Peer-Reviewed Publications

Under Review

  1. Giuseppina Carannante, Dimah Dera, Nidhal Bouaynaya, Hassan M. Fathallah-Shaykh, and Ghulam Rasool “SUPER-Net: Trustworthy Medical Segmentation with Uncertainty Estimation”, under review in IEEE Transactions on Medical Image Processing. Pre-print available at: link.

  2. Asim Waqas, Aakash Tripathi, Ravi P. Ramachandran, Paul Stewart, and Ghulam Rasool, “Multimodal Data Integration for Oncology in the Era of Deep Neural Networks: A Review”, under review in IEEE Transaction on Neural Networks and Learning Systems. (paper link)

  3. Nielsen, I. E., Epifano, J. R., Rasool, G., Bouaynaya, N. C., & Ramachandran, R. P. "Performance Evaluation of Combination Methods of Saliency Mapping Algorithms." (paper link)

  4. Asim Waqas, Warda Shahnawaz, Javeria Naveed, Muhammad Shoaib Asghar and Ghulam Rasool, “Advancements in Integrating Multimodal Data for Enhanced Insights in Digital Pathology”, under submission in BJR Artificial Intelligence, 2023.

  5. Aakash Tripathi, Asim Waqas, Kavya Venkatesan, Yasin Yilmaz, and Ghulam Rasool, “Building Flexible and Scalable Multimodal Oncology Datasets”, under submission in MDPI Sensors, 2023.

Peer-Reviewed Journals

           2023

  1. Asim Waqas, Marilyn M. Bui, Eric F. Glassy, Issam El Naqa, Piotr A. Borkowski, Andrew A. Borkowski, Ghulam Rasool, “Revolutionizing Digital Pathology with the Power of Generative Artificial Intelligence and Foundation Models”, accepted at Elsevier Laboratory Investigation, 2023. (paper link)

  2. Ahmed, S., Nielsen, I. E., Tripathi, A., Siddiqui, S., Ramachandran, R. P., & Rasool, G. (2023). Transformers in time-series analysis: A tutorial. Circuits, Systems, and Signal Processing, 1-34. (paper link)

  3. Dera, D., Ahmed, S., Bouaynaya, N. C., & Rasool, G. (2023). TRustworthy Uncertainty Propagation for Sequential Time-Series Analysis in RNNs. IEEE Transactions on Knowledge and Data Engineering. (paper link)

  4. Epifano, J. R., Ramachandran, R. P., Masino, A. J., & Rasool, G. (2023). Revisiting the fragility of influence functions. Neural Networks, 162, 581-588. (paper link)

  5. Y. Barhoumi, N. C. Bouaynaya and G. Rasool, "Efficient Scopeformer: Toward Scalable and Rich Feature Extraction for Intracranial Hemorrhage Detection," in IEEE Access, vol. 11, pp. 81656-81671, 2023, doi: 10.1109/ACCESS.2023.3301160. (paper link)

  6. I. E. Nielsen, R. P. Ramachandran, N. Bouaynaya, H. M. Fathallah-Shaykh and G. Rasool, "EvalAttAI: A Holistic Approach to Evaluating Attribution Maps in Robust and Non-Robust Models," in IEEE Access, vol. 11, pp. 82556-82569, 2023, doi: 10.1109/ACCESS.2023.3300242. (paper link)

     

    2022

  7. Mashood M. Mohsan, M. Usman Akram, Ghulam Rasool, Norah Saleh Alghamdi, M. Abdullah Aamer Baqai, Muhammad Abbas, “Vision Transformer and Language Model based Radiology Report Generation”, in IEEE Access, vol. 11, pp. 1814-1824, 2023, (paper link).

  8. Asim Waqas, Nidhal Bouaynaya, Hama Farooq, and Ghulam Rasool, “Exploring Robust Architectures for Deep Artificial Neural Networks”, Nature Communication Engineering 1, 46 (2022). (paper link)

  9. Sabeen Ahmed, Dimah Dera, Muhammad Saud Ul Hassan, Nidhal Bouaynaya and Ghulam Rasool, “Failure Detection in Deep Neural Networks for Medical Imaging”, Frontiers in Medical Technology, 4:919046. (paper link)

  10. Ian Nielsen, Dimah Dera, Ghulam Rasool, Nidhal C. Bouaynaya and Ravi P. Ramachandran, “Robust Explainability: A Tutorial on Gradient-Based Saliency Methods for Deep Neural Networks”, IEEE Signal Processing Magazine (SPM) Special Issue on Explainability in Data Science: Interpretability, Reproducibility, and Replicability. (paper link)

     

    2021

  11. Dimah Dera, Nidhal Bouaynaya, Ghulam Rasool, and Hassan M. Fathallah-Shaykh, “PremiUm-CNN: Propagating Uncertainty Towards Robust Convolutional Neural Networks”, IEEE Transactions on Signal Processing, 2021. (paper link)

  12. Daniel E. Cahall, Ghulam Rasool, Nidhal C. Bouaynaya and Hassan M. Fathallah-Shaykh, “Inception Modules Enhance Brain Tumor Segmentation”, Frontiers in Computational Neuroscience 13 (2019): 44. (paper link) .

  13. Nesrine Amor, Ghulam Rasool, Nidhal Carla Bouaynaya, and Roman Shterenberg, “Constrained Particle Filtering for Movement Identification in Forearm Prosthesis”, Signal Processing, 161 (2019): 25-35. (paper link) 

  14. Ghulam Rasool, William Z. Rymer, Allison Wang, and Sabrina Lee, “Shear Waves Reveal Viscoelastic Changes in Skeletal Muscles After Hemispheric Stroke”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26(10), pp 2006-2014, 2018. (paper link)

  15. Ghulam Rasool, Babak Afsharipour, Nina L. Suresh and William Zev Rymer, “Spatial pattern analysis of muscle architectural changes post-stroke”, IEEE Transactions on Neural Systems and Rehabilitation Engineering 25(10), pp 1802 – 1811, 2017. (paper link)

  16. Ghulam Rasool, Kamran Iqbal, Nidhal Bouaynaya and Gannon White, “Real-time Task Discrimination for Myoelectric Control Employing Task-Specific Muscle Synergies”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24(1), pp 98-108 2015. (paper link)

  17. Mufassir Abdur Rahim, Ghulam Rasool, Nasir Ahmad, “EMG-Controlled Transradial Prostheses - An Investigation into Machine Learning Techniques”, International Journal of Computer Applications, 174(3):1-8, September 2017. (paper link)

  18. Gregory S. Taylor, Yupo Chan and Ghulam Rasool, “A Three-Dimensional Bin-Packing Model: Exact Multi-criteria Solution and Computational Complexity” Annals of Operations Research, 251, 397–427, 2017. (paper link)

  19. Albunashee, Ghulam Rasool, K. Iqbal, and G. White. "A New Technique to Improve the Operation of Prosthetic Limbs during Muscle Fatigue." Journal of the Arkansas Academy of Science 70.1 (2016): 35-39. (paper link)

  20. Ghulam Rasool, Nidhal Bouaynaya, Kamran Iqbal, and Gannon White, “Surface Myoelectric Signal Classification Using the AR-GARCH Model”, Biomedical Signal Processing and Control, 13 (2014): 327-336. (paper link)

  21. Ghulam Rasool, Kamran Iqbal, Gannon A. White, “Myoelectric activity detection during a Sit-to-Stand movement using threshold methods”, Computers and Mathematics with Applications, 64(5), 1473-1483, September 2012. (paper link)

 

Peer-Reviewed Conference

          2023

  1. Epifano, J. R., Silvestri, A., Yu, A., Ramachandran, R. P., Tripathi, A., & Rasool, G. (2023, May). A Comparison of Feature Selection Techniques for First-day Mortality Prediction in the ICU. In 2023 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1-5). IEEE. (paper link)

           2022

  1. Carannante, G., Dera, D., Aminul, O., Bouaynaya, N. C., & Rasool, G. (2022, July). Self-Assessment and Robust Anomaly Detection with Bayesian Deep Learning. In 2022 25th International Conference on Information Fusion (FUSION) (pp. 1-8). IEEE. (paper link)

  2. Hikmat Khan, Nidhal Bouaynaya, and Ghulam Rasool, “Adversarially Robust Continual Learning”, accepted for publication in the International Joint Conference on Neural Network (IJCNN) 2022, Padua, Italy, July 18-23. (paper link)

           2021

  1. Yassine Barhoumi, Ghulam Rasool, “Scopeformer: n-CNN-ViT hybrid model for Intracranial hemorrhage subtypes classification”, 2021 Medical Imaging with Deep Learning conference (MIDL). (paper link)

  2. Shamoon Siddiqui, Ghulam Rasool, Ravi Ramachandran, “The Case Against Sentiment Analysis for Natural Text”, 2021 International Joint Conference on Neural Networks (IJCNN), 2021. (paper link)

  3. Specht, D. S., Waqas, A., Rasool, G., Clifford, C., & Bouaynaya, N. (2021). Intelligent Helipad Detection and (Grad-Cam) Estimation Using Satellite Imagery (No. TRBAM-21-01973).

    2020

  4. Giuseppina Carannante, Dimah Dera, Ghulam Rasool, and Nidhal Bouaynaya, “Self-Compression in Bayesian Neural Networks”, IEEE International Workshop on Machine Learning for Signal Processing (MLSP), Sep 21-24, 2020, Espoo, Finland. (paper link)

  5. Giuseppina Carannante, Dimah Dera, Ghulam Rasool, Nidhal Bouaynaya, and Lyudmila Mihaylova, “Robust Learning via Ensemble Density Propagation in Deep Neural Networks”, IEEE International Workshop on Machine Learning for Signal Processing (MLSP), Sep 21-24, 2020, Espoo, Finland. (paper link)

  6. Shamoon Siddiqui, Ghulam Rasool, Ravi Ramachandran and Nidhal Bouaynaya, “Evaluating Speech Enhancement Methods through Deep Speech Recognition”, IEEE International Joint Conference on Neural Networks (IJCNN), Jul 19-24, 2020, Glasgow, Scotland, United Kingdom. (paper link)

  7. Stephen Kovarik, Liam Doherty, Kiran Korah, Brian Mulligan, Ghulam Rasool, Yusuf Mehta, Parth Bhavsar and Mike Paglione, “Comparative Analysis of Machine Learning and Statistical Methods for Aircraft Phase of Flight Prediction”, 9th International Conference on Research in Air Transportation (ICRAT ’20), Sep 15, 2020, Virtual. (paper link)

  8. Dimah Dera, Ghulam Rasool, and Nidhal Bouaynaya, “Bayes-SAR Net: Robust SAR Image Classification with Uncertainty Estimation Using Bayesian Convolutional Neural Network”, in IEEE International Radar Conference 2020, April 27 - May 1, 2020, Washington DC, USA. (paper link)

    2019

  9. [Best Student Paper Award – First Position] Dimah Dera, Ghulam Rasool, and Nidhal Bouaynaya, “Extended Variational Inference for Propagating Uncertainty in Convolutional Neural Networks”, IEEE International Workshop on Machine Learning for Signals Processing (MLSP), Oct 13-16, 2019, Pittsburgh, PA, USA. (paper link)

  10. Hikmat Khan, Ghulam Rasool, Nidhal C. Bouaynaya, Charles C. Johnson, “Explainable AI: Rotorcraft Attitude Prediction”, Vertical Flight Society Forum 76 Proceedings, Oct 5-8, Virtual. (paper link)

  11. Eric Feuerstein, Ramachandran Ravi, Ghulam Rasool, Nidhal C. Bouaynaya, Charles C. Johnson, “Artificial Intelligence for Helicopter Safety: Head-Pose Detection in the Cockpit”, Vertical Flight Society Forum 76 Proceedings, Oct 5-8, Virtual. (paper link)

  12. Hikmat Khan, Ghulam Rasool, Nidhal C. Bouaynaya, Charles C. Johnson, “Rotorcraft Flight Information Inference from Cockpit Videos using Deep Learning”, Vertical Flight Society Forum 75 Proceedings, Philadelphia, PA, USA May 13-16, 2019. (paper link)

    2018 and earlier

  13. Nesrine Amor, Ghulam Rasool, Nidhal Bouaynaya, Roman Shterenberg, “Hand Movement Discrimination Using Particle Filters”, in 2018 IEEE Signal Processing in Medicine and Biology Symposium, Philadelphia, PA, USA, 1 December 2018. (paper link)

  14. Ghulam Rasool, Allison Wang, William Zev Rymer, Sabrina Lee, “Altered Viscoelastic Properties of Stroke-Affected Muscles Estimated Using Ultrasound Shear Waves – Preliminary Data”, in 38th Annual International IEEE EMBS Conference, Orlando USA, 16-20 August 2016. (paper link)

  15. Babak Afsharipour, Milap Sandhu, Ghulam Rasool, and William Z. Rymer, “Using surface electromyography to detect changes in innervation zones pattern after human cervical spinal cord injury”, in 38th Annual International IEEE EMBS Conference, Orlando USA, 16-20 August 2016. (paper link)

  16. Babak Afsharipour, Milap Sandhu, Ghulam Rasool, and William Z. Rymer, “Identifying Spinal Lesion Site from Surface EMG Grid Recordings”, Converging Clinical and Engineering Research on Neurorehabilitation Springer International Publishing, 2017, pp 39-43. (paper link)

  17. Ghulam Rasool, Babak Afsharipour, Nina L. Suresh and William Zev Rymer, “Spatial Analysis of Muscular Activations in Stroke Survivors”, in 37th Annual International IEEE EMBS Conference, Milan Italy, 25-29 August 2015. (paper link)

  18. Ghulam Rasool, Kamran Iqbal, Nidhal Bouaynaya and Gannon White, “Neural drive estimation using the hypothesis of muscle synergies and the state-constrained Kalman filter”, in 6th IEEE EMBS Neural Engineering Conference, San Diego, 6-8 November 2013. (paper link)

  19. Ghulam Rasool, Nidhal Bouaynaya, Kamran Iqbal, “Muscle Activity Detection from the EMG signal based on the AR-GARCH Method”, inIEEE Statistical Signal Processing Workshop (SSP), Ann Arbor, August 5-8, 2012. (paper link)

  20. Ghulam Rasool, Nidhal Bouaynaya, “Inference of Time-Varying Gene Networks using Constrained and Smoothed Kalman Filtering,” in IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS), Washington, DC, Dec 2-4, 2012. (paper link)

  21. Ghulam Rasool, Nidhal Bouaynaya, Hassan Fathallah-Shaykh and Dan Schonfeld, "Inference of Genetic Regulatory Networks Using Regularized Likelihood with Covariance Estimation," inIEEE Statistical Signal Processing Workshop (SSP), Ann Arbor, Aug 5-8, 2012. (paper link)

  22. Ghulam Rasool and Kamran Iqbal, “Muscle Activity Onset Detection Using Energy Detectors”, in 34th Annual International IEEE EMBS Conference, San Diego, USA, Aug 28 – Sep 1, 2012. (paper link)

  23. Ghulam Rasool, Asif Mahmood Mughal, and Kamran Iqbal “Fuzzy Biomechanical Sit-To-Stand Movement with Physiological Feedback Latencies”, IEEE International Conference on System, Man and Cybernetics (SMC) 2010, pp 316-321, Istanbul, Turkey, Oct 10-13, 2010. (paper link)

  24. Ghulam Rasool, Hamza Farooq and Asif Mahmood Mughal, “Biomechanical Sit-To-Stand Movement with Physiological Feedback Latencies”, in 2nd International Conference on Mechanical and Electronics Engineering (ICMEE), Aug 1-3, 2010, pp V1-159-V1-163, Kyoto, Japan. (paper link)

 

Non-Peer Reviewed Publications

  1. Cahall, D. E., Ghulam Rasool, Bouaynaya, N. C., & Fathallah-Shaykh, H. M. (2021). Dilated Inception U-Net (DIU-Net) for Brain Tumor Segmentation. arXiv preprint arXiv:2108.06772. (paper link)

  2. Amor, Nesrine, Ghulam Rasool, and Nidhal C. Bouaynaya. "Constrained state estimation-a review." arXiv preprint arXiv:1807.03463 (2018). (paper link)

 

Book Chapters

  1. Asim Waqas, Dimah Dera, Ghulam Rasool, Nidhal Bouaynaya, and Hassan M. Fathallah-Shaykh, “Brain Tumor Segmentation and Surveillance with Deep Artificial Neural Networks”, In: Elloumi M. (eds) Deep Learning for Biomedical Data Analysis. Springer, Cham, 2021. (paper link)

Posters

(link)

  1. Asim Waqas, Aakash Tripathi, Ashwin Mukund, Paul Stewart, Mia Naeini, Ghulam Rasool. “Hierarchical Multimodal Learning on Pan-Squamous Cell Carcinomas for Improved Survival Outcomes.” USF AI+X Symposium, 29 September 2023.

  2. Asim Waqas and Stewart, P and Farooq, H and Rasool, G. “Integrative Relational Learning on Multimodal Cancer Data for Improved Clinical Predictions.” The 19th Annual Conference for the Mid-South Computational Biology and Bioinformatics Society MCBIOS 202. campus of University of Dallas with the theme of "Big Data and Artificial Intelligence for Genomics and Therapeutics" from March 15-17, 2023.

  3. Sabeen Ahmed, Nathan Parker, Ghulam Rasool. "Early diagnosis of Cancer Cachexia using Body Composition Index as the Radiographic Biomarker", GTC, 2024.

Patents

  1. Method for Uncertainty Estimation in Deep Neural Networks, Hassan Fathallah-Shaykh, Nidhal Bouaynaya, Ghulam Rasool, and Dimah Dera, International Patent Application No: PCT/US2020/053441, filed on September 30, 2020. (link)