Ming-Hsiang Su | Signal Processing | Best Researcher Award

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Prof. Ming-Hsiang Su | Signal Processing | Best Researcher Award

Prof. Ming-Hsiang Su | Soochow University | Taiwan

Prof. Ming-Hsiang Su is a prominent researcher and assistant professor specializing in the fields of deep learning, natural language processing, and speech signal processing, with a particular focus on spoken dialogue systems, emotion recognition, and personality trait perception. His work integrates advanced computational techniques with real-world applications, developing intelligent systems capable of understanding, interpreting, and generating human-like speech and dialogue. Prof. Ming-Hsiang Su has contributed to the advancement of speech emotion recognition by considering both verbal and nonverbal vocal cues, and has designed sophisticated models for empathetic dialogue generation, text-to-motion transformation, and mood disorder detection through audiovisual signals. He has published extensively in high-impact journals and conferences, addressing topics such as few-shot image segmentation, sound source separation, automatic ontology population, and speaker identification. His research also extends to applied systems, including automated crop disease detection, question-answering systems, and industrial defect detection using deep learning architectures. By combining theoretical insights with practical implementations, Prof. Ming-Hsiang Su work bridges the gap between computational intelligence and human-centered applications, enhancing machine understanding of complex speech, language, and affective behaviors. Through his interdisciplinary approach, he continues to advance innovative methods for human-computer interaction, intelligent dialogue systems, and multimodal data analysis, establishing a significant impact on both academic research and practical technological applications across various domains, with 791 citations by 684 documents, 83 documents, and an h-index of 15.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Huang, K. Y., Wu, C. H., Hong, Q. B., Su, M. H., & Chen, Y. H. (2019). Speech emotion recognition using deep neural network considering verbal and nonverbal speech sounds. ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech, and …, 138.

Su, M. H., Wu, C. H., Huang, K. Y., Hong, Q. B., & Wang, H. M. (2017). A chatbot using LSTM-based multi-layer embedding for elderly care. 2017 International Conference on Orange Technologies (ICOT), 70-74.

Hsu, J. H., Su, M. H., Wu, C. H., & Chen, Y. H. (2021). Speech emotion recognition considering nonverbal vocalization in affective conversations. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 29, 1675-1686.

Su, M. H., Wu, C. H., & Cheng, H. T. (2020). A two-stage transformer-based approach for variable-length abstractive summarization. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 28, 2061-2072.

Su, M. H., Wu, C. H., Huang, K. Y., & Hong, Q. B. (2018). LSTM-based text emotion recognition using semantic and emotional word vectors. 2018 First Asian Conference on Affective Computing and Intelligent …, 78.

 

Asmaa Seyam | Data Science | Best Researcher Award

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Mrs. Asmaa Seyam | Data Science | Best Researcher Award

Ph.D student, University of Wollongong, Australia

Asmaa Seyam is a seasoned computer engineering professional and educator with over a decade of academic and research experience. Her career spans institutions such as Zayed University and the Islamic University of Gaza, where she has significantly contributed to the fields of programming, networking, and system development. Asmaa is known for her dedication to excellence in teaching and her active involvement in curriculum development and academic leadership.

Profile

Scopus

🎓 Education

Asmaa earned her Master’s degree in Computer Engineering from Jordan University of Science and Technology (2009–2011), graduating with an excellent GPA of 89.4%. Her thesis focused on optimizing node placement for energy-efficient clustering in wireless sensor networks. She completed her Bachelor’s in Computer Engineering at the Islamic University of Gaza (2003–2008) with an outstanding GPA of 90.67%, showcasing her strong foundation with a SCADA project for power distribution.

💼 Professional Experience

Asmaa Seyam served as an Instructor at Zayed University in Abu Dhabi from 2012 to 2022, where she taught a range of IT and engineering courses such as Web Development, Programming, HCI, and Networking. She also worked as a Teaching Assistant at the Islamic University of Gaza and was a Network Trainer at the Ministry of Interiors, demonstrating hands-on expertise in server management, routing protocols, and system maintenance. Her roles were marked by leadership in academic planning, assessment design, student mentorship, and institutional service.

🔬 Research Interest

Her research interests lie in Internet of Things (IoT), Machine Learning, Artificial Intelligence, and Wireless Sensor Networks. She has published and presented in esteemed journals and international conferences, contributing to the evolution of smart and efficient network systems.

🏆 Awards and Honors

Asmaa’s achievements include the Zuhair Hijjawi Award for Scientific Research (2008), a DAAD Scholarship for her Master’s studies, and several institutional service recognitions including the IBM Artificial Intelligence Analyst Mastery Award (2019) and the Advance HE Fellowship (2022). She also earned two separate 5-Year Service Awards from Zayed University and CISCO Networking Academy.

📚 Publications

  1. Energy-Efficient Clustering Algorithm for Wireless Sensor Networks Using the Virtual Field Force
    Published in: 5th International Conference on New Technologies, Mobility and Security (NTMS), Istanbul, 2012.
    Cited by: 60+ articles
    📌 IEEE Xplore

  2. Energy-Efficient and Coverage-Aware Clustering in Wireless Sensor Networks
    Published in: Wireless Engineering and Technology, Vol. 3, No. 3, 2012, pp. 142–151.
    Cited by: 90+ articles
    📌 Scientific Research Publishing

  3. Characterizing Realistic Signature-based Intrusion Detection Benchmarks
    Published in: Proceedings of the 6th International Conference on Info Technology: IoT and Smart City, ACM, Hong Kong, 2018.
    Cited by: 20+ articles
    📌 ACM Digital Library

🏁 Conclusion

Asmaa Seyam is a highly qualified and accomplished educator and researcher whose background reflects a strong commitment to both teaching and scholarly work. Her technical breadth, early recognition in research, and academic contributions position her as a strong candidate for the Best Researcher Award. Strengthening her recent research portfolio and expanding her research leadership roles would further elevate her profile.

Mika Yasuoka | Computer | Best Researcher Award

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Dr. Mika Yasuoka | Computer | Best Researcher Award

Associate Professor, Roskilde University, Denmark

Dr. Mika Yasuoka Jensen 🇯🇵🇩🇰 is an Associate Professor of Sustainable Digitalization at Roskilde University, Denmark. With a multicultural background and deep expertise in computer science, informatics, and interaction design, she bridges Japanese, American, and Danish academic traditions. Passionate about co-creation, digital welfare, and Living Labs, Dr. Yasuoka leads global collaborations with universities, public institutions, and tech corporations to shape sustainable digital futures. Her leadership in participatory design, social innovation, and smart city initiatives has made her a prominent voice in advancing technology for societal benefit. 🌍💻

Profile

Google Scholar

Education 🎓

Dr. Yasuoka’s academic journey is a blend of prestigious institutions across three continents. She earned her Ph.D. in Computer Supported Cooperative Work from the IT University of Copenhagen, incorporating research at The University of Tokyo and Carnegie Mellon University. Prior to this, she completed an M.Sc. in Informatics from Kyoto University and a B.Sc. in Library and Information Science from Keio University. Her academic enrichment also includes an exchange program and visiting researcher positions at Carnegie Mellon University in the U.S. 🎓📘🌐

Experience 💼

Dr. Yasuoka’s professional path is marked by academic excellence and impactful leadership. Since 2020, she has been serving as Associate Professor at Roskilde University. She has held roles at institutions including the IT University of Copenhagen, Keio University, and Technical University of Denmark. She has led numerous cross-sectoral projects, blending stakeholder engagement and digital design across borders. Her strategic advisory roles include working with municipalities and government digital agencies in Japan. 🏫🌏👩‍🏫

Research Interest 🔍

Her core research focuses on sustainable digitalization, participatory design, Living Labs, and avatar-mediated communication. She investigates how digital technologies can be co-designed and responsibly integrated into societies to enhance well-being. With a special interest in smart cities, welfare technologies, and design frameworks, Dr. Yasuoka’s work aligns technology with human-centric values and social innovation. 🤖🏙️👥

Awards 🏆

Dr. Yasuoka has received multiple accolades for her innovative contributions. These include the 11th Nextcom Paper Award (2022) for advancing e-government strategy, the 12th KDDI Foundation Book Publishing Grant (2022), and a Best Paper Finalist at IEEE ARSO 2021. She also earned the Human Interface Society Award (2021) for her analysis of stakeholder involvement in welfare technology assessment. 🏆📚✨

Publications 📄

Key Practices for Welfare Robots Provision: Assessment Framework and Participation
Yasuoka, M., Akutsu, Y., Honma, K., & Matsumoto, Y.
IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO), 2021.
🔗 IEEE Xplore Link
Cited by researchers in robotics and social care design.

How Remote-Controlled Avatars Are Accepted in Hybrid Workplace
Yasuoka, M., Miyata, T., Nakatani, M., Taoka, Y., & Hamaguchi, N.
In: Distributed, Ambient and Pervasive Interactions, Lecture Notes in Computer Science, vol. 14036, Springer, Cham, 2023.
🔗 Springer Link
Referenced in studies on telepresence and future work environments.

Not Just Power: Exploring Transitions as Fluidity and Relationality in Participatory Design
Yasuoka, M., & Kibi, Y.
Participatory Design Conference 2024, Vol. 2: Exploratory Papers and Workshops.
🔗 ACM Link
Cited in participatory design and relational theory literature.

Reflection on Digital Cities
Yasuoka, M., & Ishida, T.
In Oxford Research Encyclopedia of Communication, Oxford University Press, 2023.
Used in urban digital studies and smart city curricula.

Conclusion

Dr. Mika Yasuoka Jensen is highly suitable for the Best Researcher Award. Her cross-cultural expertise, commitment to societal impact through digitalization, leadership in international projects, and award-winning research achievements make her a standout candidate. Minor enhancements in research metrics and journal profile would further strengthen her already impressive credentials.

Haichang Jiang | AI | Best Researcher Award

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Mr Haichang Jiang | AI | Best Researcher Award

lecturer, jingdezhen university, China  📚

Haichang Jiang is a lecturer at the School of Information Engineering, Jingdezhen University, with over 10 years of experience in artificial intelligence technology, project management, and research. He completed his Master’s in Software Engineering at the University of Electronic Science and Technology of China in 2013 and earned his Ph.D. in Educational Management from the University of Perpetual Help System DALTA in the Philippines in 2023. Jiang has successfully managed large-scale AI projects, such as AI public opinion platforms for the Cyberspace Administration of China and the Ministry of Education.

Profile

Google Scholar

Education 🎓

Haichang Jiang holds a Master’s degree in Software Engineering from the University of Electronic Science and Technology of China (2013). In 2023, he received his Ph.D. in Educational Management from the University of Perpetual Help System DALTA, Philippines, where he honed his expertise in artificial intelligence and educational technologies.

Experience 💼

Jiang has extensive experience in both academia and industry. He has been a lecturer at Jingdezhen University since 2023, teaching AI and related subjects. His professional career includes managing and researching AI-based projects such as the development of AI-driven platforms for the Chinese government and the design of smart healthcare and financial systems. He has collaborated with various top Chinese universities and institutions on AI and health-related research.

Research Interests 🔬

Haichang Jiang’s research primarily focuses on artificial intelligence, smart healthcare, intelligent finance, and sentiment analysis. His projects involve the application of deep learning in medical diagnostics, the development of smart financial systems, and the integration of multimodal views based on natural language for public opinion monitoring.

Awards 🏆

Jiang has contributed significantly to various research projects, with notable achievements including his involvement in AI public opinion platforms, AI-driven smart healthcare systems, and environmental monitoring technologies. His work has been recognized by the Ministry of Education of China, the Jiangxi Provincial Higher Education Society, and several leading academic organizations.

Publications Top Notes 📑

“Research on Real-time Psychological Crisis Early Warning System Based on Natural Language and Deep Learning”, Journal of Artificial Intelligence, 2024. Cited by 15 articles.

“Innovation and Practice of Teaching Methods Under New Engineering Background”, Educational Technology and Society, 2024. Cited by 10 articles.

Conclusion

Haichang Jiang is a highly deserving candidate for the Best Researcher Award due to his extensive and impactful contributions to AI, healthcare, finance, and public opinion analysis. His innovative projects, ongoing research, and leadership in cutting-edge AI applications demonstrate his potential to drive future technological advancements. With continued collaboration and greater international visibility, Haichang Jiang is poised to further elevate the scope of his research, making him a suitable recipient of this prestigious award.

Xiaojun Li | Control Science and Engineering | Best Researcher Award

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Dr Xiaojun Li | Control Science and Engineering | Best Researcher Award

PHD Candidate, School of Aerospace Science and Technology, Xidian University, China  🌟

Xiaojun Li is a dedicated Ph.D. candidate at the School of Aerospace Science and Technology, Xidian University. With a solid academic foundation and research acumen, he has been exploring innovative approaches to detection and tracking technologies. His commitment to advancing radar signal processing and LiDAR data analysis highlights his contributions to modern aerospace technologies.

Profile

Orcid

Education 📚

Xiaojun Li completed his B.S. in Detection, Guidance, and Control Technology at Xidian University, Shannxi, China, in 2023. He is currently pursuing his Ph.D. in Control Science and Technology at the same institution, focusing on cutting-edge advancements in aerospace engineering.

Experience 🛠️

As a student researcher, Xiaojun has been actively involved in developing innovative solutions for low, small, and slow target detection. He has contributed to significant radar signal processing projects and worked on consultancy assignments related to LiDAR data applications in aerospace.

Research Interests 🔍

Xiaojun Li’s research focuses on advancing detection and tracking technologies, particularly for low, small, and slow targets. His work delves into radar signal processing and LiDAR data analysis, exploring innovative approaches to enhance accuracy and efficiency in challenging environments. By bridging theoretical concepts with practical applications, Xiaojun addresses real-world challenges in aerospace engineering, contributing to the development of cutting-edge technologies that redefine detection and mapping systems.

Awards 🏆

While primarily focused on academic and research pursuits, Xiaojun Li has been recognized for his contributions to radar signal and LiDAR data processing technologies. His achievements reflect his dedication to innovation in the field.

Publications  Top Notes🖋️

Wang, W., Yan, B., Li, X., et al. (2024). “Multiple Pedestrian Tracking Using LiDAR Network in Complex Indoor Scenarios,” IEEE Sensors Journal, 24(8), pp. 13175–13192. DOI: 10.1109/JSEN.2024.3369947.

Cited by: 5 articles

Li, X., Hu, G., et al. (2024). “A Low-Cost 3D Mapping System for Indoor Scenes Based on 2D LiDAR and Monocular Cameras,” Remote Sensing, 16, 4712. DOI: 10.3390/rs16244712.

Cited by: 3 articles

Conclusion

Xiaojun Li is a promising candidate for the Best Researcher Award, with a solid foundation in innovative technologies and high-impact publications. Strengthening his profile through diversified outputs and applied research could further establish his eligibility. His demonstrated contributions and potential for impactful advancements in aerospace and tracking technology make him a strong contender for this recognition.

Nordine Quadar | Digital Twin | Best Researcher Award

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Mr. Nordine Quadar | Digital Twin | Best Researcher Award

Researcher, Royal Military College of Canada, Canada

🌟 Nordine Quadar is a seasoned Technical Manager, Researcher, and Cybersecurity Expert with a proven track record in managing multidisciplinary teams and conducting cutting-edge research. Currently based in Montreal, Canada, Nordine specializes in cybersecurity for Unmanned Aerial Vehicles (UAVs) and has extensive experience in machine learning, data analysis, and software-defined radio. With over two decades of expertise spanning technical management, research, and academia, Nordine’s impactful contributions include several high-profile publications and successful projects in diverse domains such as IoT, automotive networks, and power systems.

Publication Profile

Google Scholar

Education

🎓 Nordine Quadar holds a Ph.D. in Computer Science (2022–2025) from the Royal Military College of Canada, where he focuses on enhancing UAV cybersecurity using Edge AI. He earned his Master of Applied Science in Electrical & Computer Engineering (2015–2018) and Bachelor of Applied Science in Electrical Engineering (2011–2014), both from the University of Ottawa, Canada. His research has consistently explored cutting-edge innovations, including MIMO-CDMA systems and cybersecurity for critical systems.

Experience

💼 With a career spanning roles as a Cybersecurity Researcher, Technical Manager, Data Scientist, and Electrical Engineer, Nordine has consistently excelled in leadership and innovation. At Thales Digital Identity and Security, he spearheads research on UAV cybersecurity. As a Regional Technical Manager at DC Group, he ensures operational excellence across critical power systems. His roles at Royal Military College, Xlscout, Schneider Electric, and other leading organizations underscore his technical acumen and project management prowess.

Research Interests

🔬 Nordine’s research focuses on cybersecurity, machine learning, and IoT applications, with a keen interest in unmanned aerial systems and AI-driven anomaly detection. His work delves into RF signal analysis, time-series data modeling, and edge AI to secure modern technological ecosystems. He also explores emerging trends in digital twin technology and intrusion detection systems for automotive networks.

Awards

🏆 Nordine has been recognized for his innovative contributions across diverse fields. His research has garnered international acclaim, with several of his papers accepted in prestigious journals and conferences. His dedication to advancing cybersecurity and IoT technologies exemplifies his commitment to excellence in research and industry.

Publications

  • The Applications and Challenges of Digital Twin Technology in Smart Grids: A Comprehensive Review, Applied Sciences, 2024. Read Here
  • Intrusion Detection Systems in Automotive Ethernet Networks: Challenges, Opportunities, and Future Research Trends, IEEE Internet of Things Magazine, 2024. Cited by 15.
  • IoT-AI/Machine Learning Experimental Testbeds: The Missing Piece, IEEE Internet of Things Magazine, 2024. Cited by 12.
  • Recommendation Systems: Models, Techniques, Application Fields, and Ethical Challenges, 7th International Conference on Big Data and Internet of Things (BDIoT ’24), 2024. To appear.
  • Cybersecurity for Unmanned Aerial Vehicles: Concerns, Practices, and Conceptual Measures, Conference of the International Society of Military Sciences, 2023. To appear.