Dr. Shuyi Zhao | Tunnel | Best Researcher Award

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Dr. Shuyi Zhao | Tunnel | Best Researcher Award

Dr. Shuyi Zhao | Master Student | China University of Mining and Technology | China

Zhao Shuyi is an emerging researcher in the field of Civil and Mining Engineering at the China University of Mining and Technology (Beijing), with a strong focus on rock mechanics, tunnel engineering, and anchorage system performance. Her research primarily explores the mechanical behavior, failure mechanisms, and reinforcement performance of rock and soil structures under complex geological and hydrochemical environments. She has made notable contributions to the study of infrared radiation evolution during rock failure, the dynamic response of anchorage systems with high-performance NPR bolts, and the development of resin-based anchoring materials designed for challenging hydrochemical conditions. Zhao’s scholarly work demonstrates a unique integration of laboratory experimentation and field application, emphasizing sustainable and resilient tunnel support systems. Her recent studies contribute to improving the safety, durability, and efficiency of underground engineering structures through innovative anchorage and excavation methods. She has published her findings in high-impact journals indexed in Scopus and Web of Science, including Engineering Failure Analysis, Materials, and Tunnelling and Underground Space Technology. Zhao’s research has been cited across multiple international sources, reflecting growing academic influence, with an h-index of 5 on Scopus and 6 on Google Scholar as of 2025. Her published works highlight collaborative research with prominent experts such as Jun Yang and Kexue Wang, further strengthening the scientific foundation of mining and civil engineering technologies.

Publication Profile

Scopus | ORCID

Featured Publications

Wang, K., Yang, J., Liu, Z., Bian, W., Wu, Y., & Zhao, S. (2025). Study on the infrared radiation evolution and early warning characteristics of failure in anchored specimens with different anchorage methods. Engineering Failure Analysis, 110065.

Bian, W., Dong, M., Wang, K., Sun, Z., Wang, Z., Zhao, S., & Yang, J. (2025). Performance evolution and formulation improvement of resin-based anchoring materials for hydrochemical environments. Materials, 18(20), 4741.

Wang, K., Yang, J., Bian, W., Wu, Y., Sun, Z., & Fang, Y. (2025). Dynamic behavior of anchorage systems reinforced with high-performance NPR bolts: Laboratory and field investigation. Construction and Building Materials, 142585.

Bian, W., Zhai, Z., Yang, J., Wang, K., Hao, Q., Sun, Z., & Sun, X. (2025). Resilient design of urban rock tunnels using prestressed support systems: Experimental study and field applications. Tunnelling and Underground Space Technology, 106591.

Bian, W., Yang, J., Zhu, C., Wang, K., & Xu, D. (2024). Application of excavation compensation method for enhancing stability and efficiency in shallow large-span rock tunnels. Journal of Central South University, 11771-024-5767-4.

Prof. Liying Sun | Control Theory Application | Best Researcher Award

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Prof. Liying Sun | Control Theory Application | Best Researcher Award

Prof. Liying Sun | Professor | Shanghai Dianji University | China

Dr. Liying Sun is a distinguished professor at Shanghai Dianji University with extensive expertise in control theory, particularly in nonlinear descriptor systems and Hamiltonian systems. Her research explores advanced mathematical and engineering control methodologies, including finite-time control, adaptive control, and stability analysis of nonlinear and singular Hamiltonian systems. She has made significant contributions to the theoretical development and practical implementation of robust control mechanisms that enhance system performance under uncertainty and external disturbances. Dr. Sun’s work is characterized by the integration of mathematical rigor with engineering applications, contributing to both theoretical advancements and real-world system optimization. Her research has been widely recognized and published in reputable international journals, reflecting her strong academic influence in the fields of automation, control science, and applied mathematics. According to Scopus, she has authored 66 documents, received 578 citations from 432 documents, and holds an h-index of 15, underscoring her impactful contributions to scientific research. Her publications are also well-cited on Google Scholar, confirming her broad recognition in the global academic community.

Publication Profile

Scopus

Featured Publications

  • He, S., Sun, L., & Yang, R. (2025). Finite-time H∞ control of doubly fed induction generator. Asian Journal of Control.

  • He, S., Sun, L., & Yang, R. (2025). Passive control of a set of nonlinear singular Hamiltonian systems. Journal of the Franklin Institute.

  • He, S., Sun, L., & Yang, R. (2025). Adaptive H∞ finite-time boundedness control for a set of nonlinear singular Hamiltonian systems. Control Theory and Technology.

  • Zhang, Z., Sun, L., & Yang, R. (2025). Input-output finite-time stabilization for a class of nonlinear descriptor Hamiltonian systems with actuator saturation. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering.

  • Zhang, Z., & Sun, L. (2025). Input-output finite-time adaptive control of nonlinear descriptor Hamiltonian systems. Fourth International Conference on Advanced Manufacturing.

 

Assoc. Prof. Dr. A’aeshah Alhakamy | Computer Graphics | Best Researcher Award

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Assoc. Prof. Dr. A’aeshah Alhakamy | Computer Graphics | Best Researcher Award

Assoc. Prof. Dr. A’aeshah Alhakamy | Associate Professor | University of Tabuk | Saudi Arabia

Assoc. Prof. Dr. A’aeshah Alhakamy is a distinguished academic and researcher in the field of Computer Science at the University of Tabuk, Saudi Arabia. Her research spans computer graphics, computer vision, visualization, and imaging, with a particular focus on illumination models in mixed and augmented reality (AR/MR), gesture-based interaction, and the convergence of vision and artificial intelligence in immersive environments. Her scholarly contributions bridge the gap between visual perception and computational intelligence, emphasizing human–data interaction, extended reality (XR) technologies, and AI-driven visual analytics. She has successfully supervised graduate research in emerging domains such as extended reality applications for industrial training and biometric authentication systems using AI. Dr. Alhakamy’s research outputs demonstrate a deep commitment to advancing both theoretical and applied dimensions of visual computing and human–computer interaction. Her academic excellence is reflected through strong research metrics, including Scopus with 254 citations from 235 documents and an h-index of 9, and Google Scholar with 417 citations, an h-index of 11, and an i10-index of 13. These indicators highlight her growing influence and recognition in the international research community.

Publication Profile

Scopus | ORCID | Google Scholar

Featured Publications

  • Alhakamy, A. (2025). Intersecting realms: Examining the convergence of vision and AI in extended reality graphics. IEEE Access, 1–1.

  • Alhakamy, A. (2024). Extended reality (XR) toward building immersive solutions: The key to unlocking Industry 4.0. ACM Computing Surveys, 56(9).

  • Alhakamy, A. (2023). Fathoming the Mandela effect: Deploying reinforcement learning to untangle the multiverse. Symmetry, 15(3).

  • Alatawi, H., Albalawi, N., Shahata, G., Aljohani, K., Alhakamy, A., & Tuceryan, M. (2023). Augmented reality-assisted deep reinforcement learning-based model towards industrial training and maintenance for NanoDrop spectrophotometer. Sensors, 23(13).

  • Albalawi, S., Alshahrani, L., Albalawi, N., Kilabi, R., & Alhakamy, A. (2022). A comprehensive overview on biometric authentication systems using artificial intelligence techniques. International Journal of Advanced Computer Science and Applications, 13(4).

 

Mr. Wang Pengfei | Propagation Mechanism | Excellence in Research Award

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Mr. Wang Pengfei | Propagation Mechanism | Excellence in Research Award

Mr. Wang Pengfei | Doctor | Panzhihua University | China

Dr. Pengfei Wang is a dedicated researcher and academic specializing in mechanical engineering, with a focus on the design, manufacturing, and service performance of high-precision ceramic bearings. His research primarily explores ultra-precision all-ceramic ball bearings, ceramic rolling bearing technologies, and the mechanical behaviors of silicon nitride ceramics under extreme temperature and stress conditions. Dr. Wang has actively contributed to several national research projects, including those funded by the National Natural Science Foundation of China and the National Key Research Program, emphasizing innovations in ultra-precision manufacturing and performance optimization of ceramic bearings. His studies combine theoretical modeling with experimental validation to advance understanding in fatigue failure mechanisms, crack propagation, and load-bearing capacity of ceramic bearings, significantly contributing to advancements in high-performance mechanical systems. Dr. Wang has published numerous peer-reviewed articles in prestigious international journals indexed by SCI and EI. According to Scopus, his research record includes 13 documents, 11 citations, and an h-index of 2, reflecting growing recognition in the academic community. His Google Scholar profile further demonstrates expanding scholarly impact through interdisciplinary collaborations.

Publication Profile

Scopus

Featured Publications

  • Wang, P., Li, S., Wu, Y., & Zhao, J. (2024). Research on calculation of allowable radial load of silicon nitride full ceramic ball bearing. Journal of Mechanical Science and Technology, 38(12), 6757–6767.

  • Wang, P., Li, S., Wu, Y., & Zhao, J. (2024). Initiation of secondary surface crack in the ring raceway of silicon nitride full ceramic bearing. Journal of Ceramic Processing Research, 25(4), 694–703.

  • Wang, P., Li, S., Wu, Y., Zhang, Y., Wei, C., & Wang, Y. (2024). Research on crack propagation mechanism of silicon nitride ceramic ball bearing channel surface based on rolling friction experiment. Applied Sciences, 14(2), 674.

  • Wang, P., Li, S., Wu, Y., Zhang, L., Wei, C., & Wang, Y. (2025). Research on propagation mechanism of silicon nitride full ceramic ball bearing ring raceway surface crack considering the initial inclination angle. Engineering Research – Forschung im Ingenieurwesen, 89(1), 73.

  • Wang, P., & Zhang, X. (2025). Experimental study on the service performance of full ceramic silicon nitride ball bearings. Lubricants.

 

Dr. Eleni Memi | Medicine | Best Researcher Award

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Dr. Eleni Memi | Medicine | Best Researcher Award

Dr. Eleni Memi | Clinician | National and Kapodistrian University of Athens | Greece

Dr. Eleni Memi is a distinguished medical scientist and endocrinologist from Greece whose research focuses on endocrinology, diabetes, metabolism, reproductive endocrinology, and thyroid gland pathophysiology. Her scientific contributions span both clinical and translational aspects of endocrine disorders, with special emphasis on hormonal regulation, metabolic diseases, glycosaminoglycans, and reproductive endocrinology in women. Dr. Memi has made substantial advancements in understanding the interplay between thyroid dysfunction, glucocorticoid activity, and reproductive health, integrating molecular mechanisms with clinical applications. Her work in endocrine-related metabolic disorders has contributed to novel insights into hormonal pathways and disease outcomes. She has authored several influential papers and a book chapter published by Elsevier. Her scholarly impact is reflected in Scopus with 72 citations, 12 documents, and an h-index of 5, while Google Scholar reports 129 citations, an h-index of 6, and an i10-index of 6, underscoring her growing academic influence in medical research.

Publication Profile

Scopus | ORCID | Google Scholar

Featured Publications

  1. Memi, E., Pavli, P., Maria, P., Vrachnis, N., & Mastorakos, G. (2024). Diagnostic and therapeutic use of oral micronized progesterone in endocrinology. Reviews in Endocrine and Metabolic Disorders.

  2. Alexandraki, K. I., Violetis, O., Memi, E., Fryssira, H., Papanikolaou, V., Papagianni, M., & Mastorakos, G. (2025). A rare combination of hypogonadotropic hypogonadism, GH deficiency and rectal atresia in a female with an FGFR1 variant: A case report and systematic review of the literature. Endocrine.

  3. Kanouta, F., Karampitsakos, T., Memi, E., Vrachnis, N., Macut, D., & Mastorakos, G. (2025). Epigenetic effects of endogenous and exogenous glucocorticosteroids during pregnancy on the offspring: A systematic-narrative review. Hormones (Athens).

  4. Pontikides, N., Karras, S., Kaprara, A., Anagnostis, P., Mintziori, G., Goulis, D. G., Memi, E., & Krassas, G. (2014). Genetic basis of familial isolated hyperparathyroidism: A case series and a narrative review of the literature. Journal of Bone and Mineral Metabolism.

  5. Memi, E., Karakiulakis, G., Goma, F., & Papakonstantinou, E. (2012). The functional role of glycosaminoglycans in the pathophysiology of the thyroid gland and their putative role as prognostic, diagnostic and therapeutic agents in thyroid pathologies. Review of Clinical Pharmacology and Pharmacokinetics.

Dr. Olubunmi Kayode Ayanwoye | Education | Best Researcher Award

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Dr. Olubunmi Kayode Ayanwoye | Education | Best Researcher Award

Dr. Olubunmi Kayode Ayanwoye | Lecturer | Map of Federal University Oye-Ekiti | Nigeria

Dr. Olubunmi Kayode Ayanwoye is an accomplished scholar in Mathematics Education, Curriculum Studies, and Pedagogical Innovation, recognized for his significant contributions to advancing teaching and learning practices in higher education. His research bridges mathematics pedagogy, educational technology, gender equity in STEM, and curriculum evaluation, focusing on developing data-driven instructional strategies that enhance learners’ achievement and engagement. A Life Member of the Mathematical Association of Nigeria (LMAN), Dr. Ayanwoye has established a strong academic presence through his publications, conference presentations, and peer-review engagements in both national and international scholarly outlets. His works emphasize the integration of ICT in mathematics education, the influence of teacher and learner variables on achievement, and the transformative role of emerging technologies such as virtual and extended reality in Education 4.0. He has authored and co-authored several peer-reviewed articles and book chapters, with notable citation metrics reflecting his scholarly influence — Google Scholar reports 21 citations, an h-index of 2, and an i10-index of 0, while Scopus indexing highlights his emerging academic visibility in educational technology and mathematics pedagogy. Dr. Ayanwoye continues to inspire pedagogical excellence, promote inclusive education, and advance empirical research in mathematics teaching and learning through collaborative and innovative inquiry.

Publication Profile

Google Scholar | ORCID

Featured Publications

  • Ayanwoye, O. K. (2023). Effects of teachers’ professional development on students’ academic achievement.

  • Ayanwoye, O. K. (2023). Implications of large class size on effective teaching and learning in Nigerian tertiary institutions: Lecturers’ perception.

  • Ayanwoye, O. K. (2021). Students’ learning styles as determinants of mathematical achievement in Oyo State.

  • Falebita, O. S., Kok, P. J., Ayanwoye, O. K., & Ogunjobi, A. O. (2025). Virtual reality in Education 4.0: Pre-service teachers’ technology readiness and behavioral intention.

  • Ayanwoye, O. K., Akinsola, M. K., & Oyeniran, J. O. (2024). Teacher personality traits as predictors of mathematics achievement among students in Oyo State, Nigeria.

 

Dr. Amir Ali Mokhtarzadeh | Nanomedicine | Best Academic Researcher Award

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Dr. Amir Ali Mokhtarzadeh | Nanomedicine | Best Academic Researcher Award

Dr. Amir Ali Mokhtarzadeh | Assistant Professor of Pharmaceutical Biotechnology | Tabriz University of Medical Sciences | Iran

Dr. Amir Ali Mokhtarzadeh is an accomplished Assistant Professor of Pharmaceutical Biotechnology renowned for his pioneering research in nanomedicine, cancer gene therapy, drug delivery systems, and biosensor development. His scientific pursuits center on the application of advanced nanomaterials for gene and drug delivery, with a special emphasis on microRNAs, siRNAs, and shRNAs in targeted cancer therapy, as well as innovative biosensing techniques for cancer biomarker detection. His interdisciplinary work bridges cellular and molecular biology, genetic engineering, and pharmaceutical biotechnology, contributing significantly to translational medical research. Dr. Mokhtarzadeh has published over 270 peer-reviewed articles, authored multiple book chapters, and co-edited several Persian scientific textbooks in biotechnology and molecular biology. His outstanding scholarly impact is evidenced by more than 12,574 citations and an h-index of 66 on Scopus, alongside 14,742 citations and an h-index of 72 on Google Scholar, establishing him among the world’s top two percentage of scientists as recognized by Stanford University. His research outputs are widely cited across fields such as materials science, molecular biology, and nanotechnology, underscoring his global influence in biomedical innovation and pharmaceutical applications.

Publication Profile

Scopus | ORCID | Google Scholar

Featured Publications

  1. Oroojalian, F., Beygi, M., Baradaran, B., Mokhtarzadeh, A., & Shahbazi, M. A. (2021). Immune cell membrane‐coated biomimetic nanoparticles for targeted cancer therapy. Small, 17(12), 2006484.

  2. Eivazzadeh-Keihan, R., Maleki, A., De La Guardia, M., Bani, M. S., Chenab, K. K., & Mokhtarzadeh, A. (2019). Carbon-based nanomaterials for tissue engineering of bone: Building new bone on small black scaffolds: A review. Journal of Advanced Research, 18, 185–201.

  3. Mokhtarzadeh, A., Eivazzadeh-Keihan, R., Pashazadeh, P., Hejazi, M., & Baradaran, B. (2017). Nanomaterial-based biosensors for detection of pathogenic virus. TrAC Trends in Analytical Chemistry, 97, 445–457.

  4. Yousefi, M., Dadashpour, M., Hejazi, M., Hasanzadeh, M., Behnam, B., & Mokhtarzadeh, A. (2017). Anti-bacterial activity of graphene oxide as a new weapon nanomaterial to combat multidrug-resistant bacteria. Materials Science and Engineering: C, 74, 568–581.

  5. Alamdari, S. G., Amini, M., Jalilzadeh, N., Baradaran, B., Mohammadzadeh, R., & Mokhtarzadeh, A. (2022). Recent advances in nanoparticle-based photothermal therapy for breast cancer. Journal of Controlled Release, 349, 269–303.

Dr. Jeonghoon Moon | Power Electronics | Best Researcher Award

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Dr. Jeonghoon Moon | Power Electronics | Best Researcher Award

Dr. Jeonghoon Moon | Visiting Professor in the Department of Electronic Engineer | Chosun University | South Korea

Jeonghoon Moon is a distinguished researcher in power electronics and AI-based control, with a focus on EMI-aware predictive control of DC–DC converters, sensor-level CPS security, and battery balancing strategies. His research integrates advanced machine learning techniques, including physics-informed LSTM models, with practical hardware implementations on DSP platforms for real-time disturbance prediction, ripple reduction, and system stability. He has made significant contributions to predictive and robust control, developing lightweight controllers that approximate LSTM outputs for deterministic execution on embedded systems, enabling faster detection latency and improved DC-rail performance. Moon has proposed novel safety envelopes unifying efficiency deviation with time- and frequency-domain ripple metrics to guide safe derating under dynamic operating conditions and potential spoofing scenarios. His work also encompasses EMI-aware PWM shaping and battery module balancing, validated through rigorous MATLAB/Simulink simulations and reproducible hardware experiments. Moon maintains multi-institutional collaborations with academic and industry partners to advance power electronics and AI integration. His research outputs include four SCI/SCIE journal publications, multiple consultancy projects, and one patent, reflecting both academic rigor and industrial relevance. His research impact is evidenced by 25 Scopus-indexed documents with 25 citations and an h-index of 2. Moon’s contributions extend to ultrasonic piezo resonance tracking and high-speed resonant frequency detection using AI-guided methodologies, demonstrating the applicability of machine learning in real-time control systems and intelligent energy management.

Publication Profile

Scopus | ORCID

Featured Publications

Moon, J.-H., Kim, J.-H., & Lee, J.-H. (2025). Sensor-Level Anomaly Detection in DC–DC Buck Converters with a Physics-Informed LSTM: DSP-Based Validation of Detection and a Simulation Study of CI-Guided Deception. Applied Sciences.

Moon, J., Lim, S., Kim, J., Kang, G., & Kim, B. (2024). A Study on the Mechanical Resonance Frequency of a Piezo Element: Analysis of Resonance Characteristics and Frequency Estimation Using a Long Short-Term Memory Model. Applied Sciences.

Moon, J., Park, S., & Lim, S. (2022). A Novel High-Speed Resonant Frequency Tracking Method Using Transient Characteristics in a Piezoelectric Transducer. Sensors.

Moon, J. H. (2021). A Study on Resonance Tracking Method of Ultrasonic Welding Machine Inverter. Journal of the Korean Society of Industry Convergence.

Moon, J. H. (2021). Fast and Stable Synchronization Between the Grid and Generator by Virtual Coordinates and Feed-Forward Compensation in Grid-Tied Uninterruptible Power Supply System. IEEE Access.

Prof. Dr. Cesar Hernando Valencia Niño | Evolutionary Computation | Best Researcher Award

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Prof. Dr. Cesar Hernando Valencia Niño | Evolutionary Computation | Best Researcher Award

Prof. Dr. Cesar Hernando Valencia Niño | Director of Master on Data Analytics and Intelligent Systems | Santo Tomas University Bucaramanga | Colombia

Cesar Hernando Valencia Niño is a distinguished researcher in artificial intelligence, robotics, mechatronics, and intelligent control systems. His work integrates machine learning algorithms with mechanical and electrical engineering to develop predictive, inferential, and adaptive systems applied to robotics, biomedical devices, industrial automation, and human–machine interaction. As leader of a Category A research group, he has contributed significantly to interdisciplinary applications of AI in areas such as prosthetics, echo state networks, autonomous systems, and biomedical forecasting. His portfolio includes contributions to the advancement of industrial robotics, machine design, neuroevolutionary computation, magnetorheological systems, and control architectures for UAVs and prosthetics. With active participation in 25 research and innovation projects, he has produced 17 peer-reviewed journal articles, 5 book chapters, 12 industrial prototypes, 7 documented innovations, and 5 patents. He is also a recognized reviewer of top-tier indexed journals and has directed theses across undergraduate to doctoral levels. Valencia Niño has presented his work in more than 30 knowledge dissemination events, demonstrating strong engagement in academic and scientific communities. His citation impact reflects growing international recognition: Scopus reports 45 citations from 44 documents with 17 indexed publications and an h-index of 4, while Google Scholar attributes 96 citations, an h-index of 6, and an i10-index of 2. His research continues to bridge artificial intelligence with engineering solutions for complex, real-world challenges, emphasizing innovation, automation, and intelligent system design.

Publication Profile

Scopus | ORCID | Google Scholar

Featured Publications

  • Valencia, C. H., Vellasco, M. M. B. R., & Figueiredo, K. (2023). Echo State Networks: Novel reservoir selection and hyperparameter optimization model for time series forecasting. Neurocomputing, 545, 126317.

  • Valencia Niño, C. H. (2011). Modelo de optimización en la gestión de inventarios mediante algoritmos genéticos. ITECKNE: Innovación e Investigación en Ingeniería, 8(2), 156–162.

  • Valencia, C. H., Vellasco, M. M. B. R., & Figueiredo, K. T. (2014). Trajectory tracking control using echo state networks for the CoroBot’s arm. In Robot Intelligence Technology and Applications 2.

  • Valencia, C. H., Vellasco, M., Tanscheit, R., & Figueiredo, K. T. (2015). Magnetorheological damper control in a leg prosthesis mechanical. In Robot Intelligence Technology and Applications 3.

  • Valencia Niño, C. H., & Dutra, M. S. (2010). Estado del arte de los vehículos autónomos sumergibles alimentados por energía solar. ITECKNE, 7(1), 46–53.

 

Mr. Cenyu Liu | Hybrid Architecture | Best Researcher Award

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Mr. Cenyu Liu | Hybrid Architecture | Best Researcher Award

Mr. Cenyu Liu | Master Student | Shanghai Jiaotong University | China

Academic Background

Cenyu Liu is a Master’s student at Shanghai Jiao Tong University, specializing in biomedical engineering and deep learning. His academic training encompasses advanced neural network design, signal processing, and wearable health technologies. Cenyu has focused on developing efficient deep learning models for automatic sleep stage classification from single-channel EEG signals. His work has been recognized in top journals and conferences, with citations across Google Scholar and Scopus, demonstrating the reach and influence of his research. He maintains an active researcher profile with indexed publications and a growing h-index, reflecting consistent contributions to biomedical AI and wearable device applications. Documentation of his research, including articles, patents, and profiles, is publicly accessible through ORCID and research profile links.

Research Focus

Cenyu Liu’s research centers on the intersection of artificial intelligence and healthcare technology. He develops compact hybrid deep learning models that enable accurate and efficient sleep stage classification for real-time monitoring using wearable devices. His work aims to bridge computational neuroscience and practical health applications, making AI solutions deployable on edge devices.

Work Experience

Cenyu has primarily conducted research in academic settings, collaborating with multidisciplinary teams at Shanghai Jiao Tong University. He has worked closely with experts in wearable sensor technology and biomedical signal processing, contributing to projects that integrate machine learning with portable health monitoring systems. His experience includes designing experiments, implementing deep learning pipelines, and validating models on benchmark datasets.

Key Contributions

Mr. Cenyu Liu has made significant contributions to AI-driven healthcare through the development of MultiScaleSleepNet, a hybrid CNN–BiLSTM–Transformer model that leverages multi-scale feature extraction and attention mechanisms for EEG-based sleep stage classification. His model demonstrates robustness across datasets and is optimized for computational efficiency, making it suitable for real-time applications on wearable devices. Additionally, he has contributed to mobile-based health monitoring patents and co-authored research on continuous core body temperature monitoring, enhancing the safety and efficiency of health-tracking systems.

Awards & Recognition

Cenyu Liu has been recognized for his research excellence and innovation in biomedical AI, particularly in wearable health technologies. His work has gained attention through peer-reviewed publications and citations in both Scopus and Google Scholar, reflecting its scientific impact. He has been invited to collaborate on high-profile projects that advance the practical application of AI in healthcare.

Professional Roles & Memberships

Mr. Cenyu is an active member of IEEE, participating in professional communities focused on artificial intelligence, biomedical engineering, and signal processing. He engages in collaborative research projects and maintains a profile of professional development through scholarly networks, contributing to the global scientific community.

Publication Profile

ORCID

Featured Publications

Liu, C., Guan, Q., Zhang, W., Sun, L., Wang, M., Dong, X., Xu, S. MultiScaleSleepNet: A Hybrid CNN–BiLSTM–Transformer Architecture with Multi-Scale Feature Representation for Single-Channel EEG Sleep Stage Classification. Sensors.

Zhang, W., Li, L., Wang, Y., Dong, X., Liu, C., Sun, L., Xu, S. Continuous Core Body Temperature Monitoring for Heatstroke Alert via a Wearable In-Ear Thermometer. ACS Sensors.

Impact Statement / Vision

Mr. Cenyu Liu envisions advancing artificial intelligence for personalized and portable healthcare. His research seeks to enable real-time, low-complexity AI models for wearable devices, empowering continuous health monitoring and improving preventive care through innovative computational solutions.