Yahya Alshamy | Social and Behavioral Statistics | Best Researcher Award

Published on by Statistics

Dr. Yahya Alshamy | Social and Behavioral Statistics | Best Researcher Award

New York University | United States

Dr. Yahya  Alshamy is a culturally attuned economist and policy analyst with extensive experience in higher education and research across Saudi Arabia and the United States. Currently a Post-Doctoral Fellow and Lecturer at New York University, he enhances NYU’s teaching portfolio in law, macroeconomics, and political economy by integrating cutting-edge research in behavioural and development economics into graduate instruction, mentoring teaching and research assistants, and leading independent studies such as “Legitimacy by Consumption,” which examines economic welfare and authority in transitioning rentier states. Concurrently, he serves as an Associate Research Fellow at the King Faisal Centre for Research and Islamic Studies (KFCRIS), where he oversees research, authors flagship reports, and positions KFCRIS as a thought leader through publications analyzing non-oil revenue growth, subsidy reform, and intellectual history, including cross-disciplinary works on Yemen and comparative studies of Western conservative critiques of intellectuals. Previously, as a Graduate Lecturer at George Mason University, Dr. Alshamy redesigned large macroeconomics survey courses, employing interactive problem sets, real-time polling, policy simulations, and discussion labs to boost student engagement and evaluations. His Ph.D. research at the Mercatus Centre examined institutional failures in conflict zones and the governance of defence technologies, resulting in nine peer-reviewed journal articles, multiple book chapters, and high-impact policy briefs, including pioneering frameworks for evaluating “noxious government markets” in international arms trade. Dr. Alshamy has also executed large-scale data analytics projects, including NLP pipelines tracking U.S. and EU investor sentiment on Saudi Vision 2030, and designed behavioral interventions that informed financial literacy programs for young Saudi investors. With over ten peer-reviewed and policy publications, certifications in human-subjects research and executive communication, and board appointments on research advisory and scientific boards, he exemplifies a blend of rigorous scholarship, innovative pedagogy, and policy-relevant impact in economics and governance.

Profiles: Google Scholar |  Linked In

Featured Publications

Alshamy, Y., Callais, J. T., & Ammons, J. (2024). Nonviolent regime change and economic freedom. SSRN, 4877262.

Alshamy, Y., Goodman, N. P., & Novak, M. (2025). Polycentric peace. Journal of Pacifism and Nonviolence, 1(aop), 1–29.

Alshamy, Y. (2025). Mind the cultural gap: Cultural contingency of behavioral interventions. SSRN, 5316905.

Alshamy, Y. (2024). Monocentric governance and the rise of sectarian conflict in Yemen. In Conflicts and challenges in the Middle East: Religious, political and …

Alshamy, Y. (2024). Essays on institutional analysis and development in war-torn countries. George Mason University.

Gang Yang | Statistical Genetics and Genomics | Best Researcher Award

Published on by Statistics

Prof. Gang Yang | Statistical Genetics and Genomics | Best Researcher Award

The First Hospital of Lanzhou University | China

Prof. Gang Yang is a distinguished Professor based in China, currently affiliated with The First Hospital of Lanzhou University, with a major research focus on cerebrovascular disease and glioma. Over his academic career, he has made sustained contributions to understanding molecular mechanisms and clinical implications in neurovascular and neuro-oncology fields. His representative works include: “HNF1A induces glioblastoma by upregulating EPS8 and activating PI3K/AKT signaling pathway” published in Biochemical Pharmacology, “EPS8 is a Potential Oncogene in Glioblastoma” in OncoTargets and Therapy, “Identifying the role of aging-related genes in intracranial aneurysms through bioinformatics analysis” in Chinese Neurosurgical Journal, “Revisiting sinking skin flap syndrome: a series of case reports and literature review on cranioplasty with PEEK implants” in Neurological Research, and “Ferroptosis in early brain injury after subarachnoid hemorrhage: review of literature” in Chinese Neurosurgical Journal. His body of work interweaves molecular biology, signaling pathways, bioinformatics, and translational neurosurgical topics, with a particular emphasis on how genes such as EPS8 drive glioblastoma progression and how neurovascular injury processes involve oxidative stress and ferroptotic pathways. He is also active in reporting clinical neurosurgical phenomena such as sinking skin flap syndrome and exploring genetic and aging mechanisms underlying aneurysm development, reflecting his dual interest in both basic and clinical neuroscience. Professor Yang’s academic record demonstrates a profound commitment to bridging laboratory findings with clinical applications, enhancing diagnosis, and therapeutic strategies for brain tumors and cerebrovascular conditions. He has authored 8 peer-reviewed publications, which have collectively received 63 citations, resulting in an h-index of 4. His expertise in molecular oncology, vascular neurosurgery, and bioinformatics establishes him as a leading figure in cerebrovascular and glioma research both nationally and internationally.

Profiles: Scopus 

Featured Publications

Kang, J., Xu, X., Tian, S., & Yang, G. (2025). Revisiting sinking skin flap syndrome: A series of case reports and literature review on cranioplasty with PEEK implants. Neurological Research, 47(2), 1–7.

Yongsheng Wang | Descriptive and Inferential Statistics | Excellence in Research Award

Published on by Statistics

Assoc Prof. Dr. Yongsheng Wang | Descriptive and Inferential Statistics | Excellence in Research Award

Taiyuan University of Technology | China

Assoc Prof. Dr. Yongsheng Wang is an Associate Professor in the College of Materials Science & Engineering at Taiyuan University of Technology, China. His research focuses on alloy materials and coating design, fabrication, and characterization, including high-entropy alloys, additive manufacturing, diamond coatings, and surface treatments. He obtained his Ph.D. from the University of Science & Technology Beijing and completed postdoctoral research at Beihang University, with a visiting scholar experience at Purdue University, United States. Dr. Wang has made significant contributions to the development of advanced alloy systems and surface engineering technologies. He has published over 60 peer-reviewed scientific papers in reputed international journals, authored several high-impact studies on metallic glass composites, Ti-based alloys, and high-entropy materials, and holds nine patents, including one granted in the United States. His work has received multiple financial supports from the National Natural Science Foundation of China, the China Postdoctoral Science Foundation, the Shanxi Provincial Natural Science Foundation, and the State Key Laboratory of Advanced Metal Materials. With an impressive h-index of 18, over 1,013 citations, and approximately 91 research documents, his research has established him as a leading expert in materials science. Dr. Wang’s technical expertise covers a wide range of experimental techniques such as scanning electron microscopy, X-ray diffraction, nanoindentation, and additive manufacturing, contributing to the understanding and optimization of mechanical properties, microstructures, and performance of next-generation alloy materials.

Profiles: Scopus | Orcid 

Featured Publications

Qi, J., Wu, Y., Zhang, C., Yu, S., Wang, Y., Liu, Y., & Hei, H. (2025). Ultraviolet photodetector of TiO₂ film in different phase on various substrates. Ceramics International.

Mu, Y., Liang, Y., Sheng, J., Zhang, C., Guo, Z., Yang, G., Sun, T., Wang, Y., & Lin, J. (2025). A novel approach to coating for improving the comprehensive high-temperature service performance of TiAl alloys. Journal name, volume(issue), page range.

Sun, D., Wang, H., Wang, Y., Guo, Y., Liang, Y., & Lin, J. (2025). Microstructural evolution and densification behavior of high-Nb TiAl produced by powder forging.

Sun, D., Wang, H., Wang, Y., Guo, Y., Liang, Y., & Lin, J. (2025). Low-temperature deposition of CVD diamond films on HfNbTaMo medium entropy alloy: Morphology, process and wear properties. Surface and Coatings Technology, 509, 130887.

Wang, Y., Hou, M., Huang, Z., Xu, Y., Tan, C., & Xiao, H. (2025). Effect of heat treatment on microstructure and mechanical properties of a new alpha-titanium alloy Ti-6.0Al-3.0Zr-0.5Sn-1.0Mo-1.5Nb-1.0V. Journal of Materials Engineering and Performance, 34, 12348–12358.

Mohammad Imrul Islam | Geospatial and Spatial Statistics | Best Researcher Award

Published on by Statistics

Mr. Mohammad Imrul Islam | Geospatial and Spatial Statistics | Best Researcher Award

Bangladesh Space Research and Remote Sensing Organization (SPARRSO) | Bangladesh

Mr. Mohammad Imrul Islam is a highly dedicated Remote Sensing Researcher and Senior Scientific Officer (SSO) at the Bangladesh Space Research and Remote Sensing Organization (SPARRSO), where he has been contributing his expertise since 2015. With over a decade of professional experience in Remote Sensing (RS) and Geographic Information System (GIS), his work focuses on environmental monitoring, agriculture, forestry, and water resource management, making him one of the promising scientific minds in Bangladesh’s earth observation community. He holds a Master of Engineering in Remote Sensing and GIS from Beihang University, Beijing, China (GPA 3.76), along with both Master of Science and Bachelor of Science degrees in Geography and Environment from Jahangirnagar University, Bangladesh, with first-class distinction. At SPARRSO, he has successfully led and contributed to several national and institutional projects such as flash flood monitoring in Tanguar Haor, spatio-temporal analysis of fisheries habitats, water quality assessment for inland fisheries, and GIS-based marine fishing zone identification. His research showcases his ability to integrate satellite data with advanced geospatial analytics for sustainable environmental management and disaster resilience. His postgraduate research and pilot studies explored innovative approaches such as retrieving Leaf Area Index (LAI) and analyzing the relationship between Solar-Induced Chlorophyll Fluorescence (SIF) and Gross Primary Production (GPP), reflecting his strong foundation in combining remote sensing models with ecological parameters for vegetation monitoring. Mr. Islam has participated in numerous international training and capacity-building programs organized by ISRO, APSCO, NESAC, Hokkaido University, and the University of Twente (ITC, Netherlands), enhancing his global scientific exposure. His technical expertise covers major geospatial and analytical software including ArcGIS, QGIS, ERDAS Imagine, ENVI, SNAP, and cloud-based tools such as Google Earth Engine, complemented by programming proficiency in Python, R, and MATLAB. Fluent in both English and Bangla, and with a TOEIC score of 805, he demonstrates strong communication and collaboration skills across international platforms. Through his ongoing research on seasonality mapping of surface water and hydrometeorological flood monitoring, he continues to contribute toward global climate resilience and sustainable resource management. Actively engaged on ResearchGate, LinkedIn, and ORCID, Mohammad Imrul Islam inspires emerging geospatial researchers across South Asia. His academic rigor, technical competence, and impactful research contributions make him an exemplary candidate for the Best Researcher Award, recognizing his significant role in advancing earth observation and remote sensing research at both national and international levels.

Profiles: Google Scholar | Orcid | Linked In

Featured Publications

Islam, M. I., Rahman, M. M., & Islam, M. Z. (2025). Comparative analysis of chlorophyll-a retrieval algorithms for inland waterbodies of Bangladesh using Sentinel-2 and Landsat-8 imagery. Discover Geoscience.

Niloy, N. M., Habib, S. M. A., Islam, M. I., Haque, M. M., Shammi, M., & Tareq, S. M. (2023). Distribution, characteristics and fate of fluorescent dissolved organic matter (FDOM) in the Bay of Bengal. Marine Pollution Bulletin.

Islam, M. I., Habib, S. M. A., Haque, S. A. U., Sultana, N., Faisal, B. M. R., Rahman, H., & Sharifee, M. N. H. (2020). Applicability of OCO-2 solar induced chlorophyll fluorescence (SIF) data for the estimation of photosynthetic activity in Bangladesh. Journal of Engineering Science, 11(2), 1–9.

Faisal, B. M. R., Rahman, H., Sharifee, N. H., Sultana, N., Islam, M. I., Habib, S. M. A., & Ahammad, T. (2020). Integrated application of remote sensing and GIS in crop information system: A case study on Aman rice production forecasting using MODIS-NDVI in Bangladesh. AgriEngineering, 2(2), 243–257.

Rahman, M. M., Pramanik, M. A. T., Islam, M. I., & Razia, S. (2019). Mapping mangrove forest change in Nijhum Dwip Island. Journal of Environmental Science and Natural Resources, 11(1–2), 25–32.

Xin Chen | Statistical Applications in Engineering | Best Researcher Award

Published on by Statistics

Dr. Xin Chen | Statistical Applications in Engineering | Best Researcher Award

Hainan University | China

Dr. Xin Chen is a distinguished petroleum engineering researcher currently serving as an Associate Researcher at the School of Marine Science and Engineering, State Key Laboratory of Marine Resource Utilization in the South China Sea, Hainan University. He obtained his Bachelor’s and Master’s degrees in Petroleum and Drilling Engineering from the China University of Petroleum, East China, and earned his Doctor of Philosophy in Petroleum Engineering from the University of Alberta. His research integrates theoretical modeling and experimental analysis to address complex challenges in gas hydrate systems, marine carbon sequestration, multiphase flow thermodynamics, enhanced oil recovery, polymer modification, and well cementing technologies. Dr. Chen has contributed significantly to advancing hydrate equilibrium calculations, cement slurry stability, and hydrocarbon phase behavior modeling. His prolific academic output includes numerous publications in top-tier journals such as Chemical Engineering Science, Fluid Phase Equilibria, Construction and Building Materials, SPE Journal, Energy, and Journal of Physical Chemistry C. In addition to his journal papers, he is a co-inventor on multiple international and national patents focusing on high-temperature and low-temperature well cementing systems, thermal-thickening stabilizers, and self-generating nitrogen foamed cement technologies. Dr. Chen has actively participated in several major research projects related to CO₂ sequestration in marine sediments, advanced reservoir fluid modeling, and wellbore cementing performance optimization, collaborating with both academic and industrial partners. He also serves as a peer reviewer for leading journals including Fuel, Engineering, Petroleum Science, and Construction and Building Materials, demonstrating his commitment to maintaining high standards in scientific publishing. According to Scopus, Dr. Xin Chen’s academic profile reflects a robust research impact with an h-index of 14, 26 documents, and more than 488 citations, signifying his growing global recognition in petroleum and energy engineering research.

Profiles: Scopus | Orcid

Featured Publications

Yang, H., Li, H., Xu, H., Wang, R., Zhang, Y., Xing, L., Chen, X., Peng, L., Kang, W., & Sarsenbekuly, B. (2026). Enhanced CO2 foam stabilization with fluorescent nano polymer microspheres for improved oil recovery: Insights from microscopic and macroscopic displacement studies. Geoenergy Science and Engineering.

Jiang, H., Yang, H., Ning, C., Peng, L., Zhang, S., Chen, X., Shi, H., Wang, R., Sarsenbekuly, B., & Kang, W. (2025). Amphiphilic polymer with ultra-high salt resistance and emulsification for enhanced oil recovery in heavy oil cold recovery production. Geoenergy Science and Engineering.

Yufeng Jiang | Statistical Applications in Engineering | Best Researcher Award

Published on by Statistics

Assoc Prof. Dr. Yufeng Jiang | Statistical Applications in Engineering | Best Researcher Award

Ocean University of China | China

Assoc Prof. Dr. Yufeng Jiang is an Associate Professor at the Ocean University of China, specializing in the health monitoring and safety assessment of offshore and marine engineering structures. With a strong academic foundation from the Ocean University of China, he has dedicated his career to advancing intelligent damage diagnosis methods that can directly utilize incomplete information while maintaining high noise robustness. He innovatively developed an iterative two-stage damage identification methodology capable of simultaneously locating structural damage and assessing its severity. Dr. Jiang has designed a hardware network of fiber optic sensors for condition monitoring of deepwater pressure-resistant subsea structures and created an intelligent structural health monitoring and early warning system, which has been successfully applied in a 500-meter deep-sea mixed-transport system demonstration project. His research has led to 20 Documents , 10 patents, and collaboration on three major research projects, resulting in a citation count of 111 and an h-index of 6, reflecting the significant impact of his work. Additionally, he has contributed to two consultancy projects and maintained collaborations across multiple institutions, consistently translating innovative research into practical engineering applications. Dr. Jiang continues to advance the field of marine structural safety with a focus on applied intelligence and robust monitoring solutions.

Profiles: Scopus  | Orcid

Featured Publications

Liu, Y., Wang, S., Jiang, Y., & Du, J. (2025). A spatial deformation reconstruction method of deep-sea mining riser from sparse inclination measurements. Ocean Engineering.

Wang, C., Luo, D., Guo, Y., Zheng, Z., Jiang, Y., & Du, J. (2025). A novel stochastic model updating method for offshore platforms based on Kriging model with active learning. Ocean Engineering.

Jiang, Y., Ma, C., Wang, S., & Li, Y. (2024). A novel evolutionary algorithm for structural model updating with a hybrid initialization and multi-stage update strategy. Ocean Engineering.

Jiang, Y., Liu, Y., Wang, S., & Rakicevic, Z. (2024). Structural damage classification in offshore structures under environmental variations and measured noises using linear discrimination analysis. Structural Control and Health Monitoring.

Liu, Y., Jiang, Y., Zhao, H., Wang, S., & Han, J. (2023). Experimental investigation on vortex-induced vibration characteristics of a segmented free-hanging flexible riser. Ocean Engineering.

Shujie Chang | Environmental and Climate Statistics | Best Researcher Award

Published on by Statistics

Assoc Prof. Dr. Shujie Chang | Environmental and Climate Statistics | Best Researcher Award

Guangdong Ocean University | China

Assoc Prof. Dr. Shujie Chang is an accomplished Associate Professor and supervisor of master’s students at the College of Ocean and Meteorology, Guangdong Ocean University, China, with extensive experience in atmospheric and climate sciences. His research focuses on understanding the complex interactions between the stratosphere and troposphere, with particular emphasis on gravity wave processes, ENSO dynamics, high-latitude and tropical teleconnections, and the factors influencing stratospheric ozone over the Tibetan Plateau. Dr. Chang has made significant contributions to modeling these interactions using advanced climate and weather simulation models, satellite observations, and data assimilation techniques. He has led multiple major research projects funded by national and provincial foundations, highlighting his leadership and expertise in the field. With over 20 peer-reviewed publications, his research has garnered notable attention, reflected in an h-index of 6 and approximately 85 citations, demonstrating both the impact and relevance of his work. In addition to his research achievements, he has served as a reviewer for numerous scientific journals and as a Guest Editor for the journal Atmosphere. Dr. Chang is also recognized for his dedication to teaching, having received multiple awards for excellence in instruction, and his contributions have been further acknowledged through prestigious honors such as the Guangdong Province Outstanding Young Meteorological Science and Technology Award.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Tushar Bhoite | Bayesian Networks and Decision Theory | Best Researcher Award

Published on by Statistics

Dr. Tushar Bhoite | Bayesian Networks and Decision Theory | Best Researcher Award

Dr. Tushar Bhoite | MES’s Wadia College of Engineering | India

Dr. Tushar Devidas Bhoite, Ph.D. in Mechanical Technology, M.E. in Machine Design, with over sixteen years of professional experience (including twelve in the automobile industry and four in academics), is a leading researcher and practitioner in integrating advanced IT technologies in auto-component manufacturing. His research interests encompass Industry 4.0, Industrial Internet of Things (IIoT), Digital Twin systems, Generative AI, predictive maintenance, neural and Bayesian networks, real-time monitoring, optimization and efficiency improvements in production environments. To date, he has authored 6 international journal papers and 3 international conference papers, co-authored 2 textbooks, and filed 2 patents, contributing to both theoretical and applied advancements. His master’s project, awarded from RGSTC Mumbai, stands as a landmark in his research portfolio, he has an h-index of 1 and over 1 citations as per his Scopus profile, reflecting strong scholarly impact. In his industrial roles, Dr. Bhoite has successfully led IOT implementations in assembly and press shops, improved Overall Equipment Effectiveness, standardized work systems, deployed TPM and Kaizen methodologies, and developed innovative solutions such as a wet-waste treatment machine. He currently serves as Assistant Professor in Automation & Robotics Engineering at MES’s Wadia College of Engineering, Pune, and continues consulting in production efficiency, resource optimization, and technology integration in manufacturing enterprises.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Bhoite, T. D., Pawar, P. M., & Gaikwad, B. D. FEA based study of effect of radial variation of outer link in a typical roller chain link assembly. International Journal of Mechanical and Industrial Engineering, 1, 65–70.

Bhoite, T. D., & Buktar, R. B. (2025). Productivity enhancement in Indian auto component manufacturing supply chain with IoT using neural networks. Production, 35, e20240047.

Bhoite, T. D., Buktar, R. B., Mahalle, P. N., Khond, M. P., Pise, G. S., & More, Y. Y. (2025). Productivity enhancement in the Indian auto component manufacturing supply chain through IoT, digital twins with generative AI, and stacked encoder-enhanced neural networks. Operations Research Forum, 6(4), 143.

Bhoite, D. T., & Buktar, R. (2025). An investigation into revolutionizing auto component manufacturing: An IoT-based approach for improved productivity and waste elimination. Journal of Information Systems Engineering and Management, 10(9s), 409–429.

Bhoite, D. T., Buktar, R., & Kannukkadan, G. (2024). Leveraging IoT in auto component manufacturing to monitor surface roughness and tool temperature. Journal of Electrical Systems, 20(2s), 563–574.*

Fazal Haq | Mathematical Statistics | Best Researcher Award

Published on by Statistics

Dr. Fazal Haq | Mathematical Statistics | Best Researcher Award

Dr. Fazal Haq | Karakoram International University | Pakistan

Dr. Fazal Haq is a highly accomplished academician and researcher, serving as a permanent faculty member in the Department of Mathematical Sciences at Karakoram International University (KIU), Gilgit-Baltistan, Pakistan. He earned his M.Sc. and Ph.D. in Applied Mathematics from KIU, and an M.Phil. from Sindh University, Jamshoro, consistently demonstrating exceptional academic performance, including securing the first position in his M.Sc. examinations and receiving both a Gold Medal and an Academic Excellence Award from KIU. Dr. Haq’s research spans a wide range of topics, including fluid mechanics, non-Newtonian fluids, magnetohydrodynamics, entropy generation, bioconvection, and nanofluid dynamics, with a particular focus on mathematical modeling, theoretical analysis, and computational simulations of complex fluid flows. Over the years, he has published more than 51 high-impact, peer-reviewed articles in internationally recognized journals, contributing significantly to advancing applied and computational mathematics. His work has garnered considerable attention from the scientific community, reflected in his h-index of 13 and a 616 of citations, underscoring the relevance and influence of his research. Dr. Haq is also a dedicated educator and mentor, inspiring students through his innovative teaching methods and fostering a research-oriented environment. His sustained commitment to scientific excellence and knowledge dissemination continues to make a meaningful impact both nationally and internationally.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Haq, F., Saleem, M., & Rahman, M. U. (2025). Optimization of entropy in bioconvective and reactive micropolar nanofluid flow with Arrhenius kinetics. CFD Simulation.

Saleem, M., Haq, F., Ghazwani, H. A., Ghazwani, M. H., & Alnujaie, A. (2025). Mathematical modeling and theoretical investigation of entropy generation in bioconvective micropolar hybrid nanofluid flow with activation energy and Lorentz force. ZAMM – Journal of Applied Mathematics and Mechanics, 105(10).

Khouqeer, G. A., Haq, F., Rahman, M. U., & Sallah, M. (2025). An investigation of thermo-bioconvective ternary hybrid nanofluid flow over rotating disk subject to activation energy. Journal of Thermal Analysis and Calorimetry.

Haq, F., Saleem, M., Ghazwani, H. A., Ghazwani, M. H., & Alnujaie, A. (2025). Dynamics of radiated and stratified natural bioconvective flow of cross hybrid nanomaterial with Darcy–Forchheimer and Lorentz force. ZAMM – Journal of Applied Mathematics and Mechanics, 105(9).

Saleem, M., Khouqeer, G. A., Haq, F., AbdelAll, N., Hussain, A., & Sallah, M. (2025). Implications of thermal stratification and radiative heat flux in blood-based ternary and dihybrid nanomaterial flow through a stretchable cylinder. Case Studies in Thermal Engineering, 42,

Ching Chih Tsai | Fuzzy Statistics and Uncertainty Modelling | Best Researcher Award

Published on by Statistics

Prof. Ching Chih Tsai | Fuzzy Statistics and Uncertainty Modelling | Best Researcher Award

Prof. Ching Chih Tsai |  National Chung Hsing University | Taiwan

Prof. Ching Chih Tsai is a distinguished academic in electrical engineering and control systems, currently serving as a Life Distinguished Professor at the Department of Electrical Engineering, National Chung Hsing University (NCHU), Taiwan. He earned his Ph.D. from Northwestern University in 1991. Dr. Tsai has held significant leadership roles, including serving as the President of the Chinese Automatic Control Society (CACS), the Robotics Society of Taiwan (RST), and the International Fuzzy Systems Association (IFSA). He has also been a Board of Governors member of IEEE Systems, Man, and Cybernetics Society (SMCS) and is currently the Dean of the College of Electrical Engineering and Computer Science at NCHU. An IEEE Fellow, his research focuses on intelligent control systems, mobile robotics, and automation intelligence. Dr. Tsai has published over 700 technical articles, with more than 20 in the International Journal of Fuzzy Systems since 2005. His recent work includes a 2025 paper on intelligent adaptive formation control for multi-quadrotors, introducing a hybrid controller combining Output Recurrent Fuzzy Broad Learning Systems (ORFBLS), reinforcement learning, and adaptive backstepping sliding mode control. According to Scopus, he has an h-index of 29, with 3,902 citations from 272 documents.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Rospawan, A., Tsai, C.-C., & Hung, C.-C. (2025). Two-layer intelligent learning control using output recurrent fuzzy neural long short-term memory broad learning system with RMSprop. IEEE Access.

Tsai, C.-C., Hung, C.-C., Mao, C.-F., Wu, H.-S., & Chen, C.-H. (2025). Fuzzy neural LSTM-RBLS for fractional-order PID sliding-mode motion control of autonomous mobile robots with four ISID wheels. International Journal of Fuzzy Systems.

Tsai, C.-C., Mao, C.-F., & Hussain, K. (2025). Intelligent adaptive formation control using ORFBLS and reinforcement learning for uncertain tilting multi-quadrotors. International Journal of Fuzzy Systems. =

Rospawan, A., Tsai, C.-C., & Hung, C.-C. (2025). Intelligent MIMO ORFBLS-based setpoint tracking control with its application to temperature control of an industrial extrusion barrel. International Journal of Fuzzy Systems.

Tsai, C.-C., Huang, H.-C., Chen, H.-Y., Hung, C.-C., & Chen, S.-T. (2024). Intelligent collision-free formation control of ball-riding robots using output recurrent broad learning in industrial cyber-physical systems. IEEE Transactions on Industrial Cyber-Physical Systems.