate her commitment to global impact and ethical innovation. As she continues her doctoral journey, her voice in the field of AI governance and multilingual education is becoming increasingly influential.

📝 Top Publication Notes

  1. Foundations of AI Ethics – 2024, IGI Global
    Cited by: 3 articles (as of 2024)
    Authors: Walawalkar, A. M., Moslehpour, M., Phattanaviroj, T., & Kumar, S.

  2. Utilization of Blockchain Technology to Manage Human Resources Data: Security Issues in Government Agencies – 2024, IGI Global
    Cited by: 2 articles
    Authors: Yati, P. P., & Walawalkar, A.

  3. Data Ethics and Privacy – 2024, IGI Global
    Cited by: 2 articles
    Authors: Phattanaviroj, T., Moslehpour, M., & Walawalkar, A. M.

  4. The Future of Ethical AI – 2024, IGI Global
    Cited by: 3 articles
    Authors: Firmansyah, G., Bansal, S., Walawalkar, A. M., Kumar, S., & Chattopadhyay, S.

  5. Investigating Human-AI Collaboration in Corporate Decision-Making for Sustainable Business Practices: An Extended UTAUT2 Model – 2025 (Upcoming), ICHESPAN Conference
    Status: Accepted, not yet cited
    Authors: Walawalkar, A. M., Moslehpour, M., Gupta, V., Rizaldy, H.

Prof. Dr. YiSheng Huang | Computer Science | Best Researcher Award

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Prof. Dr. YiSheng Huang | Computer Science | Best Researcher Award

Professor, National Ilan University/EE, Taiwan

Dr. Yi-Sheng Huang is a distinguished Professor at National Ilan University, Taiwan, with a remarkable career in Electrical and Electronic Engineering. Holding a Ph.D. from National Taiwan University of Science and Technology (NTUST), he has significantly contributed to Discrete Event Dynamic Systems, Petri Nets, and Intelligent Transportation Systems (ITS). Recognized among the World’s Top 2% Scientists (1960–2023), his expertise spans both theoretical advancements and real-world applications, shaping the future of smart mobility and automation. With leadership roles in academia and international collaborations, Dr. Huang continues to drive impactful research and innovation in the field of intelligent systems. 🚀

Publication Profile

📚 Academic Background

Dr. Yi-Sheng Huang earned his Ph.D. in Electrical Engineering from NTUST in 2001, laying the foundation for his expertise in dynamic systems and intelligent transportation. His commitment to academic excellence led him to various leadership positions, including Chairman of the Department of Electrical Engineering at National Ilan University (2015–2019) and Dean of the Office of Research and Development (2023–2024). He also enriched his global academic experience as a Visiting Professor at the New Jersey Institute of Technology (2008, 2014), fostering cross-border collaborations in intelligent automation. 🎓

🏢 Professional Experience

With over two decades of academic and research contributions, Dr. Huang has completed 30 major research projects and collaborated with industry leaders such as CECI Engineering Consultants, INC., Taiwan. His consultancy work spans 6 completed and 7 ongoing industry projects, demonstrating his ability to bridge theoretical research with practical applications. He is an esteemed member of the IEEE SMC Society and IEEE ITS Society, further solidifying his influence in cutting-edge technological advancements. His extensive publication record includes 114 journal papers indexed in Scopus and SCI, reflecting his commitment to advancing the field of intelligent systems. ⚡

🏆 Awards and Honors

Dr. Huang’s research excellence has earned him a place among the World’s Top 2% Scientists (1960–2023), highlighting his profound impact on electrical engineering and intelligent systems. His work has significantly influenced transportation optimization, making urban mobility smarter and more efficient. As a leading researcher, he continues to push the boundaries of Discrete Event Dynamic Systems and Petri Nets applications, setting new standards in system modeling and control. His contributions have been acknowledged globally, reinforcing his reputation as a pioneering scientist in his field. 🏅

🔬 Research Focus

Dr. Huang’s research revolves around Discrete Event Dynamic Systems, Petri Nets, and Intelligent Transportation Systems (ITS). His work has led to advanced methodologies in traffic flow management, congestion control, and system optimization, improving urban transport networks. By integrating theoretical models with real-world applications, he has contributed to automated decision-making frameworks, enhancing efficiency and sustainability in transportation. His research is instrumental in shaping smart cities and next-generation mobility solutions, fostering safer and more efficient transport ecosystems worldwide. 🚦

🔍 Conclusion

Dr. Yi-Sheng Huang stands at the forefront of intelligent transportation research, driving significant innovations in automation and dynamic systems. His global academic presence, extensive research contributions, and impactful industry collaborations establish him as a leading figure in electrical engineering and intelligent mobility solutions. With a legacy of over 114 publications, numerous research projects, and an enduring influence in academia, Dr. Huang continues to shape the future of intelligent transportation and automated systems. 🌍🚀

📝 Top Publications

A Petri net-based model for real-time traffic control in urban networks.

Optimization of discrete event systems using hybrid Petri nets.

Modeling and performance analysis of ITS using dynamic Petri nets.

Smart transportation planning with discrete event system simulation.

Enhancing automated transport systems using intelligent Petri nets.

 

Lianbo Ma | Artificial Intelligence | Best Researcher Award

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Prof. Lianbo Ma | Artificial Intelligence | Best Researcher Award

Professor, Northeastern University, China

Dr. Lianbo Ma is a distinguished professor at Northeastern University, China, with expertise in computational intelligence, machine learning optimization, big data analysis, and natural language processing. With a Ph.D. from the University of Chinese Academy of Sciences, he has significantly contributed to bio-inspired computing, multi-objective optimization, and cloud computing resource allocation. As a prolific researcher, Dr. Ma has published over 90 papers in high-impact journals and conferences, earning global recognition for his work. His research has been widely cited, and he has received numerous prestigious awards, making him a key figure in artificial intelligence and optimization.

Publication Profile

Google Scholar

🎓 Education

Dr. Ma holds a Doctorate in Machine-Electronic Engineering from the University of Chinese Academy of Sciences (2014). He earned his Master’s degree (2007) and Bachelor’s degree (2004) in Information Science and Engineering from Northeastern University, China. His academic journey has provided a solid foundation in AI-driven optimization, neural networks, and computational intelligence.

💼 Experience

Dr. Ma has held various esteemed positions in academia and research institutions. Since 2017, he has been a professor at Northeastern University, China, specializing in software engineering and AI. He previously served as an associate professor (2016-2017) and assistant research fellow at the Shenyang Institute of Automation, Chinese Academy of Sciences (2007-2015). His international experience includes a visiting scholar position at Surrey University, UK (2019-2020), under the mentorship of Prof. Yaochu Jin. His extensive professional journey highlights his contributions to AI-driven industrial applications and large-scale optimization.

🏆 Awards and Honors

Dr. Ma has been recognized among the World’s Top 2% Scientists (Elsevier & Stanford, 2022-2023) and has received several prestigious accolades, including the IEEE Best Paper Runner-Up Award (2023), the Best Student Paper Award at the International Conference on Swarm Intelligence (2021), and the Outstanding Reviewer Awards from Elsevier (2016, 2018). His achievements extend to the Liaoning Province Natural Science Academic Award and the BaiQianWan Talents Project Award. His dedication to research and mentorship is further evident in his recognition as an Excellent Master’s Thesis Instructor.

🔬 Research Focus

Dr. Ma’s research spans computational intelligence, large-scale multi-objective optimization, and bio-inspired computing. His expertise extends to cloud computing, edge computing, and social network analysis, where he has worked on cloud resource allocation and influence maximization. He is also actively engaged in multi-modal data processing, focusing on knowledge graphs, entity extraction, and text mining. His research integrates AI with industrial applications, advancing neural architecture search and intelligent data analysis.

🔍 Conclusion

Dr. Lianbo Ma is a pioneering researcher in artificial intelligence, computational intelligence, and machine learning optimization. His contributions to big data analytics, neural architecture search, and evolutionary computation have positioned him as a leading figure in the field. With numerous accolades, high-impact publications, and extensive academic service, Dr. Ma continues to shape the future of AI-driven optimization and intelligent computing. 🚀

📖 Publications

A Hybrid Neural Architecture Search Algorithm Optimized via Lifespan Particle Swarm Optimization for Coal Mine Image Recognition

Truthful Combinatorial Double Auctions for Mobile Edge Computing in Industrial IoT. IEEE Transactions on Mobile Computing, 21(11), 4125-4138. DOI

Single-Domain Generalized Predictor for Neural Architecture Search System. IEEE Transactions on Computers. DOI

One-Step Forward and Backtrack: Overcoming Zig-Zagging in Loss-Aware Quantization Training. AAAI-24 Conference Proceedings.

Pareto-wise Ranking Classifier for Multi-objective Evolutionary Neural Architecture Search. IEEE Transactions on Evolutionary Computation. DOI

An Adaptive Localized Decision Variable Analysis Approach to Large-Scale Multiobjective and Many-objective Optimization. IEEE Transactions on Cybernetics, 52(7), 6684-6696. DOI

Enhancing Learning Efficiency of Brain Storm Optimization via Orthogonal Learning Design. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51(11), 6723-6742. DOI

 

QIANG QU | Artificial Intelligence Award | Best Researcher Award

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Prof. QIANG QU | Artificial Intelligence Award | Best Researcher Award

PROFESSOR, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China

Dr. Qiang Qu is a distinguished professor and a leading researcher in blockchain, data intelligence, and decentralized systems. He serves as the Director of the Guangdong Provincial R&D Center of Blockchain and Distributed IoT Security at the Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS). Additionally, he holds a professorship at Shenzhen University of Advanced Technology and has previously served as a guest professor at The Chinese University of Hong Kong (Shenzhen). Dr. Qu has also contributed as the Director and Chief Scientist of Huawei Blockchain Lab. With a strong international academic presence, he has held research positions at renowned institutions such as ETH Zurich, Carnegie Mellon University, and Nanyang Technological University. His pioneering work focuses on scalable algorithm design, data sense-making, and blockchain technologies, making significant contributions to AI, data systems, and interdisciplinary studies.

Publication Profile

🎓 Education

Dr. Qiang Qu earned his Ph.D. in Computer Science from Aarhus University, Denmark, under the supervision of Prof. Christian S. Jensen. His doctoral research was supported by the prestigious GEOCrowd project under Marie Skłodowska-Curie Actions. He further enriched his academic journey as a Ph.D. exchange student at Carnegie Mellon University, USA. He holds an M.Sc. in Computer Science from Peking University, China, and a B.S. in Management Information Systems from Dalian University of Technology.

💼 Experience

Dr. Qu has a diverse professional background, reflecting his global expertise. Since 2016, he has been a professor at SIAT, leading groundbreaking research in blockchain and distributed IoT security. He also served as Vice Director of Hangzhou Institutes of Advanced Technology (SIAT’s Hangzhou branch). Prior to this, he was an Assistant Professor and the Director of Dainfos Lab at Innopolis University, Russia. His research journey includes being a visiting scientist at ETH Zurich, a visiting scholar at Nanyang Technological University, and a research fellow at Singapore Management University. He also gained industry experience as an engineer at IBM China Research Lab.

🏅 Awards and Honors

Dr. Qu has received several national and international research grants, recognizing his impactful contributions to blockchain and AI-driven data intelligence. He is a prominent editorial board member of the Future Internet Journal and serves as a guest editor for multiple high-impact journals. As an active contributor to the research community, he has been a TPC (Technical Program Committee) member for prestigious conferences and regularly reviews top-tier AI and data systems journals.

🔬 Research Focus

Dr. Qu’s research interests revolve around data intelligence and decentralized systems, with a strong focus on blockchain, scalable algorithm design, and data-driven decision-making. His work has been instrumental in developing efficient data parallel approaches, AI-driven network analysis, and cross-blockchain data migration techniques. His interdisciplinary contributions bridge AI, IoT security, and geospatial analytics, driving innovation in secure and intelligent computing.

🔚 Conclusion

Dr. Qiang Qu stands as a thought leader in blockchain and data intelligence, combining academic excellence with real-world impact. His contributions to AI-driven decentralized systems and scalable data solutions continue to shape the fields of computer science and IoT security. His extensive research collaborations, editorial roles, and international experience make him a key figure in advancing secure and intelligent computing technologies. 🚀

📚 Publications

SNCA: Semi-supervised Node Classification for Evolving Large Attributed Graphs – IEEE Big Data Mining and Analytics (2024). Cited in IEEE 📖

CIC-SIoT: Clean-Slate Information-Centric Software-Defined Content Discovery and Distribution for IoT – IEEE Internet of Things Journal (2024). Cited in IEEE 📖

Blockchain-Empowered Collaborative Task Offloading for Cloud-Edge-Device Computing – IEEE Journal on Selected Areas in Communications (2022). Cited in IEEE 📖

On Time-Aware Cross-Blockchain Data Migration– Tsinghua Science and Technology (2024). Cited in Tsinghua University 📖

Few-Shot Relation Extraction With Automatically Generated Prompts – IEEE Transactions on Neural Networks and Learning Systems (2024). Cited in IEEE 📖

Opinion Leader Detection: A Methodological Review – Expert Systems with Applications (2019). Cited in Elsevier 📖

Neural Attentive Network for Cross-Domain Aspect-Level Sentiment Classification– IEEE Transactions on Affective Computing (2021). Cited in IEEE 📖

Efficient Online Summarization of Large-Scale Dynamic Networks –  IEEE Transactions on Knowledge and Data Engineering (2016). Cited in IEEE 📖