Charalampos Patrikakis | Data Science | Best Researcher Award

Prof. Dr. Charalampos Patrikakis | Data Science | Best Researcher Award

Director, Consert lab at University of West Attica Greece

Professor Charalampos Z. Patrikakis is a distinguished academic at the University of West Attica (UniWA), specializing in the design of interconnected electronic systems and data-driven services πŸ“‘πŸ’‘. As Director of the Computer Network Services Research Laboratory and Chair of UniWA’s Innovation and Start-up Entrepreneurship Committee πŸš€, he bridges advanced research with real-world impact. He leads the MSc Program in Artificial Intelligence and Deep Learning πŸ€– and co-founded the spinoff THINGENIOUS, emphasizing tech transfer and innovation. A Senior Member and Distinguished Contributor of IEEE 🌐, he serves as Editor-in-Chief of IEEE IT Professional Magazine and actively mentors through IEEE Student Branch and global committees πŸŽ“. His contributions span academia, policy, and innovation, positioning him as a thought leader in digital transformation, AI, and trustworthy systems πŸ”πŸ“Š.

Professional ProfileΒ 

πŸŽ“ Education

Professor Charalampos Z. Patrikakis holds a strong academic foundation in Electrical and Computer Engineering, having completed his undergraduate and graduate studies in Greece’s premier technical institutions πŸ›οΈ. His educational journey laid the groundwork for a deep engagement in networked systems, AI, and intelligent service design 🧠. Over the years, he has continued his intellectual development through participation in advanced research programs and postdoctoral initiatives, expanding his expertise into interdisciplinary domains. His commitment to lifelong learning is evident in his leadership of postgraduate programs and mentorship of early-career researchers πŸ“˜. This educational background not only supports his academic excellence but also empowers his contributions in innovation, policy, and industry-focused technological development 🎯.

πŸ’Ό Professional Experience

With an extensive career in higher education and applied research, Professor Patrikakis serves as a Professor at the University of West Attica and Director of the Computer Network Services Research Laboratory πŸ–₯️. He has previously led the Information Transmission-Processing and Networks Division and is currently Chair of UniWA’s Committee on Technology Transfer, Innovation, and Start-up Entrepreneurship πŸš€. His experience also spans advisory roles in national policy, having served the Greek Deputy Minister of Development on research matters (2006–2007) πŸ“‹. He is Editor-in-Chief of IEEE IT Professional Magazine and actively contributes to IEEE global leadership as a Senior Member and Distinguished Contributor 🌍. His professional roles demonstrate his unique ability to bridge academia, innovation, and policy for technological advancement πŸ”§πŸ“‘.

πŸ”¬ Research Interests

Professor Patrikakis’ research spans several cutting-edge fields including interconnected electronic systems, IoT architectures, data processing, and AI-driven service design πŸ€–πŸ“Ά. He is particularly interested in the trustworthiness of social networks, ethical AI, and the integration of deep learning algorithms into real-world applications 🌐. Through his leadership in the MSc Program in Artificial Intelligence and Deep Learning, he actively explores emerging topics in smart systems, adaptive learning, and secure network protocols πŸ”πŸ”. His interdisciplinary focus bridges computing, communication systems, and human-centric applications, with a strong orientation toward technological impact and innovation. By leading national and international collaborations, he contributes to shaping future-ready digital ecosystems aligned with sustainable and ethical digital transformation goals πŸŒ±πŸ“Š.

πŸ… Awards and Honors

Professor Patrikakis has received multiple honors recognizing his dedication to academia, innovation, and IEEE leadership πŸ†. As a Senior Member of IEEE, Distinguished Contributor, and Distinguished Visitor of the IEEE Computer Society, he has earned global recognition for technical leadership and community engagement 🌍. He has also been appointed Chair of several key IEEE committees, including the Special Interest Group on Trustworthiness in Social Networks. His role as Editor-in-Chief of IEEE IT Professional Magazine further emphasizes the trust and esteem placed in him by the international research community πŸ“. These accolades highlight not only his academic and technical prowess but also his ability to inspire and lead in both educational and professional domains πŸŽ–οΈ.

πŸ§ͺ Research Skills

Professor Patrikakis brings advanced research skills in system architecture design, data analytics, AI integration, and secure communications πŸ”πŸ“Š. His capabilities extend to managing large-scale research labs, supervising MSc and PhD students, and translating research into startups through successful commercialization strategies πŸš€. He is proficient in applying machine learning and deep learning models to practical challenges, fostering cross-disciplinary collaboration and innovation πŸ’»πŸ€. He excels in project planning, grant acquisition, and strategic R&D management, positioning him as a leader in both theoretical and applied research. His editorial work and IEEE leadership roles also reflect strong skills in scientific communication, peer review, and community building πŸ“šπŸŒŸ.

Publications Top Note πŸ“

  • Title: A complete farm management system based on animal identification using RFID technology
    Authors: A.S. Voulodimos, C.Z. Patrikakis, A.B. Sideridis, V.A. Ntafis, E.M. Xylouri
    Year: 2010
    Citations: 385
    Source: Computers and Electronics in Agriculture, 70(2), 380–388

  • Title: Distributed denial of service attacks
    Authors: C. Patrikakis, M. Masikos, O. Zouraraki
    Year: 2004
    Citations: 157
    Source: The Internet Protocol Journal, 7(4), 13–35

  • Title: A cooperative fog approach for effective workload balancing
    Authors: A. Kapsalis, P. Kasnesis, I.S. Venieris, D.I. Kaklamani, C.Z. Patrikakis
    Year: 2017
    Citations: 125
    Source: IEEE Cloud Computing, 4(2), 36–45

  • Title: PerceptionNet: A deep convolutional neural network for late sensor fusion
    Authors: P. Kasnesis, C.Z. Patrikakis, I.S. Venieris
    Year: 2019
    Citations: 48
    Source: Proceedings of the 2018 Intelligent Systems and Applications

  • Title: Cloud federation and the evolution of cloud computing
    Authors: D.G. Kogias, M.G. Xevgenis, C.Z. Patrikakis
    Year: 2016
    Citations: 37
    Source: Computer, 49(11), 96–99

  • Title: Deep learning empowered wearable-based behavior recognition for search and rescue dogs
    Authors: P. Kasnesis, V. Doulgerakis, D. Uzunidis, D.G. Kogias, S.I. Funcia, et al.
    Year: 2022
    Citations: 35
    Source: Sensors, 22(3), 993

  • Title: Application of blockchain technology in dynamic resource management of next generation networks
    Authors: M. Xevgenis, D.G. Kogias, P. Karkazis, H.C. Leligou, C. Patrikakis
    Year: 2020
    Citations: 33
    Source: Information, 11(12), 570

  • Title: Publish/subscribe over information centric networks: A Standardized approach in CONVERGENCE
    Authors: N.B. Melazzi, S. Salsano, A. Detti, G. Tropea, L. Chiariglione, A. Difino, et al.
    Year: 2012
    Citations: 32
    Source: Future Network & Mobile Summit

  • Title: Security and privacy in pervasive computing
    Authors: C. Patrikakis, P. Karamolegkos, A. Voulodimos, M.H. Abd Wahab, et al.
    Year: 2007
    Citations: 31
    Source: IEEE Pervasive Computing, 6(4), 73–75

  • Title: Cognitive friendship and goal management for the social IoT
    Authors: P. Kasnesis, C.Z. Patrikakis, D. Kogias, L. Toumanidis, I.S. Venieris
    Year: 2017
    Citations: 28
    Source: Computers & Electrical Engineering, 58, 412–428

  • Title: Toward a blockchain-enabled crowdsourcing platform
    Authors: D.G. Kogias, H.C. Leligou, M. Xevgenis, M. Polychronaki, E. Katsadouros, et al.
    Year: 2019
    Citations: 27
    Source: IT Professional, 21(5), 18–25

  • Title: On the benefits of deep convolutional neural networks on animal activity recognition
    Authors: E. Bocaj, D. Uzunidis, P. Kasnesis, C.Z. Patrikakis
    Year: 2020
    Citations: 24
    Source: International Conference on Smart Systems and Technologies, 83–88

  • Title: Autonomic communication
    Authors: A.V. Vasilakos, M. Parashar, S. Karnouskos, W. Pedrycz
    Year: 2009
    Citations: 23
    Source: Springer Science & Business Media

  • Title: Serious games: an attractive approach to improve awareness
    Authors: S. Sorace, E. Quercia, E. La Mattina, C.Z. Patrikakis, L. Bacon, G. Loukas, et al.
    Year: 2018
    Citations: 22
    Source: Community-Oriented Policing and Technological Innovations, 1–9

  • Title: Changing mobile data analysis through deep learning
    Authors: P. Kasnesis, C.Z. Patrikakis, I.S. Venieris
    Year: 2017
    Citations: 20
    Source: IT Professional, 19(3), 17–23
  • Title: An ontology-based smart production management system
    Authors: D.T. Meridou, A.P. Kapsalis, M.E.C. Papadopoulou, E.G. Karamanis, et al.
    Year: 2015
    Citations: 19
    Source: IT Professional, 17(6), 36–46

  • Title: Using personalized mashups for mobile location based services
    Authors: A.S. Voulodimos, C.Z. Patrikakis
    Year: 2008
    Citations: 19
    Source: International Wireless Communications and Mobile Computing Conference

  • Title: Intelligent performance prediction: the use case of a Hadoop cluster
    Authors: D. Uzunidis, P. Karkazis, C. Roussou, C. Patrikakis, H.C. Leligou
    Year: 2021
    Citations: 18
    Source: Electronics, 10(21), 2690

  • Title: Combating fake news with transformers: a comparative analysis of stance detection and subjectivity analysis
    Authors: P. Kasnesis, L. Toumanidis, C.Z. Patrikakis
    Year: 2021
    Citations: 18
    Source: Information, 12(10), 409

βœ… Conclusion

Professor Charalampos Z. Patrikakis exemplifies the modern research leaderβ€”deeply scholarly, highly innovative, and globally engaged 🌐. His academic achievements, combined with real-world impact through innovation, mentorship, and professional service, mark him as a transformative figure in the fields of AI, IoT, and secure communication systems πŸ€–πŸ’‘. With a strong commitment to interdisciplinary research, educational excellence, and societal relevance, he contributes meaningfully to shaping the future of digital technology and its applications πŸš€. His balanced expertise in academia, industry, and policy makes him an ideal role model and a worthy candidate for high-level recognition, including the Best Researcher Award πŸ…πŸ“ˆ.

Meichen Feng | Data Science | Best Researcher Award

Prof. Meichen Feng | Data Science | Best Researcher Award

Professor at Shanxi Agricultural University, China.

Feng Meichen is a distinguished professor at Shanxi Agricultural University, specializing in crop ecology, precision agriculture, and agricultural information technology. As the Deputy Dean of the College of Agriculture, she has led 22 research projects, authored 82 SCI/Scopus-indexed papers, and secured 18 patents, demonstrating a strong commitment to advancing sustainable agriculture. With 988 citations and an H-index of 19, her work has significantly impacted agricultural innovation and technology. She has published 5 books, contributed to multiple academic committees, and serves on the editorial boards of leading agricultural journals. Her research focuses on improving crop yield, resource efficiency, and environmental sustainability, benefiting both academia and local farming communities. While her expertise is well-recognized in China, expanding global collaborations could further enhance her research impact. With a remarkable career in agricultural research and innovation, Feng Meichen is an outstanding candidate for the Best Researcher Award.

Professional ProfileΒ 

Scopus Profile
ORCID Profile

Education

Feng Meichen holds an advanced degree in agriculture and crop ecology, equipping her with a deep understanding of agricultural information technology, precision farming, and ecological sustainability. Her academic journey has been dedicated to exploring innovative agricultural techniques that improve productivity while ensuring environmental sustainability. Through extensive research and continuous professional development, she has gained expertise in 3S technology (GIS, GPS, and remote sensing) and its application in modern agriculture. Her education has provided a strong foundation for her contributions to precision agriculture, crop management, and smart farming technologies. With a commitment to advancing agricultural science, she has successfully integrated academic knowledge with practical applications, benefiting both researchers and farming communities. Her ability to translate theoretical concepts into real-world solutions has made her a recognized leader in the field of crop science and agricultural technology.

Professional Experience

As a Professor and Deputy Dean at the College of Agriculture, Shanxi Agricultural University, Feng Meichen has established herself as a leader in agricultural research and education. She has successfully led 22 major research projects, contributing to advancements in crop ecology, precision farming, and smart agriculture. Her expertise extends beyond academia, as she actively collaborates with government agencies, research institutions, and industry leaders to develop sustainable farming practices. She has authored 82 peer-reviewed journal articles, secured 18 patents, and published 5 books, showcasing her multidisciplinary expertise. Additionally, she serves on the editorial boards of prestigious agricultural journals, including the Journal of Smart Agriculture and Shanxi Agricultural Sciences. She is also a member of multiple professional committees, influencing agricultural policies and research directions in China. Her extensive academic, research, and administrative experience highlights her dedication to advancing agricultural science and technology for long-term sustainability.

Research Interests

Feng Meichen’s research focuses on crop ecology, precision agriculture, and agricultural information technology, with an emphasis on sustainable and smart farming solutions. She integrates 3S technology (GIS, GPS, remote sensing) with crop production models to enhance agricultural efficiency, resource management, and environmental conservation. Her work aims to optimize crop yield, reduce environmental impact, and improve agricultural decision-making processes. She is particularly interested in applying artificial intelligence and big data analytics to develop predictive models for crop health monitoring and precision irrigation systems. Her research extends to organic dryland agriculture, where she explores climate-resilient farming techniques. By collaborating with industry experts, policymakers, and farmers, she ensures that her research findings have practical applications that benefit the agricultural sector. Her commitment to advancing smart agriculture technologies positions her as a pioneering researcher in the field of modern agriculture.

Awards and Honors

Feng Meichen has received multiple awards and recognitions for her outstanding contributions to agricultural science and research. As a Deputy Chief Expert in the Shanxi Modern Agricultural Specialty Grain Industry Technology System, she has played a pivotal role in shaping agricultural policies and technologies. Her patents and scientific contributions have earned her recognition at national and provincial levels. She has been honored by Shanxi Agricultural University and various academic organizations for her contributions to precision farming, agricultural technology development, and ecological sustainability. She is a member of several prestigious agricultural committees, including the China Modern Agriculture Graduate School and the Chinese Society of Crops. Through her active involvement in academic and industry collaborations, she continues to make a lasting impact on the agricultural sector. Her dedication to agricultural innovation and sustainability has established her as a leading researcher and academician.

Conclusion

Feng Meichen is a highly accomplished researcher, academic leader, and innovator in agricultural science. With extensive research contributions, patents, and leadership roles, she has significantly advanced the fields of crop ecology, precision agriculture, and smart farming technologies. Her work has not only improved crop productivity and resource efficiency but also contributed to sustainable farming practices that benefit both academic research and practical applications. While her impact is widely recognized in China, expanding international collaborations and industry partnerships could further elevate her global research influence. Her dedication to scientific excellence, innovation, and sustainability makes her an outstanding candidate for the Best Researcher Award.

Publications Top Noted

2025 Publications

πŸ”Ή Evaluating the Potential of Airborne Hyperspectral Imagery in Monitoring Common Beans with Common Bacterial Blight at Different Infection Stages

  • Authors: Binghan Jing, Jiachen Wang, Xin Zhang, Xiaoxiang Hou, Kunming Huang, Qianyu Wang, Yiwei Wang, Yaoxuan Jia, Meichen Feng, Wude Yang et al.
  • Year: 2025
  • DOI: 10.1016/j.biosystemseng.2025.02.002
  • Source: Biosystems Engineering (Crossref)

πŸ”Ή Potential Impacts of Climate Change on the Spatial Distribution Pattern of Naked Oats in China

  • Authors: Zhenwei Yang, Xujing Yang, Yuheng Huang, Yalin Zhang, Yao Guo, Meichen Feng, Mingxing Qin, Ning Jin, Muhammad Amjad, Chao Wang et al.
  • Year: 2025
  • DOI: 10.3390/agronomy15020362
  • Source: Agronomy (Crossref)

2024 Publications

πŸ”Ή A Model for the Detection of Ξ²-Glucan Content in Oat Grain Based on Near Infrared Spectroscopy

  • Authors: Yang Z., Cheng Z., Su P., Wang C., Qin M., Song X., Xiao L., Yang W., Feng M., Zhang M.
  • Year: 2024
  • DOI: 10.1016/j.jfca.2024.106105
  • Source: Journal of Food Composition and Analysis (Scopus – Elsevier)

πŸ”Ή Combined Use of Spectral Resampling and Machine Learning Algorithms to Estimate Soybean Leaf Chlorophyll

  • Authors: Gao C., Li H., Wang J., Zhang X., Huang K., Song X., Yang W., Feng M., Xiao L., Zhao Y. et al.
  • Year: 2024
  • DOI: 10.1016/j.compag.2024.108675
  • Source: Computers and Electronics in Agriculture (Scopus – Elsevier)

πŸ”Ή Efficient Prediction of SOC and Aggregate OC Components by Continuous Wavelet Transform Spectra Under Different Feature Selection Methods

  • Authors: Yang S., Wang Z., Ji C., Hao Y., Liang Z., Yan X., Qiao X., Feng M., Xiao L., Song X. et al.
  • Year: 2024
  • DOI: 10.1016/j.compag.2023.108550
  • Source: Computers and Electronics in Agriculture (Scopus – Elsevier)

πŸ”Ή Prediction of the Potential Distribution and Analysis of the Freezing Injury Risk of Winter Wheat on the Loess Plateau Under Climate Change

  • Authors: Qing Liang, Xujing Yang, Yuheng Huang, Zhenwei Yang, Meichen Feng, Mingxing Qing, Chao Wang, Wude Yang, Zhigang Wang, Meijun Zhang et al.
  • Year: 2024
  • Source: Journal of Integrative Agriculture

2023 Publications

πŸ”Ή AMF Inoculation Positively Regulates Soil Microbial Activity and Drought Tolerance of Oat

  • Authors: Li Y., Li L., Zhang B., LΓΌ Y.-F., Feng M.-C., Wang C., Song X.-Y., Yang W.-D., Zhang M.-J.
  • Year: 2023
  • DOI: 10.11674/zwyf.2022561
  • Source: Journal of Plant Nutrition and Fertilizers (Scopus – Elsevier)

πŸ”Ή Analyzing Protein Concentration from Intact Wheat Caryopsis Using Hyperspectral Reflectance

  • Authors: Zhang X., Hou X., Su Y., Yan X., Qiao X., Yang W., Feng M., Kong H., Zhang Z., Shafiq F. et al.
  • Year: 2023
  • DOI: 10.21203/rs.3.rs-2887647/v1
  • Source: Research Square

πŸ”Ή Hyperspectral Monitoring of Growth and Physiology Parameters of Winter Wheat Based on Different Quantification Methods

  • Authors: Wang Z.-G., Yang S., Feng M.-C., Yang W.-D., Liang Q., Yang X.-J., Yan X.-B., Sun X.-K., Qin M.-X., Wang C. et al.
  • Year: 2023
  • DOI: 10.2139/ssrn.4535833
  • Source: SSRN

πŸ”Ή Identification of Structural Variations Related to Drought Tolerance in Wheat (Triticum aestivum L.)

  • Authors: Zhao J., Li X., Qiao L., Zheng X., Wu B., Guo M., Feng M., Qi Z., Yang W., Zheng J.
  • Year: 2023
  • DOI: 10.1007/s00122-023-04283-4
  • Source: Theoretical and Applied Genetics (Scopus – Elsevier)