Mohammad Shifat-E-Rabbi | Mathematical Modeling | Best Researcher Award

Posted on by ScienceFather

Dr. Mohammad Shifat-E-Rabbi | Mathematical Modeling | Best Researcher Award

Assistant Professor at North South University, Bangladesh

Dr. Mohammad Shifat-E-Rabbi is an Assistant Professor in the Department of Electrical and Computer Engineering at North South University, Bangladesh. He earned his Ph.D. in Biomedical Engineering from the University of Virginia, where his dissertation, “Transport Generative Models in Pattern Analysis and Recognition,” focused on developing mathematical and computational frameworks for artificial intelligence and machine learning. Dr. Shifat-E-Rabbi’s research interests include applied mathematics, machine learning, image informatics, computational biology, and pattern recognition. He has contributed to various publications, such as “End-to-End Signal Classification in Signed Cumulative Distribution Transform Space” in IEEE Transactions on Pattern Analysis and Machine Intelligence. At North South University, he teaches courses in Artificial Intelligence, Machine Learning, and programming languages. His academic journey began with a B.Sc. in Electrical and Electronic Engineering from the Bangladesh University of Engineering and Technology.

Professional Profile 

  • Google Scholar
  • Scopus Profile
  • ORCID Profile

Education

Dr. Mohammad Shifat-E-Rabbi’s educational journey began at Rangpur Zilla School and Rangpur Cadet College in Bangladesh. He earned his B.Sc. in Electrical and Electronic Engineering from the Bangladesh University of Engineering and Technology (BUET) in 2015. He then pursued his Ph.D. in Biomedical Engineering at the University of Virginia (UVa), USA, focusing on Pattern Analysis and Recognition within the Imaging and Data Science Laboratory. His dissertation, titled “Transport Generative Models in Pattern Analysis and Recognition,” centered on developing mathematical and computational frameworks for artificial intelligence and machine learning. During his doctoral studies, Dr. Shifat-E-Rabbi served as a research assistant under the supervision of Prof. Gustavo Rohde.

Professional Experience

Dr. Mohammad Shifat-E-Rabbi is an Assistant Professor in the Department of Electrical and Computer Engineering at North South University, Bangladesh. He earned his Ph.D. in Biomedical Engineering from the University of Virginia, USA, where he specialized in Pattern Analysis and Recognition within the Imaging and Data Science Laboratory. During his doctoral studies, Dr. Shifat-E-Rabbi served as a research assistant under the supervision of Prof. Gustavo Rohde. Prior to his Ph.D., he completed his B.Sc. in Electrical and Electronic Engineering at the Bangladesh University of Engineering and Technology (BUET) in 2015. At BUET, he was involved in the Digital Signal Processing research lab. Dr. Shifat-E-Rabbi’s research interests encompass applied mathematics, machine learning, image informatics, computational biology, and pattern recognition. In his current role, he teaches courses in Artificial Intelligence, Machine Learning, and programming languages. His academic journey began at Rangpur Zilla School and Rangpur Cadet College in Bangladesh.

Research Interest

Dr. Mohammad Shifat-E-Rabbi’s research interests encompass applied mathematics, machine learning, image informatics, computational biology, and pattern recognition. He has contributed to the development of the Radon Signed Cumulative Distribution Transform (R-CDT) and its applications in classifying signed images. Additionally, he has worked on predictive modeling of hematoma expansion in intracerebral hemorrhage patients and the real-time intelligent classification of COVID-19 and thrombosis through massive image-based analysis of platelet aggregates. Dr. Shifat-E-Rabbi has also explored transport-based morphometry for analyzing nuclear structures in digital pathology images across various cancers. His work aims to bridge theoretical advancements with practical applications, enhancing the understanding and analysis of complex biological and medical data.

Award and Honor

Dr. Mohammad Shifat-E-Rabbi has been recognized for his significant contributions to the fields of artificial intelligence and machine learning. His collaborative research on “End-to-End Signal Classification in Signed Cumulative Distribution Transform Space” was published in the prestigious IEEE Transactions on Pattern Analysis and Machine Intelligence. This work, conducted alongside colleagues from the University of Virginia, received support from esteemed institutions such as the National Institutes of Health and the Office of Naval Research, underscoring its impact and importance.

Research Skill

Dr. Mohammad Shifat-E-Rabbi possesses a robust set of research skills that bridge applied mathematics, machine learning, and computational biology. His expertise includes developing mathematical models and computational frameworks, notably in pattern recognition and image informatics. Dr. Shifat-E-Rabbi has contributed to the advancement of the Radon Cumulative Distribution Transform (R-CDT), enhancing image classification techniques. His collaborative work on “End-to-End Signal Classification in Signed Cumulative Distribution Transform Space” exemplifies his ability to integrate theoretical concepts with practical applications, leading to more efficient signal classification methods. His research portfolio demonstrates proficiency in handling complex datasets, developing innovative algorithms, and applying interdisciplinary approaches to solve real-world problems. Dr. Shifat-E-Rabbi’s commitment to advancing artificial intelligence and machine learning is evident through his scholarly publications and ongoing projects.

Conclusion

If the researcher has made significant contributions through innovation, publications, and demonstrated impact, they would be a strong candidate for the Best Researcher Award. However, if the research is still in its early stages or lacks broader validation, additional work on practical applications, benchmarking, and interdisciplinary collaborations could further strengthen their case.

Publications Top Noted

  • Massive image-based single-cell profiling reveals high levels of circulating platelet aggregates in patients with COVID-19

    • Authors: M. Nishikawa, H. Kanno, Y. Zhou, T.H. Xiao, T. Suzuki, Y. Ibayashi, J. Harmon, M. Shifat-E-Rabbi, et al.
    • Published in: Nature Communications
    • Year: 2021
    • Citations: 71

  • Enabling early detection of osteoarthritis from presymptomatic cartilage texture maps via transport-based learning

    • Authors: S. Kundu, B.G. Ashinsky, M. Bouhrara, E.B. Dam, S. Demehri, M. Shifat-E-Rabbi, et al.
    • Published in: Proceedings of the National Academy of Sciences
    • Year: 2020
    • Citations: 57

  • Cell image classification: a comparative overview

    • Authors: M. Shifat-E-Rabbi, X. Yin, C.E. Fitzgerald, G.K. Rohde
    • Published in: Cytometry Part A
    • Year: 2020
    • Citations: 39

  • Radon cumulative distribution transform subspace modeling for image classification

    • Authors: M. Shifat-E-Rabbi, X. Yin, A.H.M. Rubaiyat, S. Li, S. Kolouri, A. Aldroubi, G.K. Rohde
    • Published in: Journal of Mathematical Imaging and Vision
    • Year: 2021
    • Citations: 28

  • PREHEAT: Precision heart rate monitoring from intense motion artifact corrupted PPG signals using constrained RLS and wavelets

    • Authors: M.S. Islam, M. Shifat-E-Rabbi, A.M.A. Dobaie, M.K. Hasan
    • Published in: Biomedical Signal Processing and Control
    • Year: 2017
    • Citations: 26

  • Blind Deconvolution of Ultrasound Images Using ℓp\ell_p-Norm-Constrained Block-Based Damped Variable Step-Size Multichannel LMS Algorithm

    • Authors: M.K. Hasan, M. Shifat-E-Rabbi, S.Y. Lee
    • Published in: IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
    • Year: 2016
    • Citations: 12

  • Local sliced Wasserstein feature sets for illumination invariant face recognition

    • Authors: Y. Zhuang, S. Li, M. Shifat-E-Rabbi, X. Yin, A.H.M. Rubaiyat, G.K. Rohde
    • Published in: Pattern Recognition
    • Year: 2025
    • Citations: 10

  • End-to-end signal classification in signed cumulative distribution transform space

    • Authors: A.H.M. Rubaiyat, S. Li, X. Yin, M. Shifat-E-Rabbi, Y. Zhuang, G.K. Rohde
    • Published in: IEEE Transactions on Pattern Analysis and Machine Intelligence
    • Year: 2024
    • Citations: 9

  • Nearest Subspace Search in The Signed Cumulative Distribution Transform Space for 1D Signal Classification

    • Authors: A.H.M. Rubaiyat, M. Shifat-E-Rabbi, Y. Zhuang, S. Li, G.K. Rohde
    • Published in: IEEE International Conference on Acoustics, Speech and Signal Processing
    • Year: 2022
    • Citations: 9

  • Speckle tracking and speckle content based composite strain imaging for solid and fluid filled lesions

    • Authors: M. Shifat-E-Rabbi, M.K. Hasan
    • Published in: Ultrasonics
    • Year: 2017
    • Citations: 9