Saeed Amal
Assistant Research Professor,
Bioengineering
Research Focus
Artificial Intelligent including Deep Learning and Machine Learning for Healthcare, Natural Language Processing (NLP) and Image Processing for Healthcare, Recommender Systems for Healthcare
About
Saeed Amal is an Assistant Research Professor at Northeastern University. Amal was a Postdoctoral Fellow at the Stanford University School of Medicine where he focused on the applications of artificial intelligence to improve healthcare, specifically care for cardiovascular disease. He received his PhD and MSc degree in Computer Science from the University of Haifa and a BSc degree in Computer Science from Technion.
Amal has vast leadership experience in applied research from the tech industry and is a former VP of an R&D data medical startup in the field of cardiology. His research interests are the healthcare applications for artificial intelligence, including deep learning and machine learning, natural language processing (NLP), image processing, and recommender systems.
Research Overview
Artificial Intelligent including Deep Learning and Machine Learning for Healthcare, Natural Language Processing (NLP) and Image Processing for Healthcare, Recommender Systems for Healthcare
Department Research Areas
Selected Publications
- Co-first author on – Ghanzouri, I., Amal, S., Ho, V., Safarnejad, L., Cabot, J., Brown-Johnson, C. G., … & Ross, E. G. (2022). Performance and usability testing of an automated tool for detection of peripheral artery disease using electronic health records. Scientific reports, 12(1), 1-11.
- Amal, S., Safarnejad, L., Omiye, J. A., Ghanzouri, I., Cabot, J. H., & Ross, E. G. (2022). Use of Multi-Modal Data and Machine Learning to Improve Cardiovascular Disease Care. Frontiers in Cardiovascular Medicine, 9.
- Amal, S., Minkov, E., & Kuflik, T. (2021). Person Entity Profiling Framework: Identifying, Integrating and Visualizing Online Freely Available Entity-Related Information. arXiv e-prints, arXiv-2110.
- Amal, S., Adam, M., Brusilovsky, P., Minkov, E., & Kuflik, T. (2020, September). Personalized Multifaceted Visualization of Scholars Profiles. In Proceedings of the International Conference on Advanced Visual Interfaces (pp. 1-3).
- Amal, S., Adam, M., Brusilovsky, P., Minkov, E., Segal, Z., & Kuflik, T. (2020, July). Visualizing Personalized Multifaceted ad-hoc Social Network. In Adjunct Publication of the 28th ACM Conference on User Modeling, Adaptation and Personalization (pp. 101-102).
- Amal, S., Adam, M., Brusilovsky, P., Minkov, E., Segal, Z., & Kuflik, T. V. (2020, March). Demonstrating personalized multifaceted visualization of people recommendation to conference participants. In Proceedings of the 25th International Conference on Intelligent User Interfaces Companion (pp. 49-50).
- Amal, S., Tsai, C. H., Brusilovsky, P., Kuflik, T., & Minkov, E. (2019). Relational social recommendation: Application to the academic domain. Expert Systems with Applications, 124, 182-195.
- Amal, S., Adam, M., Brusilovsky, P., Minkov, E., & Kuflik, T. (2019, March). Enhancing explainability of social recommendation using 2D graphs and word cloud visualizations. In Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion (pp. 21-22).
- Amal, S., KuFlik, T., & Minkov, E. (2017, July). Harvesting entity-relation social networks from the web: Potential and challenges. In Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization (pp. 351-352).