Zhang Zhenqian | Neuroscience | Best Researcher Award

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Mr. Zhang Zhenqian | Neuroscience | Best Researcher Award

University of Toyama | Japan

Mr. Zhang Zhenqian is a dedicated researcher whose work bridges artificial intelligence, machine learning, and meteorology, with an emphasis on developing advanced neural network models for predictive analytics. His recent publication, “RD2: Reconstructing the Residual Sequence via Under Decomposing and Dendritic Learning for Generalized Time Series Predictions,” featured in Neurocomputing (October 2025), showcases his innovative approach to enhancing time series forecasting accuracy through the integration of dendritic learning mechanisms and residual sequence reconstruction. Collaborating with Houtian He, Zhenyu Lei, Zihang Zhang, and Shangce Gao, Mr. Zhang contributes to advancing the computational intelligence field by addressing challenges in dynamic data modeling and predictive reliability. His research explores the intersection of data-driven modeling and environmental systems, offering valuable insights for improving real-world forecasting, particularly in meteorological and environmental applications. With a growing scholarly presence and contributions recognized through peer-reviewed international publications, Mr. Zhang exemplifies a new generation of researchers committed to interdisciplinary innovation. His work not only strengthens the theoretical foundations of artificial intelligence but also demonstrates its transformative potential in understanding and managing complex natural and engineered systems.

Profile : Orcid

Featured Publication

Zhang, Z., He, H., Lei, Z., Zhang, Z., & Gao, S. (2025). RD2: Reconstructing the residual sequence via under decomposing and dendritic learning for generalized time series predictions. Neurocomputing, 131867.

Simy Baby | Engineering | Best Researcher Award

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Mrs. Simy Baby | Engineering | Best Researcher Award

National Institute of Technology | India

Mrs. Simy Baby is an emerging researcher whose scholarly contributions center on semantic communications, machine learning, and computer vision, with a strong emphasis on communication-efficient feature extraction for edge inference tasks. She has authored 2 documents, received 2 citations, and holds an h-index of 1, reflecting the growing impact of her research in advanced communication technologies. Her publications in SCI-indexed journals, including Elsevier’s Computers & Electrical Engineering and IEEE Transactions on Cognitive Communications and Networking, demonstrate her commitment to innovation and excellence. Her study, “Complex Chromatic Imaging for Enhanced Radar Face Recognition”, introduced a novel complex-valued representation preserving amplitude and phase information of mmWave radar signals, achieving 99.7% recognition accuracy. Another major contribution, “Complex-Valued Linear Discriminant Analysis on mmWave Radar Face Signatures for Task-Oriented Semantic Communication”, proposed a CLDA-based encoding framework that improved feature interpretability and robustness under varying channel conditions. Her ongoing projects explore Data Fusion Discriminant Analysis (DFDA) for multi-view activity recognition and Semantic Gaussian Process Regression (GPR) for vehicular pose estimation, advancing the integration of semantic communication and computer vision. Mrs. Simy Baby’s research represents a vital step toward the development of intelligent, efficient, and adaptive communication systems for next-generation technologies.

Profiles : Scopus | Orcid | Google Scholar

Featured Publications

Baby, S. M., & Gopi, E. S. (2025). Complex valued linear discriminant analysis on mmWave radar face signatures for task-oriented semantic communication. IEEE Transactions on Cognitive Communications and Networking.

Baby, S. M., & Gopi, E. S. (2025, April). Complex chromatic imaging for enhanced radar face recognition. Computers and Electrical Engineering.

Yaqin Wu | Computer Science | Excellence in Research Award

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Ms. Yaqin Wu | Computer Science | Excellence in Research Award

Shanxi Agricultural University | China

Ms. Yaqin Wu is an accomplished researcher and educator specializing in acoustic signal analysis, deep learning, and multimodal information fusion, with a research record reflecting 80 citations across 78 documents, 9 publications, and an h-index of 3. She holds a Master of Engineering in Electronic and Communication Engineering from Tianjin University and a Bachelor’s degree in Communication Engineering from Dalian Maritime University. Currently serving as a full-time faculty member at the School of Software, Shanxi Agricultural University, she teaches courses such as Speech Signal Processing, Natural Language Processing, and Human-Computer Interaction. Ms. Wu has led and contributed to several cutting-edge research projects, including pathological voice restoration, multimodal animal behavior monitoring, and AVS audio codec development. She has authored multiple SCI-indexed papers and holds several patents and software copyrights related to voice signal processing. Her technical proficiency spans Python, MATLAB, Linux systems, and MySQL databases. Notably, her master’s thesis earned the Outstanding Achievement Award of Engineering Master’s Practice from Tianjin University. Through her innovative contributions in signal processing and intelligent systems, Ms. Wu continues to advance the intersection of engineering and artificial intelligence research.

Profiles : Scopus | Orcid

Featured Publications

Zhang, J., Wu, Y., & Zhang, T. (2025). Fusing time-frequency heterogeneous features with cross-attention mechanism for pathological voice detection. Journal of Voice. Advance online publication.

Li, X., Wang, K., Chang, Y., Wu, Y., & Liu, J. (2025). Combining Kronecker-basis-representation tensor decomposition and total variational constraint for spectral computed tomography reconstruction. Photonics, 12(5), 492.

Hanlin Liu | Engineering | Research for community Impact Award

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Mr. Hanlin Liu | Engineering | Research for community Impact Award

Jilin Jianzhu University | China

Author profile

Google Scholar

Early Academic Pursuits

Mr. Hanlin Liu began his academic journey in the field of surveying and mapping engineering during his undergraduate studies at Jilin Jianzhu University. His dedication to precision and technical learning laid a strong foundation in geospatial sciences and civil engineering. With consistent performance and research-oriented thinking, he advanced to pursue a master’s degree in architecture and civil engineering at the same university. Under the guidance of his academic mentor, he cultivated a deep interest in remote sensing, machine learning, and environmental studies, setting the stage for his future research career.

Professional Endeavors

During his postgraduate years, Mr. Liu devoted himself to intensive laboratory work and field research. His professional endeavors included collaborative projects on soil analysis, wetland dynamics, mineral exploration, and fault diagnosis in mechanical systems. He demonstrated strong proficiency in scientific software, programming languages, and experimental design, which allowed him to develop advanced computational models and analytical frameworks. His role as an academic leader, serving as a class representative and editorial head, reflects his ability to balance research with organizational responsibilities.

Contributions and Research Focus

Mr. Liu’s research contributions span across environmental monitoring, mechanical fault diagnosis, and hyperspectral remote sensing. He explored the spatiotemporal dynamics of natural wetlands in Northeast China by integrating machine learning methods with optimization algorithms, offering new insights into ecological change drivers. His work on offshore wind turbine gearbox fault diagnosis proposed an interpretable, knowledge-driven framework that enriched mechanical reliability studies. Additionally, he advanced hyperspectral techniques for mineral alteration information extraction and developed innovative models to estimate soil heavy metal contents. These studies highlight his interdisciplinary focus combining artificial intelligence, geoscience, and environmental engineering.

Accolades and Recognition

Throughout his academic journey, Mr. Liu received multiple honors that reflect his excellence in research and innovation. He was awarded the National Scholarship and university-level first-class academic scholarships during his master’s program. His innovative projects earned recognition in provincial competitions, including awards in the “Internet+” Innovation and Entrepreneurship Contest, the “Challenge Cup,” and the Aerospace Knowledge Contest. During his undergraduate studies, he also won several distinctions in provincial surveying skill competitions, affirming his technical expertise and problem-solving ability.

Impact and Influence

Mr. Liu’s scholarly output includes multiple first-author and co-authored publications in high-impact journals indexed in SCI and EI. His research on wetlands, hyperspectral analysis, and mechanical fault diagnosis has been acknowledged in leading platforms, showcasing his ability to address both environmental and industrial challenges. Beyond publications, his patents for soil sampling and laser scanning devices demonstrate his commitment to translating research into practical technological solutions. His work not only contributes to scientific literature but also provides valuable methodologies for sustainable resource management and engineering applications.

Legacy and Future Contributions

Driven by a spirit of perseverance and innovation, Mr. Liu aspires to further his academic path through doctoral studies. His long-term vision is to refine computational methods for solving pressing environmental and engineering challenges. By integrating artificial intelligence with remote sensing and fault diagnosis systems, he seeks to contribute solutions with real-world impact. His dedication to teamwork, resilience under pressure, and scientific curiosity positions him as a researcher capable of leaving a lasting legacy in the interdisciplinary fields of environmental monitoring and intelligent engineering systems.

Publications

Article: Research on Abrasive Particle Target Detection and Feature Extraction for Marine Lubricating Oil
Authors: Chenzhao Bai, Jiaqi Ding, Hongpeng Zhang, Zhiwei Xu, Hanlin Liu, Wei Li, Guobin Li, Yi Wei, Jizhe Wang
Journal: Journal of Marine Science and Engineering
Year: 2024

Article: An axiomatic fuzzy set theory-based fault diagnosis approach for rolling bearings
Authors: Xin Wang, Hanlin Liu, Wankang Zhai, Hongpeng Zhang, Shuyao Zhang
Journal: Engineering Applications of Artificial Intelligence
Year: 2024

Article: An adversarial single-domain generalization network for fault diagnosis of wind turbine gearboxes
Authors: Xinran Wang, Chenyong Wang, Hanlin Liu, Cunyou Zhang, Zhenqiang Fu, Lin Ding, Chenzhao Bai, Hongpeng Zhang, Yi Wei
Journal: Journal of Marine Science and Engineering
Year: 2023

Article: Driving force analysis of natural wetland in Northeast plain based on SSA-XGBoost model
Authors: Hanlin Liu, Nan Lin, Honghong Zhang, Yongji Liu, Chenzhao Bai, Duo Sun, Jiali Feng
Journal: Sensors
Year: 2023

Article: Extraction of mineralized indicator minerals using ensemble learning model optimized by SSA based on hyperspectral image
Authors: Nan Lin, Hanlin Liu, Genjun Li, Menghong Wu, Delin Li, Ranzhe Jiang, Xuesong Yang
Journal: Open Geosciences
Year: 2022

Conclusion

Mr. Hanlin Liu is an emerging researcher whose academic pursuits blend civil engineering, remote sensing, and machine learning. His contributions span from ecological studies of wetlands to industrial fault diagnostics and soil heavy metal analysis, underpinned by strong technical skills and innovative methodologies. Recognized with scholarships, competition awards, and impactful publications, he has already established himself as a promising scholar. His future vision is centered on advancing scientific understanding and delivering practical solutions through rigorous doctoral research. With his blend of academic excellence, technical expertise, and research dedication, Mr. Liu represents the new generation of scholars poised to make meaningful contributions to science and society.

Hafiz Mohammad Hasan Babu | Computer Science | Lifetime Achievement in Books Award

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Prof. Hafiz Mohammad Hasan Babu | Computer Science | Lifetime Achievement in Books Award

University of Dhaka | Bangladesh

Author Profile

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Early Academic Pursuits

Prof. Hafiz Mohammad Hasan Babu began his academic journey in the realm of computer science and engineering with a strong foundation from the Brno University of Technology, Czech Republic, where he completed his M.Sc. with a focus on logic network automation. His curiosity for advanced computational systems took him to the Kyushu Institute of Technology in Japan, where he earned his Ph.D. in Computer Science and Electronics. His doctoral work concentrated on data structures for multiple-output functions and their applications in VLSI CAD, under the guidance of Prof. Dr. Tsutomu Sasao. These formative years laid the groundwork for his future innovations in quantum computing, reversible logic, and nanotechnology.

Professional Endeavors

Prof. Hasan Babu's academic career spans several decades and institutions, notably the University of Dhaka, where he served in various capacities, including as professor in the departments of Computer Science and Engineering, and Robotics and Mechatronics Engineering. His early academic roles also included positions at Khulna University. He has been deeply involved in curriculum development, student mentorship, and departmental leadership. Beyond teaching, he also contributed significantly as a research supervisor and played a critical role in developing the academic and research culture of computer science in Bangladesh.

Contributions and Research Focus

A prolific researcher, Prof. Hasan Babu has made groundbreaking contributions in the fields of quantum computing, reversible logic design, DNA computing, and machine learning applications in healthcare and agriculture. His interdisciplinary research integrates electronics, artificial intelligence, and biological systems. His most recent works delve into quantum biocomputing and nanotechnology, as evidenced by his multi-volume publications with Springer Nature and CRC Press. He has also authored numerous peer-reviewed articles on topics such as cardiovascular disease detection using mobile AI, air quality forecasting, and toxic substance identification in fruits through deep learning.

Accolades and Recognition

Prof. Hasan Babu has received numerous prestigious awards recognizing his excellence in research and scholarly contributions. These include the Dhaka University Research Excellence Recognition, the UGC Gold Medal, and the Dr. M. O. Ghani Memorial Gold Medal from the Bangladesh Academy of Sciences. His biography has been featured in “Who's Who in the World, USA.” He has also received international fellowships such as the Japanese Government Scholarship, the DAAD Fellowship from Germany, and a Czechoslovakian Government Scholarship, marking his global academic influence.

Impact and Influence

Throughout his academic life, Prof. Hasan Babu has significantly influenced the fields of computer science, electronics, and artificial intelligence. His innovations in reversible logic and DNA computing have shaped research methodologies and applications in both academia and industry. He has been instrumental in advancing computational methods that address real-world problems, particularly in environmental monitoring, biomedical diagnostics, and agricultural automation. His role as a mentor to doctoral and master’s students further amplifies his impact on the next generation of scholars.

Legacy and Future Contributions

Prof. Hasan Babu’s extensive scholarly contributions, particularly in the emerging domains of quantum AI and biocomputing, position him as a thought leader in futuristic technologies. His upcoming publications promise to offer new paradigms in nanotechnology and molecular-level computing. As he continues to mentor new researchers and expand the boundaries of interdisciplinary science, his legacy will be defined by his relentless pursuit of innovation and his dedication to fostering a globally relevant research ecosystem.

List of Book Publications

Books Published in 2025:

1. Quantum AI Emerging Technologies: Driving Innovation and Shaping the Future of Nanotechnology, Volume I, Springer Nature, Singapore.

2. Quantum AI Emerging Technologies: Driving Innovation and Shaping the Future of Nanotechnology, Volume II, Springer Nature, Singapore.

3. Quantum Biocomputing in Quantum Biology, Volume I, Springer Nature, Singapore.

4. Quantum Biocomputing in Quantum Biology, Volume II, Springer Nature, Singapore.

Book Published in 2024:
5. DNA Logic Design: Computing with DNA, World Scientific Publishing Co Pte Ltd., Singapore.

Books Published in 2023:
6. Multiple-Valued Computing in Quantum Molecular Biology, Volume I, CRC Press, USA.
7. Multiple-Valued Computing in Quantum Molecular Biology, Volume II, CRC Press, USA.

Books Published in 2022:
8. VLSI Circuits and Embedded Systems, CRC Press, USA.
9. Control Engineering Theory and Applications (Co-authored with Md. Jahangir Alam, Guoqing Hu, and Huazhong Xu), CRC Press, USA.

Books Published in 2020:
10. Quantum Computing: A Pathway to Quantum Logic Design, 2nd Edition, IOP Publishers, Bristol, UK.
11. Reversible and DNA Computing, Wiley Publishers, UK.

Journal Publications

Analyzing infant cry to detect birth asphyxia using a hybrid CNN and feature extraction approach
Authors: Samrat Kumar Dey, Khandaker Mohammad Mohi Uddin, Arpita Howlader, Md Mahbubur Rahman, Hafiz Md Hasan Babu, Nitish Biswas, Umme Raihan Siddiqi, Badhan Mazumder
Journal: Neuroscience Informatics (Elsevier)
Year: 2025

Empowering early detection: A web-based machine learning approach for PCOS prediction
Authors: Md. Mahbubur Rahman, Ashikul Islam, Forhadul Islam, Mashruba Zaman, Md Rafiul Islam, Md Shahriar Alam Sakib, Hafiz Md Hasan Babu
Journal: Journal of Informatics in Medicine (Elsevier)
Year: 2024

Computer vision based deep learning approach for toxic and harmful substances detection in fruits
Authors: Abdus Sattar, Md. Asif Mahmud Ridoy, Aloke Kumar Saha, Hafiz Md. Hasan Babu, Mohammad Nurul Huda
Journal: Heliyon (Cell Press)
Year: 2024

A Comprehensive Approach to Detecting Chemical Adulteration in Fruits Using Computer Vision, Deep Learning, and Chemical Sensors
Authors: Abdus Sattar, Md. Asif Mahmud Ridoy, Aloke Kumar Saha, Hafiz Md. Hasan Babu, Mohammad Nurul Huda
Journal: Journal of Intelligent Systems with Applications (Elsevier)
Year: 2024

A Voice assistive mobile application tool to detect cardiovascular disease using machine learning approach
Authors: Khandaker Mohammad Mohi Uddin, Samrat Kumar Dey, Hafiz Md Hasan Babu
Journal: Biomedical Materials & Devices (Springer US)
Year: 2024

Conclusion

Prof. Hafiz Mohammad Hasan Babu embodies the spirit of academic excellence and innovation in computer science. With a career rich in scholarly output, international collaborations, and student mentorship, he has become a beacon of transformative research and a visionary in integrating quantum theory with computational systems. His work continues to influence the scientific community both in Bangladesh and globally, promising continued advancements in technology and applied sciences.

Ziang Liu | Engineering | Best Researcher Award

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Mr. Ziang Liu | Engineering | Best Researcher Award

Nanjing University | China

Author Profile

Scopus

Orcid

Early Academic Pursuits

Mr. Ziang Liu began his academic journey with distinction at Tianjin University, where he earned his Bachelor of Science in Electronic Engineering. His strong foundation in engineering and mathematics laid the groundwork for advanced research and innovation. Continuing his academic trajectory, he pursued a Master of Science in Electronic Engineering at the prestigious Nanjing University, where he was recognized as an Outstanding Student and awarded the First-class Academic Scholarship.

Professional Endeavors

Ziang has accumulated valuable industry experience through impactful internships. At Meituan Shanghai, he served as an LLMs Evaluation Algorithm Intern, where he designed evaluation schemes and analyzed instruction-following capabilities across large language models such as Qwen, Doubao, ChatGPT 3.5/4, and Llama2-70B.  In another significant role at Alibaba DingTalk in Hangzhou, he worked on the back-end development of Chatmemo, an enterprise AI assistant. There, he implemented knowledge graph subgraph displays and integrated Retrieval-Augmented Generation (RAG), significantly boosting response speed and system performance.

Contributions and Research Focus

Mr. Liu’s core interests revolve around LLMs (Large Language Models), RAG (Retrieval-Augmented Generation), and knowledge graph technologies. He has contributed to the design and optimization of backend systems for intelligent applications in healthcare and enterprise settings. His work on deploying frameworks like Graph RAG and utilizing tools like Redis, MySQL, and Spring Boot has shown practical outcomes in real-world systems, particularly in performance optimization, load balancing, and cache management. His participation in the Nanjing University Intelligent Hospital Project resulted in a custom online medication purchasing system, complete with AI-powered Q&A capabilities and scalable backend infrastructure.

Accolades and Recognition

Ziang Liu’s academic excellence is evident through a remarkable series of accolades earned during both his undergraduate and postgraduate studies. He was honored as the Outstanding Student of Nanjing University in 2023 and received the First-class Academic Scholarship in 2022, recognizing his superior academic performance. His analytical and technical skills were demonstrated through competition achievements, including the Third Prize in the 19th Chinese Graduate Mathematical Modeling Competition (2022) and the Second Prize in the 18th Chinese Electronic Design Competition (2023). Earlier in his academic journey, he was named a Meritorious Winner in the Mathematical Contest in Modeling (MCM) in 2021 and was recognized as an Outstanding Graduate of Tianjin University in 2022. These accomplishments reflect his consistent dedication, innovation, and leadership in engineering and applied mathematics.

Impact and Influence

Ziang Liu’s work has made a tangible impact in both academia and industry. His efforts in improving instruction-following performance in LLMs and optimizing backend systems for enterprise AI applications have proven valuable for real-world implementation. His innovations in intelligent hospital systems demonstrate a commitment to applying advanced AI technologies to enhance societal well-being and operational efficiency.

Legacy and Future Contributions

Poised at the intersection of AI, backend engineering, and applied innovation, Mr. Ziang Liu is emerging as a key contributor to the next generation of AI infrastructure. His hands-on experience with cutting-edge technologies like gRPC, GraphRAG, JWT, and multi-threaded optimization positions him to drive future advancements in AI systems, enterprise platforms, and digital healthcare. With a strong academic record and robust technical expertise, he is well on his way to becoming a leading voice in intelligent systems development.

 

 

Publications

Channel-Dependent Multilayer EEG Time-Frequency Representations Combined with Transfer Learning-Based Deep CNN Framework for Few-Channel MI EEG Classification

Authors: Ziang Liu, Kang Fan, Qin Gu, Yaduan Ruan
Journal: Bioengineering
Year: 2025

Studying Multi-Frequency Multilayer Brain Network via Deep Learning for EEG-Based Epilepsy Detection

Authors: Weidong Dang, Dongmei Lv, Linge Rui, Ziang Liu, Guanrong Chen, Zhongke Gao
Journal: IEEE Sensors Journal
Year: 2021

Ming Cao | Engineering | Best Researcher Award

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Prof. Dr. Ming Cao | Engineering | Best Researcher Award

Nanchang University | China

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🎓 Early Academic Pursuits

Prof. Dr. Ming Cao embarked on his academic journey with a Bachelor's degree in Software Engineering  from Nanchang University. His interdisciplinary curiosity led him to pursue a Master's in Vehicle Engineering , followed by a Doctorate in Mechanical Engineering  from the same institution. This academic progression illustrates his transition from software to hardware systems, laying a solid foundation for his future in automotive and advanced manufacturing research.

🏢 Professional Endeavors

Currently serving as Associate Dean and Associate Professor at the School of Advanced Manufacturing, Nanchang University, Dr. Cao has held numerous academic positions over the years. His career began as an Assistant Lecturer, then Lecturer , and advanced to his current role in 2023. Simultaneously, he is enriching his research profile as a Postdoctoral Researcher at the prestigious Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences . Notably, he also gained international exposure as a Visiting Scholar at the University of Kansas.

🔬 Contributions and Research Focus

Prof. Cao's research sits at the intersection of mechanical engineering, microfluidics, bio-manufacturing, and artificial intelligence. His recent works focus on high-throughput digital microfluidic systems, YOLOv8-based object detection, automated inkjet printing, and cryogenic extrusion technologies. His innovative approaches are evident in impactful publications like:

  •  ➤ YOLOv8-Seg-based evaluation for bioprinting

  •  ➤ AI-enhanced microfluidic systems

  •  ➤ Smart composite hydrogels for flexible strain sensors
    These contributions aim to transform precision manufacturing, sensor development, and biomedical applications.

🏆 Accolades and Recognition

While explicit awards are not listed, Prof. Cao's continuous progression within Nanchang University, international collaborations, and his prolific publication record in Micromachines, ACS Applied Polymer Materials, and Fibers and Polymers underscore the academic community’s recognition of his innovative work and leadership in research. His appointment as Associate Dean further reflects his respected status in academic and administrative circles.

🌍 Impact and Influence

Dr. Cao's work is bridging the gap between academia and real-world manufacturing challenges. His research on smart sensors and AI-integrated fabrication methods is pushing the frontiers of intelligent manufacturing and sustainable biomedical device development. Moreover, by mentoring students and contributing to global research dialogue, he is shaping the next generation of engineers and innovators.

🔮 Legacy and Future Contributions

Looking ahead, Prof. Dr. Ming Cao is poised to make landmark contributions in precision bio-manufacturing, AI-integrated engineering, and smart materials. His leadership at Nanchang University and collaboration with CAS suggest continued influence in shaping China's advanced manufacturing roadmap. As technology rapidly evolves, his work will likely be instrumental in crafting more sustainable, intelligent, and adaptable production systems.

Publications

📄 Uniformity evaluation of bio-printer products based on an improved YOLOv8-Seg model
Authors: Cao Ming, Duan Wufeng, Ma Mengxiao, et al.
Journal: Journal of Zhejiang University (Engineering Science)
Year: 2025

📄 Design and Implementation of a High-Throughput Digital Microfluidic System Based on Optimized YOLOv8 Object Detection
Authors: Cao M, Duan W, Huang Z, Liang H, Ai F, Liu X
Journal: Micromachines
Year: 2025

📄 An automated digital microfluidic system based on inkjet printing
Authors: Wansheng Hu, Ming Cao, Lingni Liao, Yuanhong Liao, Yuhan He, Mengxiao Ma, Simao Wang, Yimin Guan*
Journal: Micromachines
Year: 2024

📄 Self-Adhesive, Antifreezing, and Antidrying Conductive Glycerin/Polyacrylamide/Chitosan Quaternary Ammonium Salt Composite Hydrogel as a Flexible Strain Sensor
Authors: Liu S, Wan L, Hu FF, Wen ZW, Cao M., Ai FR
Journal: ACS Applied Polymer Materials
Year: 2023

📄 Cryogenic Extrusion Printing of PCL-HAW Scaffolds and Self-induced Crystalline Surface Modification
Authors: Zhou K., Chen H., Xu Z., Zeng J., Cao M
Journal: Fibers and Polymers
Year: 2024

Xiaoya Wang | Computer Science | Best Researcher Award

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Ms. Xiaoya Wang | Computer Science | Best Researcher Award

Beijing University of Posts and Telecommunications | China

Author Profile

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🎓 Early Academic Pursuits

Ms. Xiaoya Wang began her academic journey with a strong foundation in electronics and communication. In 2005, she earned her Master’s degree in Communication and Information Systems from the prestigious Xi’an University of Electronic Science and Technology. Demonstrating an enduring passion for advanced research, she is currently pursuing her Ph.D. at Beijing University of Posts and Telecommunications, specializing in areas crucial to the future of signal intelligence and communications.

🏢 Professional Endeavors

Ms. Wang holds the position of Researcher at the 54th Research Institute of China Electronics Technology Group Corporation (CETC). This institute is renowned for pioneering developments in electronic systems and defense-related technologies. Within this dynamic environment, Ms. Wang plays a pivotal role in pushing forward the frontiers of signal processing and intelligent data processing, contributing to both national-level projects and global innovations.

🔬 Contributions and Research Focus

Ms. Wang’s research is deeply rooted in modulation recognition, signal feature extraction, and integrated sensing and communication (ISAC). She has co-authored impactful publications, including:

📘 "Multi-Feature AND–OR Mechanism for Explainable Modulation Recognition" in Electronics (2025), which offers insights into machine explainability in modulation recognition frameworks.
📗 "RF Signal Feature Extraction in Integrated Sensing and Communication" published in IET Signal Processing (2023), a study enhancing the performance of RF signal analysis under ISAC architectures.

Her contributions emphasize intelligent interpretation of signals, integrating machine learning mechanisms with real-time communication systems.

🏆 Accolades and Recognition

Though currently pursuing her Ph.D., Ms. Wang has already earned recognition for her innovative research and has been published in highly regarded peer-reviewed journals such as Electronics and IET Signal Processing. Her collaborative work with experts like Songlin Sun and Haiying Zhang further illustrates her influence in multidisciplinary research teams.

🌐 Impact and Influence

Ms. Wang’s research holds strategic importance in enhancing signal intelligence, particularly in military communication systems and next-gen wireless technologies. Her work bridges theoretical models with real-world applicability, making signal analysis more transparent, reliable, and intelligent. Her development of explainable AI mechanisms in signal processing is especially vital for defense and critical communication infrastructures.

🌟 Legacy and Future Contributions

As she continues her doctoral studies and deepens her involvement in cutting-edge research, Ms. Xiaoya Wang is poised to be a leading force in intelligent signal processing. Her legacy will likely lie in making signal systems more secure, adaptive, and interpretable, laying the groundwork for smart communication systems of the future. Her forward-thinking approach ensures she will remain a vital contributor to both academic advancement and industrial innovation.

Publications

📄 Multi-Feature AND–OR Mechanism for Explainable Modulation Recognition
Authors: Xiaoya Wang, Songlin Sun, Haiying Zhang, Yuyang Liu, Qiang Qiao
Journal: Electronics
Publication Year: 2025

📄 RF Signal Feature Extraction in Integrated Sensing and Communication
Authors: Xiaoya Wang, Songlin Sun, Haiying Zhang, Qiang Liu, Sourabh Sahu
Journal: IET Signal Processing
Publication Year: 2023

Benjamin Kwakye Danso | Computer Science | Best Paper Award

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Mr. Benjamin Kwakye Danso | Computer Science | Best Paper Award

University of Science and Technology of China | China

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🌱 Early Academic Pursuits

Mr. Benjamin Kwakye Danso began his academic journey in Ghana, earning a DBE in Science and Mathematics from the University of Cape Coast in 2011. He continued to build a strong foundation in mathematics with a B.Ed. in Mathematics from Valley View University. His academic excellence led to recognition on the Vice Chancellor’s List of Excellent Students. Driven by a passion for analytical sciences, he pursued a Master’s degree in Mathematics at Hohai University, China, and is currently a Ph.D. candidate in Statistics at the University of Science and Technology of China, focusing on cutting-edge statistical methods and optimization techniques.

💼 Professional Endeavors

Mr. Kwakye Danso has a rich background in teaching and project leadership. He served as a mathematics and integrated science teacher in Ghana’s education system, holding leadership roles such as Secretary of the PTA and Head of the Examination Committee. His international exposure expanded in China, where he leads the Project Management Team at Grace Outreach Global Foundation. He has also supported various academic and cultural initiatives, including student registration and the Sino-Cultural Festival organization.

🔬 Contributions and Research Focus

Mr. Kwakye Danso's research is deeply rooted in optimization, metaheuristic algorithms, feature selection, and mathematical statistics. His 2024 publication in Expert Systems with Applications introduces a particle-guided metaheuristic algorithm for complex global optimization problems. His interdisciplinary work spans radar systems, agricultural technologies, and data science, contributing to IEEE conferences and journals like Signal Processing, Science Journal of Chemistry, and Pharmacognosy Journal. His academic rigor is complemented by practical insights in data analysis and high-dimensional feature modeling.

🏆 Accolades and Recognition

His academic achievements have been recognized with Chinese University Scholarships from both Hohai University and the University of Science and Technology of China. Additionally, his placement on the Vice Chancellor’s List reflects his sustained excellence. He has also been selected for prestigious international conferences, such as ASPAI 2022 and IEEE ICSIP 2020.

🌍 Impact and Influence

Benjamin's work bridges applied mathematics and real-world challenges, particularly in optimization and data modeling for signal processing and agricultural innovation. His research has contributed to solving high-dimensional problems in radar communication and food science, while also influencing educational standards in Ghana. His leadership in academic communities and volunteering initiatives exemplifies a commitment to societal advancement through science.

🔮 Legacy and Future Contributions

Mr. Kwakye Danso’s scholarly path showcases an inspiring trajectory of growth from local educator to international researcher. With ongoing Ph.D. research and active membership in global academic networks such as the Institute of Mathematical Statistics and OAAD, he is poised to make substantial contributions to AI-driven optimization, statistical modeling, and STEM education in Africa. His future work promises to enrich both academic theory and practical applications.

 

Publications

📝 Particle guided metaheuristic algorithm for global optimization and feature selection problems

Authors: B.D. Kwakye (Benjamin Danso Kwakye), Y. Li (Yongjun Li), H.H. Mohamed (Halima Habuba Mohamed), E. Baidoo (Evans Baidoo), T.Q. Asenso (Theophilus Quachie Asenso)

Journal: Expert Systems with Applications

Year: 2024

 

Fabio Matiussi | Radiology | Innovative Research Award

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Dr. Fabio Matiussi | Radiology | Innovative Research Award

Imaging Institute of Southern Switzerland | Switzerland

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🎓 Early Academic Pursuits

Dr. Fabio Mattiussi’s journey began with a firm commitment to healthcare and imaging sciences. He earned his degree in Medical Radiologic Technology from the University of Insubria in 2016, which laid the foundation for his clinical expertise. Eager to expand his horizons, he pursued advanced studies in healthcare system administration and health management, followed by a strategic academic leap into the realm of computer engineering. These steps reflect his unique vision to combine traditional radiology with emerging digital technologies.

🏥 Professional Endeavors

Dr. Mattiussi has served across a range of reputable healthcare institutions throughout Italy and Switzerland, building a versatile portfolio in diagnostic imaging. From private clinics in the Varese province to key positions at ASST Sette Laghi and now at the Ente Ospedaliero Cantonale in Lugano, he has mastered the art and science of radiology. His proficiency spans traditional radiography, computed tomography (CT), and magnetic resonance imaging (MRI), making him a trusted expert in patient diagnostics.

🤖 Contributions and Research Focus

Blending clinical know-how with advanced data science, Dr. Mattiussi has ventured into uncharted territory—merging machine learning with diagnostic radiology. With certifications from top institutions like Meta, IBM, Google, and DataMasters, he has cultivated deep expertise in neural networks, Python programming, and AI applications in medical imaging. His current focus lies in developing intelligent systems that can revolutionize image interpretation, automate detection, and significantly enhance diagnostic accuracy.

🏅 Accolades and Recognition

While his formal recognitions are still on the rise, Dr. Mattiussi’s consistent pursuit of innovation has earned him recognition within both the medical and tech education spheres. His completion of numerous elite certifications and active engagement in online scientific communities marks him as a forward-thinking professional committed to lifelong learning and impactful research.

🌍 Impact and Influence

Dr. Mattiussi’s influence spans both clinical and technological domains. His ability to work seamlessly across languages and disciplines empowers him to contribute to international healthcare dialogues. By staying at the cutting edge of both patient care and digital innovation, he serves as a bridge between traditional radiology departments and the fast-evolving world of AI-driven diagnostics.

🔮 Legacy and Future Contributions

Dr. Fabio Mattiussi is poised to leave a legacy as a pioneer in the integration of artificial intelligence into medical imaging. His academic rigor, technical acumen, and compassionate healthcare experience equip him to lead future innovations in radiology. As machine learning continues to redefine medical practices, Dr. Mattiussi is set to be at the forefront—developing tools, systems, and protocols that will shape the future of global healthcare.

Publications

📄  Use of Open-Source Large Language Models for Automatic Synthesis of the Entire Imaging Medical Records of Patients: A Feasibility Study

Authors: Fabio Mattiussi, Francesco Magoga, Simone Schiaffino, Vittorio Ferrari, Ermidio Rezzonico, Filippo Del Grande, Stefania Rizzo

Journal: Tomography

Year: 2025