Kaoutar Ben Ahmed

Assistant Teaching Professor

Dr. Kaoutar Ben Ahmed has over 6 years of experience in education and over 11 years of experience in research on the application of artificial intelligence and machine learning to solve real world problems. Dr. Ben Ahmed received her first Ph.D. degree in information science from Abdelmalek Essaadi University, Morocco in 2016. She received her second Ph.D. degree in computer science and engineering from the University of South Florida, USA in Dec, 2022. Her main research concerns addressing automatic medical image analysis problems using novel deep learning methods. Dr. Ben Ahmed’s research interests are artificial intelligence, machine learning, data mining, and deep learning. She is a recipient of the 2018 American Association of University Women Fellowship and the 2015 Fulbright Joint-Supervision Scholarship.

Honors and Awards
  • American Association of University Women Fellowship
    Issued by AAUW · (Aug 2018)
  • Joint- Supervision Fulbright Scholarship
    Issued by Fulbright · (Aug 2015)
  • Excellence Scholarship for Scientific Research
    Issued by Morrocan National Center for Scientific and Technical Research CNRST. · (Jan 2013)
Research and Educational Interests
  • Deep Learning
  • Data Mining
  • Machine Learning
  • Artificial Intelligence
  • Medical image Processing
  • Medical imaging
Background Education

2022 Ph.D., Computer Science and Engineering, University of South Florida
2016 Ph.D., Information Science, Abdelmaalek Essaadi University
2012 B.S., Computer Engineering, Abdelmaalek Essaadi University

Professional Experience
  • Assistant Teaching Professor, School of Computing and Information Sciences, Florida International University (2022 – Present)
  • Graduate Teaching Assistant, Department of Computer Science and Engineering, University of South Florida (2017- 2022)
  • R & D Engineer, Bluesettle SARL, Tangiers, Morocco (2012 – 2014)
Selected Publications
  1. K. Ben Ahmed, L. O. Hall, D. B. Goldgof and R. Fogarty, “Achieving Multisite Generalization for CNN-Based Disease Diagnosis Models by Mitigating Shortcut Learning,” in IEEE Access, vol. 10, pp. 78726-78738, 2022, doi: 10.1109/ACCESS.2022.3193700.
  2. K. B. Ahmed, G. M. Goldgof, R. Paul, D. B. Goldgof and L. O. Hall, “Discovery of a Generalization Gap of Convolutional Neural Networks on COVID-19 X-Rays Classification,” in IEEE Access, vol. 9, pp. 72970-72979, 2021, doi: 10.1109/ACCESS.2021.3079716.
  3. Ben Ahmed K, Hall LO, Goldgof DB, Gatenby R. Ensembles of Convolutional Neural Networks for Survival Time Estimation of High-Grade Glioma Patients from Multimodal MRI. Diagnostics (Basel). 2022 Jan 29;12(2):345. doi: 10.3390/diagnostics12020345. PMID: 35204436; PMCID: PMC8871067.
  4. K. B. Ahmed, L. O. Hall, R. Liu, R. A. Gatenby and D. B. Goldgof, “Neuroimaging Based Survival Time Prediction of GBM Patients Using CNNs from Small Data,” 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), Bari, Italy, 2019, pp. 1331-1335, doi: 10.1109/SMC.2019.8913929.
  5. Kaoutar B. Ahmed, Lawrence O. Hall, Dmitry B. Goldgof, Renhao Liu, and Robert A. Gatenby “Fine-tuning convolutional deep features for MRI based brain tumor classification”, Proc. SPIE 10134, Medical Imaging 2017: Computer-Aided Diagnosis, 101342E (3 March 2017); https://doi.org/10.1117/12.2253982
  6. R. Liu, L. O. Hall, K. W. Bowyer, D. B. Goldgof, R. Gatenby and K. Ben Ahmed, “Synthetic minority image over-sampling technique: How to improve AUC for glioblastoma patient survival prediction,” 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Banff, AB, Canada, 2017, pp. 1357-1362, doi: 10.1109/SMC.2017.8122802.
  7. K. Ben Ahmed, B. Goel, P. Bharti, S. Chellappan and M. Bouhorma, “Leveraging Smartphone Sensors to Detect Distracted Driving Activities,” in IEEE Transactions on Intelligent Transportation Systems, vol. 20, no. 9, pp. 3303-3312, Sept. 2019, doi: 10.1109/TITS.2018.2873972.
  8. B. Goel, A. K. Dey, P. Bharti, K. B. Ahmed and S. Chellappan, “Detecting Distracted Driving Using a Wrist-Worn Wearable,” 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Athens, Greece, 2018, pp. 233-238, doi: 10.1109/PERCOMW.2018.8480282.
  9. Renhao Liu, L. O. Hall, D. B. Goldgof, Mu Zhou, R. A. Gatenby and K. B. Ahmed, “Exploring deep features from brain tumor magnetic resonance images via transfer learning,” 2016 International Joint Conference on Neural Networks (IJCNN), Vancouver, BC, 2016, pp. 235-242, doi: 10.1109/IJCNN.2016.7727204.
  10. Ahmed, Kaoutar Ben, et al. “Sentiment analysis for smart cities: state of the art and opportunities.” Proceedings on the international conference on internet computing (ICOMP). The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp), 2016.
  11. Ahmed, Kaoutar Ben, Mohammed Bouhorma, and Mohamed Ben Ahmed. “Smart citizen sensing: a proposed computational system with visual sentiment analysis and big data architecture.” International Journal of Computer Applications 152.6 (2016): 20-27.
  12. El Amrani, C., Filali, K. B., Ahmed, K. B., Diallo, A. T., Telolahy, S., & El-Ghazawi, T. (2012, May). A compartive study of cloud computing middleware. In 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012) (pp. 690-693). IEEE.


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