Vikas Mehta | Statistical Computing and Programming | Research Excellence Award

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Dr. Vikas Mehta | Statistical Computing and Programming | Research Excellence Award

Korean National Institute for International Education | South Korea

Dr. Vikas Mehta is a structural engineer and researcher specializing in seismic performance optimization, sustainable construction materials, and the application of advanced computational and machine learning methodologies to civil infrastructure systems. He completed his Ph.D. in Civil Engineering at Keimyung University, South Korea, where his award-winning doctoral research introduced innovative modifier-based and data-driven techniques for improving shear strength prediction and design accuracy in reinforced concrete beam-column joints. His expertise spans nonlinear finite element modeling, fragility analysis, physics-informed and graph-based machine learning, geospatial analytics, and performance-based seismic assessment, supported by strong proficiency in ETABS, OpenSees, SeismoSoft, Abaqus, MATLAB, Q-GIS, SPSS, Python, PyTorch, WEKA, and OriginPro. Dr. Mehta serves as a Postdoctoral Researcher at the Chonnam National University R&BD Foundation, contributing to advanced safety technologies for nuclear power plant structures under extreme hazard scenarios, including buckling resistance enhancement, retrofit optimization, and complex wind–terrain interaction studies. His professional background includes academic appointments in structural and construction engineering, where he taught subjects in earthquake engineering, finite element analysis, and structural systems while supervising graduate research and contributing to curriculum and laboratory development. Dr. Mehta has authored a substantial body of SCI-indexed research on seismic damage prediction, torsional behavior modeling, hybrid AI-mechanics frameworks, recycled and sustainable materials, computational methods, and structural performance evaluation, complemented by multiple patents in construction materials, damping devices, and waste-based composites. He has presented at leading international and national conferences and contributed to funded collaborative research, including projects involving global academic and industry partners. His professional affiliations include membership in ASCE, the Institute of Physics (AMInstP), IAEME (Fellow), and licensure as a Class-A engineer under the Himachal Pradesh Town and Country Planning Act. Dr. Mehta’s contributions to structural engineering and computational mechanics continue to gain international visibility, reflected in an h-index of 7, over 172 citations, and more than 19 published documents, underscoring his growing influence in machine learning–driven structural design, seismic resilience, and sustainable construction innovation.

Profiles: Scopus | Orcid

Featured Publications

Mehta, V., Jang, S. H., & Chey, M. H. (2025). Corrigendum to “Adaptive simulation and data-driven hybrid modeling for predicting shear strength and failure modes of interior reinforced concrete beam-column joints”.

Mehta, V., Jang, S. H., & Chey, M. H. (2025). Predictive framework for shear strength and failure modes of exterior reinforced concrete beam–column joints using machine learning. Structural Concrete. h.

Sagar, G. S., Mukthi, S., & Mehta, V. (2025). Analyzing compressive, flexural, and tensile strength of concrete incorporating used foundry sand: Experimental and machine learning insights. Archives of Computational Methods in Engineering.

Mehta, V., Thakur, M. S., & Chey, M. H. (2025). Enhancing seismic design accuracy of RC beam-column joints: Modifier-based approach for shear strength predictions. Structures.

Mehta, V., Jang, S. H., & Chey, M. H. (2025). Adaptive simulation and data-driven hybrid modeling for predicting shear strength and failure modes of interior reinforced concrete beam-column joints. Structures.

Michael Pitton | Descriptive and Inferential Statistics | Best Researcher Award

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Prof. Dr. Michael Pitton | Descriptive and Inferential Statistics | Best Researcher Award

Medical University of Mainz | Germany

Professor Dr. Michael Pitton is a distinguished German physician-scientist and expert in diagnostic and interventional radiology. A graduate of the Johannes Gutenberg University Mainz, he completed his medical studies and advanced clinical training in internal medicine, cardiology, radiology, and neuroradiology at leading German university hospitals, including the University Medical Center Mainz and the Deutsches Herzzentrum Berlin. His academic achievements include a habilitation on functional and morphological aspects of endovascular aneurysm therapy, followed by his appointment as university lecturer and senior consultant in interventional radiology. Professor Pitton has held successive leadership positions and currently serves as the Acting Director of the Department of Diagnostic and Interventional Radiology and Head of the Section of Interventional Radiology at the University Medical Center Mainz. He also holds European Board Certification in Interventional Radiology (EBIR) and the European Certification for Endovascular Specialists (CIRSE) and is a certified DEGIR instructor across all modules. Combining clinical excellence with managerial insight, he earned a Master of Health Business Administration, reflecting his engagement in healthcare management and innovation. Professor Pitton has an extensive scientific record, with approximately 127 publications, an h-index of around 33, and more than 6,771 citations, underscoring his influence in vascular and interventional radiology. His research contributions have advanced the understanding and treatment of aneurysms, transjugular intrahepatic portosystemic shunt (TIPS) interventions, and image-guided oncologic therapies. Recognized with numerous national and international awards, his work bridges academic medicine, translational research, and health leadership. Professor Pitton exemplifies excellence in clinical radiology, academic scholarship, and interdisciplinary collaboration, contributing significantly to the development of interventional radiology in Europe.

Profiles: Scopus | Orcid

Featured Publications

Graafen, D., Bart, W., Halfmann, M. C., Müller, L., Hobohm, L., Yang, Y., Neufang, A., Espinola-Klein, C., Pitton, M. B., Kloeckner, R., Varga-Szemes, A., & Emrich, T. (2022). In vitro and in vivo optimized reconstruction for low-keV virtual monoenergetic photon-counting detector CT angiography of lower legs.

Gairing, S. J., Kuchen, R., Müller, L., Cankaya, A., Weerts, J., Kapucu, A., Sachse, S., Zimpel, C., Stoehr, F., Pitton, M. B., Mittler, J., Straub, B. K., Marquardt, J. U., Schattenberg, J. M., Labenz, C., Kloeckner, R., Weinmann, A., Galle, P. R., Wörns, M. A., & Foerster, F. (2022.). 13C-Methacetin breath test predicts survival in patients with hepatocellular carcinoma undergoing transarterial chemoembolization.

Müller, L., Hahn, F., Mähringer-Kunz, A., Stoehr, F., Gairing, S. J., Foerster, F., Weinmann, A., Galle, P. R., Mittler, J., Pinto Dos Santos, D., Pitton, M. B., Düber, C., Fehrenbach, U., Auer, T. A., Gebauer, B., & Kloeckner, R. (2022). Prevalence and clinical significance of clinically evident portal hypertension in patients with hepatocellular carcinoma undergoing transarterial chemoembolization.

Yohanna Kusuma | Multivariate Statistical Analysis | Best Researcher Award

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Dr. Yohanna Kusuma | Multivariate Statistical Analysis | Best Researcher Award

The Royal Melbourne Hospital-The University of Melbourne | Australia

Dr. Yohanna Kusuma is an Australian-trained, internationally recognised neurologist and academic whose clinical and research work bridges acute stroke, neuroimaging, neurosonology, and movement disorders, with a strong translational focus across the Asia-Pacific region. She obtained her neurology specialist qualification from the University of Indonesia with honours, completed advanced fellowships in neurosonology and stroke at leading institutions in Singapore, and earned a PhD from Deakin University supported by an international scholarship, focusing on advanced CT-perfusion imaging in acute ischaemic stroke and the influence of ethnicity on imaging and clinical outcomes. She holds Fellowship of the Royal Australasian College of Physicians, qualifying her as a Consultant Neurologist in Australia. Dr Kusuma serves as Chief Investigator of the AI-powered SERENA platform for real-time stroke triage and decision support, leads the multinational APEX registry on acute ischaemic stroke with cancer spanning nine Asia–Pacific countries, and co-supervises PhD and honours students at Deakin University. She holds senior appointments in both Australia and Indonesia, including Senior Consultant Neurology at Metropolitan Medical Centre Hospital in Jakarta and Senior Research Fellow at The University of Melbourne. Her professional leadership includes representing Indonesia on the Asia Pacific Stroke Organisation and the Asian Stroke Advisory Panel, serving on the Education Council of the Australian Stroke Academy, and having previously served as a Co-opted Board Member of the World Stroke Organisation. Actively engaged in education and training, she has organised and delivered numerous neurosonology and stroke imaging workshops across the Asia-Pacific. Her research output is extensive, with an h-index of 4 and 144 citations, 13 peer-reviewed publications, book chapters, and international presentations. Dr Kusuma exemplifies a clinician-scientist who integrates cutting-edge imaging, neurosonology, and translational stroke research while advancing global collaborations in academic neurology, clinical innovation, and medical education.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Palidan Muhetaer | Statistical Computing and Programming | Best Researcher Award

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Assoc Prof. Dr. Palidan Muhetaer | Statistical Computing and Programming | Best Researcher Award

Xinjiang University of Finance & Economics | China

Profiles: Scopus 

Featured Publications

Fan, Y., Qian, Y., Gong, W., Chu, Z., Qin, Y., & Muhetaer, P. (2024). Multi-level interactive fusion network based on adversarial learning for fusion classification of hyperspectral and LiDAR data

Moumita Mukherjee | Machine Learning and Statistics | Best Researcher Award

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Dr. Moumita Mukherjee | Machine Learning and Statistics | Best Researcher Award

Charite-University Medicine Berlin | Germany

Dr. Moumita Mukherjee is an accomplished health economist and digital health researcher with expertise in health systems research, machine learning applications in healthcare, and interdisciplinary teaching. She holds a PhD in Economics from the University of Calcutta, an MBA in Entrepreneurship, Innovation and Project Development from International Telematic University, and an MSc in Data Science from the University of Europe for Applied Sciences, Germany. Her professional experience spans both academic and applied research environments, including positions at Charite-University Medicine Berlin, the Indian Institute of Public Health in Shillong, and the Berlin School of Business and Innovation. She has contributed extensively to global health research focusing on digital transformation, equity in healthcare access, and the use of data-driven methods for improving health outcomes. Her body of work includes numerous peer-reviewed publications in leading journals such as Scientific Reports, Journal of Health, Population and Nutrition, Journal of Health Management, and International Journal for Equity in Health, as well as book chapters and authored volumes addressing child health, nutrition, and health equity. In her current role at Charite-University Medicine Berlin, she lectures on digital health and artificial intelligence, supervises master’s theses, and mentors students. With advanced technical proficiency in Python, STATA, and NVivo, she applies econometric, machine learning, and deep learning models to address complex public health and policy questions. Her interdisciplinary approach integrates health economics, digital innovation, and policy analysis to support equitable and sustainable health systems worldwide. Through her research, teaching, and mentorship, Dr. Moumita Mukherjee continues to bridge data science and health economics to shape the future of evidence-based global health policy and digital healthcare transformation.

Profiles: Google Scholar | Orcid

Featured Publications

Tao Zhong | Machine Learning and Statistics | Best Researcher Award

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Dr. Tao Zhong | Machine Learning and Statistics | Best Researcher Award

Sun Yat-sen University | China

Dr. Zhong Tao is a dedicated interdisciplinary researcher specializing in environmental engineering, material science, and computational modelling. A native of Chongqing, China, he is a member of the Communist Party of China and currently based in Guangzhou. He earned his Bachelor’s degree in Environmental and Ecological Engineering with a minor in Computer Science and Technology from Sichuan Agricultural University, followed by a Master’s in Environmental Science and Engineering from Guangxi University under Prof. Yu Zebin, and is pursuing his Doctor of Engineering (Ph.D.) in Resources and Environment at Sun Yat-sen University under Prof. He Chun. His research focuses on the design and development of high-activity environmental functional materials for atmospheric and water pollutant removal, catalytic ozonation, and clean-energy catalysis, including hydrogen production via water splitting. He also employs Density Functional Theory (DFT) to analyze catalytic materials and pollutant molecular structures, building structure–property relationships to guide experiments. Dr. Zhong has contributed to 31 SCI-indexed papers, including 11 as first or co-first author, and applied for 5 patents, with 4 granted. His ongoing research includes national and provincial projects as principal investigator or key contributor. He has received multiple national and university-level scholarships and awards for academic excellence, innovation, and leadership. His Scopus metrics reflect a growing international influence, with an h-index of 10, 22 documents, and over 343 citations, underscoring his strong academic productivity. Known for his rigorous research approach, interdisciplinary collaboration, and mentoring of peers and students, Dr. Zhong also pursues interests in history, literature, and sports, maintaining an optimistic, resilient, and disciplined outlook that complements his scientific career.

Profiles: Scopus 

Featured Publications

Guo, X., Yao, Z., Long, X., Zeng, L., Wang, C., Fang, Z., Zhong, T., Tian, S., Shu, D., & He, C. (2025). Recent advances in tailored nanostructured ozonation catalysts for enhanced VOCs removal: Synergistic optimization of scale configuration and electronic microenvironment.

Zhong, T., Yao, Z., Zeng, L., Zhao, H., Long, X., Li, T., Tian, S., & He, C. (2025). Manipulating spin-configuration via electron reverse overflow to dynamically tune the adsorption behavior of sulfur-containing intermediates for enhanced sulfur resistance.

Aladji Abatchoua Madi Madi Ibram | Multivariate Statistical Analysis | Best Researcher Award

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Dr. Aladji Abatchoua Madi Madi Ibram | Multivariate Statistical Analysis | Best Researcher Award

University of Ebolowa | Cameroon

Dr. Aladji Abatchoua Madi Madi Ibram is a distinguished academic and researcher currently serving as the Head of the Department of Biological Sciences Applied to Agriculture at the University of Ebolowa, Cameroon. He holds a Ph.D. in Genetics and Plant Breeding, with a specialized focus on genetic variability, plant improvement, and sustainable agricultural development. As a lecturer, he teaches a wide range of subjects including Mendelian and Morganian genetics, quantitative traits genetics, and seed production. His research primarily emphasizes improving crop yield and nutritional quality in economically important plants, thereby contributing to both food security and human health. Dr. Aladji Abatchoua’s scientific contributions have been recognized across several reputed platforms such as Springer, BMC, Nature Portfolio, Scientific American, Palgrave Macmillan, and Adis. He has published over 14 research papers in internationally indexed journals, showcasing his dedication to advancing plant genetics and breeding. His collaborative research with the University of Ngaoundéré and the University of Yaoundé 1 has further enhanced the understanding of genotype–environment interactions, particularly in crops like sesame and peanut, to identify stable and high-yielding varieties suitable for diverse agro-ecological zones. Beyond his research endeavors, he actively contributes to the academic community as a reviewer for several international journals, including the Journal of Plant Sciences, International Journal of Genetics and Genomics, and Journal of Plant Studies, ensuring the maintenance of high-quality peer-reviewed publications. His commitment to scientific excellence has been acknowledged through multiple certificates of excellence in peer reviewing from reputable international journals such as BP International and the Journal of Experimental Agriculture International. Through his academic leadership, innovative research, and dedication to agricultural advancement, Dr. Aladji Abatchoua Madi Madi Ibram continues to play a pivotal role in fostering agricultural innovation and scientific integrity in Cameroon and beyond.

Profiles:  Orcid

Featured Publications

Aladji Abatchoua Madi Madi Ibram. (2025). Genetic analysis of common bean (Phaseolus vulgaris L.) for root traits, yield components and seed yield. Journal of Applied Genetics.

Guo Tian | Machine Learning and Statistics | Best Researcher Award

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Assoc Prof. Dr. Guo Tian | Machine Learning and Statistics | Best Researcher Award

Tsinghua University | China

Assoc Prof. Dr. Guo Tian is an accomplished young chemical engineer whose research lies at the frontier of sustainable catalysis and CO₂/CO conversion. He earned his Bachelor’s degree in Chemical Engineering under Prof. Xuezhi Duan at the East China University of Science and Technology and pursued his doctoral studies in Chemical Engineering at Tsinghua University under the guidance of Prof. Fei Wei. Following his doctoral training, he joined Southwest Jiaotong University as an Associate Professor and Principal Investigator. At only twenty-five years of age, Guo has led pioneering work on high-pressure thermo-catalytic systems, including the design of a reactor capable of stable operation at up to 60 bar integrated with surface-enhanced infrared absorption spectroscopy (SEIRAS) for in-situ monitoring of reaction intermediates. His studies have revealed critical mechanistic pathways in CO/CO₂ conversion using bifunctional catalysts, identifying oxygenate intermediates as key to improving the traditional methanol-to-hydrocarbons (MTH) mechanism. Drawing inspiration from biological systems, he has advanced the concept of bio-inspired multifunctional catalysts and introduced the innovative idea of “catalytic shunt” strategies to enhance selectivity and efficiency. Combining experimental research with density-functional theory (DFT) and micromodel simulations, his work bridges molecular-level understanding with reactor-scale engineering. Dr. Tian has authored numerous influential publications in high-impact journals such as Nature Sustainability, Nature Communications, ACS Catalysis, and the Journal of the American Chemical Society. Notable among these are “Efficient syngas conversion via catalytic shunt” (Nature Sustainability), and “Upgrading CO₂ to sustainable aromatics via perovskite-mediated tandem catalysis” (Nature Communications). According to his Scopus profile, he has authored 14 documents, accumulated around 297 citations, and holds an h-index of 9, reflecting a strong and growing impact in the field. His expertise includes thermochemical measurement and data analysis, catalytic materials design, reactor and reaction-system development, in-situ spectroscopy (SEM, XRD, XPS, XAS), and DFT-based theoretical modeling. Integrating theory, advanced characterization, and engineering innovation, Guo Tian’s vision focuses on transforming CO₂ and CO into high-value sustainable fuels such as aviation fuel components, contributing to global carbon-neutral energy goals. Through his scientific rigor, leadership, and creativity, he has rapidly emerged as a rising star in heterogeneous catalysis and sustainable chemical engineering.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

M. Zhao, Q. Wu, X. Chen, H. Xiong, G. Tian, L. Yan, F. Xiao, & F. Wei. (2025). Entropy-governed zeolite intergrowth. Journal of the American Chemical Society.

Z. Wang, X. Liu, G. Tian, Z. Wang, L. Li, F. Lu, Y. Yu, Z. Li, F. Wei, & C. Zhang. (2025). Research advances in coal-based syngas to aromatics technology. Clean Energy, 9(5), 136–152.

J. He, G. Tian, D. Liao, Z. Li, Y. Cui, F. Wei, C. Zeng, & C. Zhang. (2025). Mechanistic insights into methanol conversion and methanol-mediated tandem catalysis toward hydrocarbons. Journal of Energy Chemistry.

H. Xiong, Y. C. Wang, X. Liang, M. Zhao, G. Tian, G. Wang, L. Gu, & X. Chen. (2025). In situ quantitative imaging of nonuniformly distributed molecules in zeolites. Journal of the American Chemical Society, 147(32), 28965–28972.

Z. Li, J. Chen, G. Xu, Z. Tang, X. Liang, G. Tian, F. Lu, Y. Yu, Y. Wen, & J. Yang. (2025). Constructing three-dimensional covalent organic framework with aea topology and flattened spherical cages. Chemistry of Materials, 37(5), 1942–1948.

Kuruba Chandrakala | Machine Learning and Statistics | Best Researcher Award

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Dr. Kuruba Chandrakala | Machine Learning and Statistics | Best Researcher Award

Siddhartha Academy of Higher Education | India

Dr. Kuruba Chandrakala is an emerging researcher in the domains of computer vision, deep learning, and medical image processing, currently serving as Assistant Professor (Selection Grade) in the CSE department at Siddhartha Academy of Higher Education, Vijayawada. She earned her Ph.D. from NIT Tiruchirappalli, preceded by M.Tech in Computer Science and Engineering with distinction from JNTU Kakinada and B.Tech in the same discipline from JNTU Anantapur. She has qualified both NET and APSET examinations. Her professional trajectory includes roles as Head of Department (CSE-AIML) at Vignan’s Nirula Institute of Technology & Science for Women and previous teaching appointments at VNITSW and SITAM, along with industry experience as a System Engineer with Tata Consultancy Services. Her publication record comprises five Scopus indexed papers, four of which are in SCIE journals, two IEEE conference papers, and one book chapter; she also holds one patent. Her Scopus metrics include an h-index of 4, 10 documents, and 150 citations. Her research has addressed areas such as diabetic retinopathy segmentation, robust blood vessel detection, and image enhancement through deep learning architectures. She teaches courses including Deep Learning, Machine Learning, Big Data Analytics, Cloud Computing, and programming in C, C++, Java, and Python. She has earned numerous certifications from NPTEL, Coursera, Microsoft, IBM, and Wipro and received awards such as the NPTEL Discipline Star and Wipro Project Excellence Award. Her leadership and mentoring roles include serving as a mentor for Wipro TalentNext, nodal officer for Microsoft Upskilling and APSCHE virtual internship programs, and coordinator for various hackathons. She is a life member of professional bodies such as CSI, ISTE, IAENG, and IET, and has delivered several invited and guest lectures, contributing significantly to academic excellence and research advancement.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Chandrakala, K., & Gopalan, N. P. (2025). 3DECNN: A novel method for segmentation of diabetic retinopathy in retinal fundus images using 3D-edge CNN. Neural Computing and Applications.

Kuruba, C., Sharmila, S. K., Mounika, V., Aswini, D., & Poojitha, G. (2023). Three layered security model to prevent credit card fraud using LBPH and CNN-ResNet architecture. International Conference on Hybrid Intelligent Systems, 422–428.

Dharmaiah, K., Mebarek-Oudina, F., Sreenivasa Kumar, M., & Chandra Kala. (2023). Nuclear reactor application on Jeffrey fluid flow with Falkner-Skan factor, Brownian and thermophoresis, non-linear thermal radiation impacts past a wedge. Journal of the Indian Chemical Society, 100(2), 117.

Kuruba, C., & Gopalan, N. P. (2023). Robust blood vessel detection with image enhancement using relative intensity order transformation and deep learning. Biomedical Signal Processing and Control, 86, 105195.

Kuruba, C., Pushpalatha, N., Ramu, G., Suneetha, I., Kumar, M. R., & Harish, P. (2023). Data mining and deep learning-based hybrid health care application. Applied Nanoscience, 13(3), 2431–2437.

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

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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.