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

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

 

MUNMI DUTTA | Machine Learning | Best Researcher Award

Mrs. MUNMI DUTTA | Machine Learning | Best Researcher Award

Research Scholar, Assam Engineering College, India

🔬 Munmi Dutta is a dedicated academic and researcher with expertise in Artificial Intelligence and Machine Learning. Her research focuses on speaker identification, product categorization, and generative AI for online education systems. Currently pursuing her Ph.D. at Gauhati University, she has contributed significantly to AI-driven applications in e-commerce and speech processing.

Publication Profile

Scopus

Strengths for the Award

  1. Academic Excellence: Munmi Dutta’s academic journey, including a Ph.D. in progress and an M.Tech in Electronics and Communication Technology, demonstrates her commitment to research and knowledge advancement.
  2. Project Experience: She has completed several significant projects, such as developing a fire alarm system, a remote-controlled fan regulator, and a pitch determination system using neural networks. These projects showcase her practical and research skills in both hardware and software domains.
  3. Research in AI and Machine Learning: Dutta’s work in speaker identification using Artificial Neural Networks (ANN) and product categorization in e-commerce using machine learning reflects her proficiency in cutting-edge technologies, especially Artificial Intelligence. Her research also addresses real-world problems, adding practical relevance.
  4. Publications: She has multiple journal publications, including in the prestigious Applied Soft Computing Journal, which demonstrates her research output in emerging technologies like machine learning and neural networks. The acceptance of a book chapter on AI and IoT in online education further highlights her versatility.
  5. Collaborative Research: The variety of co-authors in her publications suggests that Dutta is capable of working in teams and contributes effectively to collaborative research, which is a valuable quality in any researcher.

Areas for Improvement

  1. Broader Research Impact: Although her work in machine learning and AI is commendable, the scope of her research could be expanded to other interdisciplinary areas to broaden the impact. This would also enhance her chances of being recognized as a top researcher in her field.
  2. PhD Completion: As she is still pursuing her PhD, completing this degree could further strengthen her candidacy for the Best Researcher Award, as a completed doctoral degree adds academic credibility.
  3. Leadership and Mentorship: While her publications and research experience are impressive, demonstrating leadership in research groups or mentorship roles would help solidify her position as a leading researcher.
  4. International Exposure: Although she has participated in conferences and published research, gaining more international exposure by attending or presenting at global conferences could help elevate her recognition and contribution to the global research community.

Education

Munmi Dutta holds an M.Tech in Electronics and Communication Technology from IST, Gauhati University, with a CGPA of 7.13. She completed her B.E. in Applied Electronics and Instrumentation Engineering from GIMT, also under Gauhati University, achieving a percentage of 67.67%. Her academic journey began at Don Bosco High School, followed by J. B. College for higher secondary education. 🎓💡

Experience

💼 Munmi Dutta has extensive experience in academic research, with a focus on AI applications in speech processing, product categorization, and e-commerce. She has presented at national and international conferences and co-authored several notable publications. Her work includes building speaker identification systems and applying neural networks for speech recognition.

Research Focus

🧠 Munmi Dutta’s research interests include speaker identification using artificial neural networks, machine learning for product categorization in e-commerce, and generative AI in education systems. She has worked on innovative projects such as pitch determination for speaker identification, remote-controlled fan regulators, and fire alarms using temperature sensors.

Awards and Honors

🏆 Munmi Dutta has earned recognition for her contributions to AI and technology, including presenting at prestigious conferences like the International Conference on Recent Developments in Science, Technology, Engineering, and Management (ICRDSTEM-2022). Her work in the fields of AI and e-commerce has garnered respect within academic circles.

Publication Top Notes

📝 “Closed-Set Text Independent Speaker Identification System Using Multiple ANN Classifiers” – Advances in Intelligent Systems and Computing, 2014. Cited by several researchers, this paper focuses on the application of ANN for speaker identification Link.

📝 “Product Categorization in Fashion and Lifestyle Commerce using Machine Learning” – Journal of Emerging Technologies and Innovation Research, 2022. This study explores the use of machine learning in e-commerce product categorization Link.

📝 “Incremental-based YoloV3 model with Hyper-parameter Optimization for Product Image Classification in E-commerce Sector” – Applied Soft Computing Journal, 2024. A detailed examination of YoloV3 model optimization for product image classification Link.

Conclusion

Munmi Dutta has demonstrated strong potential as a researcher with her contributions in AI, machine learning, and electronics. Her numerous publications, research projects, and continued pursuit of a Ph.D. make her a promising candidate for the Best Researcher Award. However, achieving more interdisciplinary impact, completing her PhD, and gaining further international exposure will significantly bolster her qualifications for this award.