Artificial Intelligence, Deep Learning, Biomedical Imaging, AI for Epigenetics, AI for Transportation Engineering, AI for Power Systems, AI for Electromagnetics.


Machine Learning, Deep Learning, Neural Network Architectures.

Research description

My research interests include Biomedical image analysis, Artificial Intelligence, Machine Learning, and AI architectures for Epigenomics. My long term research aspiration is to let machines gain faculties that put them at par with humans in terms of performing tasks in which humans currently outperform the machines.

Graduate Student Opportunities

Dr. Ashraf is currently seeking graduate students. Please contact him for more information.

Selected Publications

Journal Articles
1. Mantach, S: Gill, P; Oliver, D, Ashraf, A; Kordi, B. (2022). An Interpretable CNN Model for Classification of Partial Discharge Waveforms in 3D-Printed Dielectric Samples with Different Void Sizes. Neural Computing and Applications. 34(14): 11739–11750.

2. Khoshdel, V; Asefi, M; Ashraf, A; LoVetri, J. (2021). A Multi-Branch Deep Convolutional Fusion Architecture for 3D Microwave Inverse Scattering. Neural Computing and Applications. 33: 13467–13479.

3. Mantach, S.; Ashraf, A.; Janani, H; Kordi B. (2021). A Convolutional Neural Network-Based Model for Multi-Source and Single-Source Partial Discharge Pattern Classification Using Only Single-Source Training Set.
Energies. 14(5): 1355.

4. Jin, Y; Jia, S; Ashraf, A; Hu, P. (2020). Integrative Data Augmentation with U-Net Segmentation Masks Improves Detection of Lymph Node Metastases in Breast Cancer Patients. Cancers. 12(10): 2934-2946.

5. Puig J et al. (2020). The Aging Imageomics Study: Rationale, design and baseline characteristics of the study population. Mechanisms of Aging and Development. 111257: online.

6. Khoshdel, V; Asefy, M, Ashraf, A, LoVetri, J. (2020). Full 3D Microwave Breast Imaging Using a Deep-Learning Technique. Journal of Imaging. 6(2): 80-97.

7. Babak Taati, Shun Zhao, Ahmed Ashraf, Azin Asgarian, M Erin Browne, Kenneth M Prkachin, Alex Mihailidis, Thomas Hadjistavropoulos. (2019). Algorithmic Bias in Clinical Populations—Evaluating and Improving Facial Analysis Technology in Older Adults With Dementia. IEEE Access. 7: 25527-25534.

8. M Erin Browne, Thomas Hadjistavropoulos, Kenneth Prkachin, Ahmed Ashraf, Babak Taati. (2019). Pain Expressions in Dementia: Validity of Observers’ Pain Judgments as a Function of Angle of Observation. Journal of Nonverbal Behavior. 43(3): 1019.

9. Vahab Khoshdel, Ahmed Ashraf, Joe LoVetri. (2019). Enhancement of Multimodal Microwave-Ultrasound Breast Imaging Using a Deep Learning Technique. Sensors. 19(18): 4050.

10. Thomas Hadjistavropoulos, Michelle Browne, Ken Prkachin, Babak Taati, Ahmed Ashraf, Alex Mihailidis.(2018). Pain in severe dementia: A comparison of a fine-grained assessment approach to an observational checklist designed for clinical settings. European Journal of Pain. 22(5): 915-925.

11. Ahmed Ashraf, Babak Taati. (2016). Automated video analysis of handwashing behavior as a potential marker of cognitive health in older adults. IEEE Journal of Biomedical and Health Informatics (JBHI). 20(2):

12. Majid Mahrooghy, Ahmed B Ashraf, Dania Daye, Elizabeth S McDonald, Mark Rosen, Carolyn Mies, Michael Feldman, Despina Kontos. (2015). Pharmacokinetic tumor heterogeneity as a prognostic biomarker for classifying breast cancer recurrence risk. IEEE Transactions on Biomedical Engineering (TBME). 62(6):

13. Ahmed Ashraf, Bilwaj Gaonkar, Carolyn Mies, Angela DeMichele, Mark Rosen, Christos Davatzikos, Despina Kontos. (2015). Breast DCE-MRI kinetic heterogeneity tumor markers: preliminary associations with neoadjuvant chemotherapy response. Translational Oncology. 8(3): 154-162.

14. Ashraf, A; Daye, D; Gavenonis, S; Mies, C; Feldman, M; Rosen, M; Kontos, D. (2014). Identification of intrinsic imaging phenotypes for breast cancer tumors: preliminary associations with gene expression profiles. Radiology. 272(2): 374-384.

15. Ashraf,A; Feldman, M; Rose, M; Mies, C; Kontos, D. (2013). A Multichannel Markov Random Field Framework for Tumor Segmentation with an application to classification of Gene-Expression-based breast cancer recurrence risk. IEEE Transactions on Medical Imaging. ,

16. Lucey, S; Ashraf, A. (2013). Nearest neighbor classification generalization through spatially constrained filters. Pattern Recognition. 46(1): 325-331.
Last Author,

17. Ashraf, A; Lucey, S; Chen, T. (2010). Reinterpreting the application of Gabor-filters as a manipulation of themargin in linear support vector machines. IEEE Transactions on Pattern Analysis and Machine Intelligence.