Piotr Porwik | Machine Learning and AI Applications | Best Researcher Award

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Prof. Dr. Piotr Porwik | Machine Learning and AI Applications | Best Researcher Award

University of Silesia | Poland

Prof. Dr. Piotr Porwik is a full professor in the Institute of Computer Science at the University of Silesia in Katowice, specializing in engineering and technical sciences. He earned his M.Sc. in computer science from the University of Silesia in 1978, his Ph.D. in 1985, and completed his habilitation in 2006 at AGH University of Science and Technology in Krakow. His research spans machine learning, biometrics, image processing, biomedical imaging, and spectral methods for Boolean functions. Across his career, he has authored 81 scientific documents that have attracted 1,003 citations from 783 citing documents, and he holds an h-index of 17. He has published extensively in journals, international conferences, books, and book chapters, while also supervising Master’s and Ph.D. students. Prof. Porwik has served in major academic leadership roles, including Deputy Dean and Director of the Institute, and played a key role in shaping academic publishing as Editor-in-Chief of the Journal of Medical Informatics and Technologies. His achievements have been recognized through numerous distinctions, including the Bronze Cross of Merit and multiple awards from the President of the University of Silesia for scientific accomplishments. His work continues to advance biometric security, classifier development, and biomedical informatics, underscoring his long-standing academic influence and research innovation.

Profiles : Scopus | Orcid

Featured Publications

Wrobel, K., Porwik, P., & Orczyk, T. (2025). “Evaluation of the Effectiveness of Ranking Methods in Detecting Feature Drift in Artificial and Real Data” in (Book) / Lecture Notes in?

Mensah Dadzie, B., & Porwik, P. (2025). “Feature-Based Drift Detection in Non-stationary Data Streams Using Multiple Classifiers: A Comprehensive Analysis” in (Book)

Porwik, P., Orczyk, T., Wrobel, K., & Mensah Dadzie, B. (2025). “A Novel Method for Drift Detection in Streaming Data Based on Measurement of Changes in Feature Ranks” in Journal of Artificial Intelligence and Soft Computing Research, (DOI: 10.2478/jaiscr-2025-0008).

Porwik, P., Orczyk, T., & Japkowicz, N. (2024). “Supervised and Unsupervised Analysis of Feature Drift in a New Type of Detector” in Preprint (Research Square)

Porwik, P., Orczyk, T., & Doroz, R. (2022). “A Stable Method for Detecting Driver Maneuvers Using a Rule Classifier” in Lecture Notes in Computer Science

Nicholas Otumi | Neuroscience Data Analysis | Best Researcher Award

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Mr. Nicholas Otumi | Neuroscience Data Analysis | Best Researcher Award

University of Rochester | United States

Nicholas Otumi is a biomedical imaging researcher with a strong foundation in diagnostic imaging and deep learning. He holds a BSc in Diagnostic Imaging Technology from the University of Cape Coast (Ghana) and an MS in Diagnostic Imaging (Bioengineering & Biomedical Engineering) from the University of Rochester (USA), where his coursework included deep learning, inverse problems in imaging, clinical imaging, and signal processing. He has held research and technical roles at multiple institutions: as a remote Research Assistant at Indiana University working on pharmaceutical pricing and market analytics, and at the University of Rochester contributing to segmentation (with UNet-R) and image analysis in brain CT. Previously, as a Research and Teaching Assistant at UCC, he supported imaging equipment courses, data analysis, and undergraduate research. His research interests center on medical image analysis, especially applying deep learning to brain MRI and CT segmentation, classification of disease from imaging, and imaging in resource-constrained settings. He has several manuscripts under review or published, including a multicentre survey on advanced brain MRI in low-resource settings and case reports in radiology.  He is a recipient of honors such as the Harry W. Fischer Research Funds (2025) and the HSEAS Dean’s Fellowship (2024) at Rochester, as well as campus leadership awards in Ghana. Nicholas is committed to advancing AI-driven neuroimaging and translational imaging research across low- and middle-income settings, aiming to bridge technology gaps and enhance equitable access to advanced diagnostic tools.

Profiles : Orcid | Google Scholar

Featured Publications

Piersson, A. D., Nunoo, G., Dzefi-Tettey, K., & Otumi, N. (2025). Utility of advanced brain MRI techniques for clinical and research purposes in a low-resource setting: A multicentre survey. Next Research.

Fiagbedzi, E., Arkorful, J., Brobbey, I. F., Appiah, E., Nyarko, S., Otumi, N., Piersson, A. D., Nimo, O., Ofori, I. N., & Gorleku, P. N. (2025). A case of ruptured infrapatellar bursa sac with Baker’s cyst. Radiology Case Reports, 20(1).

Fiagbedzi, E., Arkorful, J., Appiah, E., Otumi, N., Ofori, I., & Gorleku, P. N. (2024). A rare case of intussusception in a 6-month-old baby. Radiology Case Reports, 19(10).