Kun He | Computer Science | Research Excellence Award

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Assoc Prof Dr. Kun He | Computer Science | Research Excellence Award 

Renmin University | China

Dr. Kun He is an accomplished computer scientist and currently serves as an Associate Professor at Renmin University of China (since January 2023). His academic journey reflects a strong foundation in theoretical computer science, backed by extensive research experience across leading Chinese institutions. Before joining Renmin University, he worked at the Institute of Computing Technology (ICT), Chinese Academy of Sciences (CAS), first as an Assistant Researcher (2021–2022) and later as an Associate Researcher (2022). He also completed a postdoctoral fellowship at Shenzhen University between 2019 and 2021. Dr. He earned his Ph.D. in Computer Science from ICT, CAS in 2019 under the supervision of Prof. Xiaoming Sun. He also holds a Master’s degree from ICT, CAS and a Bachelor of Engineering in Computer Science from Wuhan University. His research centers on the theory of computing, with particular emphasis on probabilistic methods, sampling algorithms, quantum computing, combinatorial structures, and theoretical machine learning. His work has significantly advanced algorithmic techniques related to the Lovász Local Lemma (LLL), Holant problems, and random constraint satisfaction. Over the years, Dr. He has received numerous prestigious awards recognizing the impact and quality of his research. These include the New Hundred Stars of ICT (2021), the Outstanding Doctoral Dissertation Award of the China Computer Federation (2020), the Special Award for the President of CAS (2019), and the National Scholarship of China (2018). These honors highlight his early and sustained contributions to theoretical computer science. Dr. He has published extensively in top-tier venues such as SODA, STOC, FOCS, ITCS, and Random Structures & Algorithms. His notable works include breakthroughs on the Moser–Tardos algorithm, deterministic counting versions of the Lovász Local Lemma, sampling solutions to random CNF formulas, and quantum extensions of classical combinatorial frameworks. Several of his papers have been widely cited and recognized, including a top-downloaded publication in Random Structures & Algorithms (2020). Recently, his research continues to push theoretical boundaries, with upcoming papers on the phase transition of the Sinkhorn–Knopp algorithm and efficient approximation schemes for Holant problems. Dr. He also actively works on emerging topics involving perfect sampling and permutation constraints within the Lopsided LLL regime, with multiple manuscripts currently under submission. With strong expertise, a prolific publication record, and multiple high-impact contributions, Dr. Kun He stands as a leading figure in modern theoretical computer science.

Profiles: Scopus | Google Scholar

Featured Publications

He, K., Li, L., Liu, X., Wang, Y., & Xia, M. (2025). Variable version Lovász Local Lemma: A tale of two boundaries. Information and Computation, 105386.

He, K. (2025). Phase transition of the Sinkhorn-Knopp algorithm. arXiv preprint arXiv:2507.09711.

He, K., Li, Z., Qiu, G., & Zhang, C. (2025). FPTAS for Holant problems with log-concave signatures. In Proceedings of the 2025 Annual ACM–SIAM Symposium on Discrete Algorithms (SODA).

He, K., Qiu, G., & Sun, X. (2024). Sampling permutations satisfying constraints within the lopsided local lemma regime. arXiv preprint arXiv:2411.02750.

He, K., Qiu, G., & Sun, X. (2024). Sampling permutations satisfying constraints within and beyond the local lemma regime. arXiv e-prints, arXiv:2411.02750.

He, K., Li, Q., & Sun, X. (2023). Moser-Tardos algorithm: Beyond Shearer’s bound. In Proceedings of the 2023 Annual ACM–SIAM Symposium on Discrete Algorithms (SODA).

He, K., Wang, C., & Yin, Y. (2023). Deterministic counting Lovász Local Lemma beyond linear programming. In Proceedings of the 2023 Annual ACM–SIAM Symposium on Discrete Algorithms (SODA).

He, K., Wu, K., & Yang, K. (2023). Improved bounds for sampling solutions of random CNF formulas. In Proceedings of the 2023 Annual ACM–SIAM Symposium on Discrete Algorithms (SODA).

He, K., Wang, C., & Yin, Y. (2022). Sampling Lovász Local Lemma for general constraint satisfaction solutions in near-linear time. In 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS).

Dinesh Babu M | Engineering | Best Researcher Award

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Dr. Dinesh Babu M | Engineering | Best Researcher Award

Rajalakshmi Institute of technology | India 

Dr. M. Dinesh Babu, B.E., M.Tech., Ph.D., is a distinguished academic and researcher recognized among the Top 2% Scientists Worldwide in the subfield of Energy for the year 2023 by Elsevier and Stanford University. He holds a Ph.D. in Energy Systems Engineering from the College of Engineering, Anna University, Chennai, where his doctoral research focused on “Studies on the Effect of Internal Longitudinal Fins and Nanoparticles on the Performance of Solar Flat Plate Collectors.” He also holds an M.Tech. in Energy Systems Engineering from Vellore Institute of Technology (VIT), Vellore, and a B.E. in Mechanical Engineering from Sriram Engineering College, University of Madras, both with First Class distinction. With over 21 years of teaching and research experience, Dr. Dinesh Babu has served in reputed institutions such as Dr. M.G.R. University, Sathyabama University, R.M.K. Engineering College, Panimalar Engineering College, and currently, as a Professor at Rajalakshmi Institute of Technology, Chennai. His academic contributions encompass teaching core subjects like Heat and Mass Transfer, Thermodynamics, Thermal Engineering, Power Plant Engineering, Machine Design, Manufacturing Technology, Environmental Science, and Entrepreneurship Development. Dr. Babu has an outstanding research profile with 93 publications in Scopus, SCI, and Web of Science-indexed journals, achieving a cumulative impact factor of 302.54. His research has garnered over 3,500 citations on Google Scholar (h-index: 32, i10-index: 52), 3,177 citations on Scopus (h-index: 31), and 2,978 citations with 15,220 reads on ResearchGate. He has also published two patents and has four ongoing research papers under review. He currently supervises four Ph.D. research scholars registered under Anna University (Supervisor ID: 3120042). His research interests include renewable energy systems, solar thermal engineering, nanofluids, biofuels, combustion and emission analysis, and sustainable manufacturing. Dr. Babu has designed innovative projects such as a 50 LPD copper solar water heater with a ladder-type heat exchanger and has secured funding through initiatives like the RIT-FIT Seed Money Fund and a SERB project proposal worth ₹16.1 lakhs. An active academic contributor, Dr. Babu serves as a Doctoral Committee Member at Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, and frequently participates as a resource person and reviewer for journals and research programs. He has completed multiple Elsevier Research Academy certifications on topics such as producing highly visible research, academia–industry collaboration, journal impact metrics, and open hardware innovation. Dr. M. Dinesh Babu’s exemplary academic dedication, prolific research output, and consistent pursuit of innovation in the field of energy systems engineering have earned him a reputation as one of India’s leading scholars in sustainable and renewable energy technologies.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Yuvarajan, D., Babu, M. D., Beem Kumar, N., & Kishore, P. A. (2018). Experimental investigation on the influence of titanium dioxide nanofluid on emission pattern of biodiesel in a diesel engine. Atmospheric Pollution Research, 9(1), 47–52.

Radhakrishnan, S., Munuswamy, D. B., Devarajan, Y., T., A., & Mahalingam, A. (2018). Effect of nanoparticle on emission and performance characteristics of a diesel engine fueled with cashew nut shell biodiesel. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 40, 1–10.

Sathiyamoorthi, R., Sankaranarayanan, G., Munuswamy, D. B., & Devarajan, Y. (2021). Experimental study of spray analysis for Palmarosa biodiesel‐diesel blends in a constant volume chamber. Environmental Progress & Sustainable Energy, 40(6), e13696.

Devarajan, Y., Munuswamy, D. B., & Mahalingam, A. (2018). Influence of nano-additive on performance and emission characteristics of a diesel engine running on neat neem oil biodiesel. Environmental Science and Pollution Research, 25(26), 26167–26172.

Devarajan, Y., Munuswamy, D. B., Nagappan, B., & Pandian, A. K. (2018). Performance, combustion and emission analysis of mustard oil biodiesel and octanol blends in diesel engine. Heat and Mass Transfer, 54(6), 1803–1811.

Devarajan, Y., Munuswamy, D. B., & Mahalingam, A. (2019). Investigation on behavior of diesel engine performance, emission, and combustion characteristics using nano-additive in neat biodiesel. Heat and Mass Transfer, 55(6), 1641–1650.

Pandian, A. K., Munuswamy, D. B., Radhakrishnan, S., & Devarajan, Y. (2018). Emission and performance analysis of a diesel engine burning cashew nut shell oil biodiesel mixed with hexanol. Petroleum Science, 15(1), 176–184.

Devarajan, Y., Mahalingam, A., Munuswamy, D. B., & Arunkumar, T. (2018). Combustion, performance, and emission study of a research diesel engine fueled with palm oil biodiesel and its additive. Energy & Fuels, 32(8), 8447–8452.

Kangwon Lee | Computer Science | Best Researcher Award

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Mrs. Mihaela Corina Radu | Reproductive Health | Excellence in Research 

Carol Davila University of Medicine and Pharmacy Bucharest, Romania.

Radu Mihaela Corina is a Romanian midwifery expert and academic dedicated to improving maternal healthcare. She currently serves as an Associate University Assistant at UMF Carol Davila Bucharest, contributing to both the Department of General and Specific Nursing and the Department of Microbiology, Parasitology, and Virology. With extensive clinical experience, she is also the Head Midwife at Dr. Constantin Andreoiu County Emergency Hospital. Beyond academia, she is actively engaged in European midwifery policy, serving as a member of the Ethics Committee of the European Midwives Association and as a National Expert for Romania in an EU-funded midwifery sectoral project.

Profile

Orcid

🎓 Education

Radu Mihaela Corina has pursued an extensive academic journey in the field of medicine and midwifery. She is currently a PhD candidate in Medicine (2021 – Present) at Carol Davila University of Medicine and Pharmacy, Romania, where she is advancing her expertise in maternal and reproductive healthcare. She holds a Master’s Degree in Medical & Public Health Management (2019 – 2021) from the same institution, graduating with a perfect 10.00 GPA, demonstrating her dedication to academic excellence and healthcare leadership. Her foundational training in midwifery was completed with a Bachelor’s Degree in Midwifery (2014 – 2018) at UMF Carol Davila, Romania, where she distinguished herself as the Class Leader, showcasing her leadership skills and commitment to the profession from the early stages of her career.

💼 Professional Experience

With a strong background in midwifery and maternal healthcare, Radu Mihaela Corina has been actively contributing to both academia and clinical practice. Since 2021, she has been serving as an Associate University Assistant at UMF Carol Davila Bucharest, where she plays a key role in training future midwives and healthcare professionals. In parallel, she holds the position of Head Midwife at Dr. Constantin Andreoiu County Emergency Hospital since 2022, overseeing maternity care and ensuring the highest standards in obstetric practice.

Her passion for maternal education led her to work as a Lecturer in Prenatal Courses at the Rhodos Proviva Family Health Education Center (2020 – 2022), where she provided essential guidance to expectant mothers. Additionally, from 2018 to 2022, she served as the Head Midwife in the Birth Block at Obstetrics and Gynecology Hospital, Ploiesti, where she played a crucial role in labor and delivery management, ensuring safe and effective maternity care. Through these roles, she continues to make a significant impact in both education and clinical midwifery.

🔬 Research Interests

Maternal and Child Health 🏥

Midwifery Education & Practice 👶

Reproductive Health & Ethics 🧬

Medical Policy and Public Health 📊

🏆 Awards & Recognitions

2025: Member of the Ethics Committee, European Midwives Association

2024: National Expert for Romania, EU Project on Midwifery Professional Standards

2022 – Present: AMI Delegate, General Council, International Confederation of Midwives

2020 – Present: Vice President, Association of Independent Midwives, Romania

📚 Selected Publications

(2025) Validation of a Questionnaire Assessing Pregnant Women’s Perspectives on Addressing the Psychological Challenges of Childbirth – Nursing Reports, 15(1):8

(2024) Predictors of Pregnant Women's Decision to Opt for Cesarean Section in Romania – Cureus, 16(9)

(2024) Exploring Factors Influencing Pregnant Women’s Perceptions and Attitudes Towards Midwifery Care in Romania – Nursing Reports, 14(3), 1807-1818

(2024) COVID-19 and Flu Vaccination in Romania: Post-Pandemic Lessons – PLoS ONE, 19(3)

(2023) Similarities in Midwifery Education, Regulation, and Practice Across Europe – European Journal of Midwifery, 7(Supplement 1)

 

 

 

Hussein Alabdally | Computer Science | Best Researcher Award

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Mr. Hussein Alabdally | Computer Science | Best Researcher Award

Mr. Hussein Alabdally | University of Southern Queensland | Australia

Mr. Hussein Alabdally is a talented computer scientist, software engineer, and telecommunications specialist with diverse professional expertise spanning Australia and Iraq. With a foundation in mathematics, web development, and programming, he has contributed significantly to education, technology, and translation services. Hussein’s journey reflects his adaptability and passion for learning, from tutoring students in mathematics and English to working in IT, telecommunications, and software engineering roles. His bilingual communication skills in English and Arabic have enabled him to serve communities as an interpreter and translator, while his technical creativity continues to drive his work in coding, software design, and network systems.

Profiles

Scopus
Google Scholar

Education

Mr. Hussein’s educational path is marked by academic excellence in mathematics, computer science, and engineering studies. He earned his Bachelor of Science degree in Toowoomba, Australia, achieving outstanding results in advanced courses including operations research, numerical computing, experimental design, and web technologies. His solid foundation in mathematics and computing equipped him with analytical and problem-solving skills crucial for tackling real-world technical challenges. Alongside formal studies, he pursued professional training in web development and programming, mastering coding languages such as HTML, CSS, Python, JavaScript, and C++. Hussein also gained practical experience in website design and database management, complementing his academic knowledge with hands-on projects.

Experience

Mr. Hussein’s professional experience covers a wide range of roles across education, IT, translation, and engineering. He worked as a website developer with leading companies in Toowoomba, building digital platforms and enhancing user experience. His teaching journey as an English and mathematics tutor demonstrated his ability to simplify complex concepts for students, helping many succeed in academic pursuits. Hussein’s bilingual expertise was recognized in his work as an interpreter, supporting communication in medical, legal, and educational contexts. Transitioning into engineering roles, he contributed as an IT specialist at Dar Al-Auloom Private High School and later advanced to software engineering and telecommunications positions in Kirkuk. His diverse portfolio reflects both technical mastery and cultural adaptability.

Research Interests

Mr. Hussein’s research interests are deeply rooted in the intersection of mathematics, programming, and technology innovation. He is passionate about computational methods, web technologies, and advanced applications of mathematical modeling in computer engineering. His curiosity extends to artificial intelligence, game programming, and database systems, where he enjoys creating applications that merge creativity with technical precision. Hussein is particularly enthusiastic about designing intelligent software solutions, including document readers and chess games with AI capabilities. He also explores optimization techniques and performance computing, driven by a desire to apply theoretical knowledge to practical systems. His long-term vision is to bridge mathematics with next-generation software solutions.

Awards

Mr. Hussein’s achievements highlight his academic dedication and community engagement. He earned recognition in national and international competitions, including the Australian Statistics Competition, where he won the Queensland prize. He also secured credits in the UNSW ICAS Science and Mathematics contests, demonstrating excellence across STEM disciplines. At the University of Southern Queensland, he was actively involved in science and engineering challenges, achieving commendable rankings. Beyond academics, Hussein received awards for both academic excellence and school community participation, showcasing his commitment to leadership and service. These honors underline his consistent performance, strong analytical skills, and ability to contribute meaningfully both inside and outside the classroom.

Publication Top Notes

Empirical curvelet transform based deep DenseNet model to predict NDVI using RGB drone imagery data
Journal: Computers and Electronics in Agriculture, 
Authors: M. Diykh, M. Ali, M. Jamei, S. Abdulla, M.P. Uddin, A.A. Farooque, A.H. Labban, H. Alabdally, et al.

Improving Dry-Bulb Air Temperature Prediction Using a Hybrid Model Integrating Genetic Algorithms with a Fourier–Bessel Series Expansion-Based LSTM Model
Journal: Forecasting, 
Authors: H. Alabdally, M. Ali, M. Diykh, R.C. Deo, A.A. Aldhafeeri, S. Abdulla, et al.

ECT-DLM: Deep Learning Based Empirical Curvelet Transform Approach for Thoracic Disease Diagnosis from X-RAY Images
Conference: ICTIS
Authors: S. Abdulla, S.K. Alkhafaji, H. Marhoon, M. Diykh, M.A. Majed, J. Sadiq, H. Alabdally, et al.

Physical Human Activity Recognition Based on Spectral Graph Wavelet Transforms Integrated with Machine Learning Model
Conference: International Conference on Health Information Science,
Authors: S. Abdulla, A.S. Majeed, A.B. Al-Khafaji, W. Alsalman, M. Diykh, A. Sahi, H. Alabdally, et al.

Robust Approach for Human Activity Recognition Using Decomposing Technique Based Machine Learning Models
Conference: International Conference on Health Information Science,
Authors: S.Z. Hmoud, M. Diykh, S. Abdulla, H. Alabdally, A. Sahi

Conclusion

Mr. Hussein Alabdally represents a professional who blends education, technical skill, and cultural versatility. His journey reflects resilience, adaptability, and a deep passion for mathematics and technology. Whether teaching students, translating across languages, or designing digital systems, Hussein demonstrates excellence in every role he undertakes. His dual citizenship in Australia and Iraq positions him as a global professional with a multicultural perspective. With his diverse experience in tutoring, web development, software engineering, and telecommunications, Hussein continues to grow as a researcher and practitioner in the field of computer science. His career trajectory shows promise for future contributions to both academia and industry.

Dr. David Hua | Artificial Intelligence | Best Researcher Award

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Dr. David Hua | Artificial Intelligence | Best Researcher Award

Ball State University, United States.

Dr. David M. Hua is an Associate Professor at the Center for Information and Communication Sciences, Ball State University. With a rich academic background and over two decades of teaching, Dr. Hua has become a pivotal figure in the intersection of technology education, cybersecurity, and higher education. He is recognized for mentoring student-led innovation and his contribution to emerging tech curricula including offensive security, private cloud infrastructure, and sustainability in IT.

Profile

Scopus
Orcid

🎓 Education

Dr. Hua earned his Ed.D. in Higher Education in 2010 from Ball State University, where he also completed an MBA in Information Systems (2000) and a B.S. in Psychological Science (1991). This diverse academic foundation reflects his commitment to both technical expertise and educational leadership.

💼 Experience

Since July 20, 1998, Dr. Hua has served at Ball State University, advancing to the role of Associate Professor. He began as an Assistant Professor in 2000. His teaching spans undergraduate and graduate levels with courses ranging from cybersecurity and network configuration to cloud technologies. Beyond Ball State, his engagements with other institutions and organizations have broadened his interdisciplinary impact on both students and faculty.

🔬 Research Interests

Dr. Hua’s research interests lie at the crossroads of cybersecurity, AI in mental health surveillance, sustainable IT practices, and technology integration in higher education. He is especially passionate about leveraging machine learning to support mental health outcomes and empower student innovation through data-driven methodologies.

🏆 Awards & Mentorship

Dr. Hua has been an active mentor in various student projects, honors theses, and national competitions like the National Cyber League. He’s also served on several doctoral committees, contributing to dissertations in educational leadership and adult learning. His efforts have earned him recognition as a dedicated mentor, innovator, and academic leader.

📚 Publication

AI-Driven Mental Health Surveillance: Identifying Suicidal Ideation Through Machine Learning Techniques
📅 2025 | Big Data and Cognitive Computing
🧾 Cited by: 3 articles (as of early 2025)
👉 DOI: 10.3390/bdcc9010016

Mr. Hussm Rostum | Computer Science | Best Researcher Award

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Mr. Hussm Rostum | Computer Science | Best Researcher Award

Miskolc University, Institute of Automation and Info-communication, Hungary.

Hussam Rostum is a PhD candidate and researcher at the University of Miskolc in Hungary, specializing in computer vision for autonomous drone navigation. With a strong background in telecommunications and electronics, he blends academic excellence with hands-on experience as a part-time software engineer at FIEK. Hussam is known for developing cutting-edge solutions in industrial automation, biomedical imaging, and human–machine interfaces. Fluent in Arabic and English, he brings international insight into interdisciplinary research projects, merging software innovation with engineering systems.

Profile

Scopus
Orcid
Google Scholar

🎓 Education

Hussam holds a BSc and MSc in Telecommunication and Electronic Engineering, equipping him with deep theoretical and practical knowledge in signal processing, system design, and electronics. Currently, he is pursuing a PhD in Information Science at the University of Miskolc, focusing on AI-based vision systems for autonomous drone operations.

💼 Experience

Hussam serves as an Assistant Researcher and Part-time Software Engineer at FIEK, where he builds C# monitoring software, implements PLC-to-PC communications, and automates data workflows using Linux, Docker, and Excel. His professional journey includes work as a Full Stack Developer and Telecom Engineer, with experience in GUI development, DevOps collaboration, and .NET technologies.

🔬 Research Interests

📸 Computer Vision & Image Processing

🤖 Autonomous Systems & Drone Navigation

🩺 Biomedical Imaging & Oxygen Saturation Estimation

🔬 Optical System Design (Zemax)

⚙️ Industrial Automation & Data Visualization

🧠 Human–Machine Interfaces & Sensor Integration

📚 Selected Publications

Enhancing Machine Learning Techniques in VSLAM for Robust Autonomous Unmanned Aerial Vehicle Navigation
📅 2025-04-02 | 📰 Electronics
📌 Focus: Improving Visual SLAM with machine learning for UAVs in complex environments.
🔗 DOI: 10.3390/electronics14071440
👥 Co-author: József Vásárhelyi

Comparing the Effectiveness and Performance of Image Processing Algorithms in Face Recognition
📅 2024-05-22 | 📚 Conference Paper
📌 Focus: Evaluation of various image processing techniques for face recognition applications.
🔗 DOI: 10.1109/ICCC62069.2024.10569864
👥 Co-author: József Vásárhelyi

FPGA Implementation in Mobile Robot Applications: State of the Art Review
📅 2023-12-20 | 📰 Multidiszciplináris Tudományok
📌 Focus: Overview of FPGA-based systems in robotics.
🔗 DOI: 10.35925/j.multi.2023.2.21
👥 Co-authors: Omar M. Salih, Noha Hammami

An Overview of Energies Problems in Robotic Systems
📅 2023-12-14 | 📰 Energies
📌 Focus: Challenges in energy management for robotic systems.
🔗 DOI: 10.3390/en16248060
👥 Co-authors: József Vásárhelyi, Omar M. Salih, Rabab Benotsname

A Review of Using Visual Odometry Methods in Autonomous UAV Navigation in GPS-Denied Environments
📅 2023-12-01 | 📰 Acta Universitatis Sapientiae, Electrical and Mechanical Engineering
📌 Focus: Use of visual odometry for UAVs in GPS-denied settings.
🔗 DOI: 10.2478/auseme-2023-0002
👥 Co-author: József Vásárhelyi

 

 

 

 

Prof. Dr. Chih-Hsien Hsia | Image Processing | Best Researcher Award

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Prof. Dr. Chih-Hsien Hsia | Image Processing | Best Researcher Award

National Ilan University, Taiwan.

Chih-Hsien Hsia is a distinguished professor and researcher in computer science, specializing in DSP IC Design, Computer Vision, Image Processing, and Cognitive Engineering. He holds dual Ph.D. degrees in Engineering Science from National Cheng Kung University and Electrical & Computer Engineering from Tamkang University, Taiwan. Currently, he serves as a Distinguished Professor at National Ilan University and holds key positions in AI research, industry collaborations, and professional organizations. His contributions to AI, image processing, and intelligent systems have earned him prestigious awards and widespread recognition.

Profile

Scopus
Orcid
Google Scholar

🎓 Education

Prof. Dr. Chih-Hsien Hsia holds dual Ph.D. degrees in Engineering Science from National Cheng Kung University, Taiwan, and Electrical & Computer Engineering from Tamkang University, Taiwan. His expertise spans multiple engineering disciplines, with a strong focus on cutting-edge technological advancements and interdisciplinary research.

💼 Experience

Prof. Dr. Chih-Hsien Hsia is a Distinguished Professor at National Ilan University (2024 – Present) and serves as the Executive Director of the AI Promotion Office at the same institution. He is also the Director of the AIoX Research Center at National Ilan University (2024 – Present).

Beyond his role at NIU, he has been an Honorary Distinguished Professor at Chaoyang University of Technology since 2022 and a Board Member of the Chinese Society of Consumer Electronics since 2018. Additionally, he holds the position of Vice Chair of the IEEE Taipei Chapter Signal Processing Society (2024 – Present).

Previously, he served as a Professor at National Ilan University (2020 – 2024) and was the Chairperson of the Department of Computer Science at NIU from 2021 to 2024. His leadership and research contributions have significantly advanced AI, signal processing, and computer science education.

🔬 Research Interests

🖥 DSP IC Design

📷 Computer Vision & Image Processing

🧠 Cognitive Engineering

🏆 Awards & Honors

🥇 Taiwan International Science Fair (2025) – First Prize in Computer Science & Engineering

🏅 Best Paper Awards at IEEE Eurasia Conference on IoT, IET International Conference, National Defense Technology Academic Conference (2024)

🌟 World's Top 2% Scientists (2022)

🎖 Outstanding Young Scholar Award – Computer Society of the Republic of China (2018, 2020)

📚 Notable Publications

Finger Vein Recognition Based on Vision Transformer with Feature Decoupling for Online Payment Applications
IEEE Access, 2025 | DOI: 10.1109/ACCESS.2025.3552075
Contributors: Liang-Ying Ke, Yi-Chen Lin, Chih-Hsien Hsia

Artificial Intelligence and Machine Learning in Sensing and Image Processing
Sensors, 2025-03-18 | DOI: 10.3390/s25061870
Contributors: Jing Chen, Miaohui Wang, Chih-Hsien Hsia

An Edge-Cloud Collaborative Scalp Inspection System Based on Robust Representation Learning
IEEE Transactions on Consumer Electronics, 2024 | DOI: 10.1109/TCE.2024.3474911
Contributors: Sin-Ye Jhong, Guan-Ting Li, Chih-Hsien Hsia

Tucker Decomposition and Log-Gabor Feature-Based Quality Assessment for the Screen Content Videos
IEEE Transactions on Instrumentation and Measurement, 2024 | DOI: 10.1109/TIM.2024.3381267
Contributors: Hailiang Huang, Huanqiang Zeng, Jing Chen, Junhui Hou, Chih-Hsien Hsia, Kai-Kuang Ma

Width-Adaptive CNN: Fast CU Partition Prediction for VVC Screen Content Coding
IEEE Transactions on Multimedia, 2024 | DOI: 10.1109/TMM.2024.3410116
Contributors: Chao Jiao, Huanqiang Zeng, Jing Chen, Chih-Hsien Hsia, Tianlei Wang, Kai-Kuang Ma

 

 

 

Dr. Michela Longhi | Metamaterials | Best Researcher Award

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Dr. Michela Longhi | Metamaterials | Best Researcher Award

Niccolò Cusano University, Italy,

Michela Longhi is an Italian researcher and engineer specializing in electromagnetics, artificial materials, and wireless systems. She holds multiple positions, including Associate Editor of the Nonlinear Engineering - Modeling and Application Journal and Partner of LabChain. Throughout her career, she has gained extensive experience in R&D engineering, particularly in the fields of RF devices, antennas, and electromagnetic fields, contributing significantly to the design and optimization of high-performance materials and systems. She has a PhD in Electromagnetic Engineering from the University of Rome "Tor Vergata," and has held numerous positions in prestigious institutions such as ETH Zurich, Microwave Vision Group, and Niccolò Cusano University. 🌍

Profile

Orcid

Education 🎓

Michela Longhi earned her PhD in Electromagnetic Engineering (European Label) from the University of Rome "Tor Vergata", where she conducted research at the Pervasive Electromagnetics Lab between November 2015 and October 2018. During her doctoral studies, she focused on the design and prototyping of RF devices for short-range sensing, specifically in drone applications, with real-world implications for Smart City infrastructure, precision agriculture, and supply chains.

In addition to her PhD, Michela completed an International PhD at ETH Zurich, working with the Autonomous Systems Lab from November 2017 to May 2018. Here, she gained hands-on experience in the development of intelligent robotic systems capable of autonomous operation in complex and dynamic environments, which further enriched her research and broadened her expertise in electromagnetics and robotics.

Michela also holds a Master’s Degree in Electronic Engineering from the University of Rome "Tor Vergata", where she developed a strong foundation in electromagnetic materials, RF engineering, and wireless communications.

Experience 💼

Michela Longhi is an accomplished researcher and academic, currently serving as an Associate Editor for the Nonlinear Engineering - Modeling and Application Journal and a Partner at LabChain, focusing on blockchain and innovation. She is also a founding member of the URSI WIRS and a Commission Member for the MUR Public Concourse. Since 2021, Michela has held roles as a Post-Doctoral Researcher and Professor at Niccolò Cusano University, specializing in upper limb exoskeletons and electromagnetic materials. She has extensive experience in RF engineering and system design from her time at Microwave Vision Group (MVG) and CNR, where she worked on advanced EMC technologies and neuromodulation research.

Research Interests 🔬

Antenna Design and Telecommunications

Michela has made significant contributions to antenna design, particularly in the context of 5G communication, telecommunications, and aerospace. Her work in these areas has helped advance the development of high-performance antennas and EMC technologies for a variety of industries.

Smart City and Precision Agriculture

In recent years, Michela has focused on the development of upper-limb exoskeletons for medical and assistive purposes, as well as innovations in electromagnetic materials tailored for smart city infrastructure and precision agriculture. These advancements aim to improve urban living and agricultural practices by integrating cutting-edge RF technologies into everyday applications.

Exoskeleton Development

A key part of Michela's research is the development and optimization of upper-limb exoskeletons, which have promising applications in rehabilitation and assistive technologies. Her work seeks to enhance mobility and quality of life for individuals with physical impairments through advanced electromagnetic and robotic systems.

Awards 🏆

Founding Member, URSI WIRS (Women in Radio Science), (2023 - Present)

IEEE WIE Communication Team, IEEE Women in Engineering (2023 - Present)

MUR Commission Member, Ministero dell’Università e della Ricerca (2021-2022)

Publications Top Notes📚

Optimization Tools for the Design of Meta-Covers for Linear Antenna with Beam- and Null-Steering Capabilities
Published in: Applied Sciences, 2025-01-08

A Statistical Approach for Robust Metasurfaces and Metasurface-Based RIS Engineering
Published in: IEEE Transactions on Antennas and Propagation, 2024-06

Phase-Gradient Huygens’ Metasurface Coatings for Dynamic Beamforming in Linear Antennas
Published in: IEEE Transactions on Antennas and Propagation, 2023

Array Synthesis of Circular Huygens Metasurfaces for Antenna Beam-Shaping
Published in: IEEE Antennas and Wireless Propagation Letters, 2023-11

A Statistical Approach for Robust Metasurfaces and Metasurface-Based RIS Engineering
Preprint: 2023-10-12