Prof. Dr. Jörg Schäfer | Machine Learning | Best Researcher Award

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Prof. Dr. Jörg Schäfer | Machine Learning | Best Researcher Award

Professor, Frankfurt University of Applied Sciences, Germany

Professor Dr. Jörg Schäfer is a renowned academic and researcher in the field of Computer Science, currently serving at the Frankfurt University of Applied Sciences in Germany. With a distinguished background in mathematics and a dynamic career bridging academia and industry, Dr. Schäfer is celebrated for his expertise in object-oriented programming, distributed systems, databases, and machine learning. His innovative research in artificial intelligence and human activity recognition, paired with decades of experience in technology strategy and complex system architecture, have made him a leading figure in both academic and professional circles.

Publication Profile

🎓 Education Background:

Dr. Schäfer completed his Ph.D. in Mathematics with summa cum laude at Ruhr-Universität Bochum (1991–1993) under the supervision of Prof. Dr. Sergio Albeverio. His doctoral work was part of the elite DFG graduate program “Geometrie und Mathematische Physik” and included an academic travel scholarship to Japan. Before his Ph.D., he earned a diploma in Mathematical Physics with distinction from Ruhr-Universität Bochum (1987–1991), laying the groundwork for his future interdisciplinary research.

💼 Professional Experience:

Dr. Schäfer’s professional career blends deep academic involvement with high-impact industry roles. Since 2009, he has been a professor at Frankfurt University of Applied Sciences, teaching subjects such as object-oriented programming, distributed systems, and machine learning. He is the founding member of the Industrial Data Science (INDAS) research group and serves as Chairman of the B.Sc. Computer Science program. Prior to his academic tenure, Dr. Schäfer held senior positions at Accenture (2005–2009) and Cambridge Technology Partners (2000–2005), where he was responsible for large-scale architecture design, pre-sales, delivery, and enterprise integration strategies. His early career includes project management roles at Westdeutsche Landesbank and a trainee program at Salomon Brothers, as well as scientific assistant roles focused on stochastic analysis.

🏅 Awards and Honors:

Professor Schäfer has received several prestigious accolades throughout his career. Most notably, he was awarded the Hessischer Hochschulpreis in 2022 for excellence in teaching. During his academic formation, he was also a scholar of the Studienstiftung des deutschen Volkes (1987–1991), reflecting his outstanding academic promise from an early stage.

🔬 Research Focus:

Dr. Schäfer’s research is focused on artificial intelligence, machine learning, mobile and distributed systems, and human activity recognition. His work leverages WiFi channel state information (CSI) for device-free activity detection, contributing significantly to the field of pervasive computing. He also has a foundational background in mathematical physics, particularly in Chern–Simons theory and stochastic analysis, which informs his unique approach to computer science problems.

🧩 Conclusion:

With a remarkable blend of academic rigor and real-world application, Professor Dr. Jörg Schäfer stands out as a multifaceted scholar and technology leader. His research continues to shape the future of data science and AI-driven systems, while his dedication to teaching and mentorship inspires the next generation of computer scientists.

📚 Top Publications

  1. Computer-implemented method for ensuring the privacy of a user, computer program product, device
    J Schäfer, D Toma
    US Patent 8,406,988, 2013
    Cited by: 237 articles

  2. Device free human activity and fall recognition using WiFi channel state information (CSI)
    N Damodaran, E Haruni, M Kokhkharova, J Schäfer
    CCF Transactions on Pervasive Computing and Interaction, 2020
    Cited by: 109 articles

  3. Human activity recognition using CSI information with nexmon
    J Schäfer, BR Barrsiwal, M Kokhkharova, H Adil, J Liebehenschel
    Applied Sciences, 2021
    Cited by: 75 articles

  4. Abelian Chern–Simons theory and linking numbers via oscillatory integrals
    S Albeverio, J Schäfer
    Journal of Mathematical Physics, 1995
    Cited by: 53 articles

  5. A rigorous construction of Abelian Chern-Simons path integrals using white noise analysis
    P Leukert, J Schäfer
    Reviews in Mathematical Physics, 1996
    Cited by: 43 articles

  6. Fall detection from electrocardiogram (ECG) signals and classification by deep transfer learning
    FS Butt, L La Blunda, MF Wagner, J Schäfer, I Medina-Bulo, et al.
    Information, 2021
    Cited by: 40 articles

  7. Device free human activity recognition using WiFi channel state information
    N Damodaran, J Schäfer
    2019 IEEE SmartWorld Conference
    Cited by: 37 articles

  8. Cloud computing – Evolution in der Technik, Revolution im Business
    G Münzl, B Przywara, M Reti, J Schäfer, et al.
    Berlin: BITKOM, 2009
    Cited by: 37 articles

 

Abdelhak Bouayad | machine Learning | Young Scientist Award

Posted on by Computer Scientists Awards

Dr. Abdelhak Bouayad | machine Learning | Young Scientist Award

PhD, UM6P, Morocco

📚 Abdelhak Bouayad is a dedicated researcher in artificial intelligence and privacy from the College of Computing at Mohammed VI Polytechnic University in Ben-Guérir, Morocco. His work explores innovative methods to protect sensitive data in machine learning models, ensuring both privacy and AI effectiveness. With a robust background in machine learning, data security, and federated learning, Abdelhak aims to drive advancements in privacy-preserving AI applications.

Publication Profile

Google Scholar

Education

🎓 Abdelhak Bouayad is currently pursuing a Ph.D. in Computer Science at Mohammed VI Polytechnic University under the guidance of Dr. Ismail Berrada. He holds an M.Sc. in Big Data Analytics and Smart Systems from Sidi Mohamed Ben Abdellah University, where he developed a thesis on lip reading for speech recognition, and a B.A. in Mathematics and Computer Science from the same institution in Fès, Morocco.

Experience

👨‍💻 Abdelhak has served as a Research Assistant at the College of Computing at Mohammed VI Polytechnic University since 2019. His research delves into the intersection of machine learning, privacy, and federated learning, with a focus on protocols to secure data exchanges and safeguard privacy within machine learning systems.

Research Focus

🔍 Abdelhak’s research is centered on artificial intelligence, machine learning, and privacy-preserving mechanisms. His primary focus lies in creating algorithms and protocols that protect sensitive data in machine learning models from potential exploitation. He aims to strengthen federated learning systems to ensure robust data privacy without compromising AI performance.

Awards and Honors

🏆 Abdelhak was awarded the College of Computing Fellowship for a pre-doctoral fellowship at Mohammed VI Polytechnic University from October 2018 to October 2019. This fellowship recognizes his commitment to research excellence and contributions to privacy-preserving AI methods.

Publication Highlights

NF-NIDS: Normalizing Flows for Network Intrusion Detection Systems

On the atout ticket learning problem for neural networks and its application in securing federated learning exchanges

Investigating Domain Adaptation for Network Intrusion Detection