Professor at Northeastern University, United States
Saeed Amal is an accomplished researcher in Artificial Intelligence (AI) with a strong focus on healthcare and precision medicine. Currently serving as an Assistant Research Professor at Northeastern University, his work integrates cutting-edge AI methodologies such as deep learning, machine learning, and generative AI to address complex challenges in healthcare. With extensive experience spanning academia and industry, Saeed’s contributions are shaping the future of personalized medicine and intelligent healthcare solutions.
Profile
ORCID
Education🎓
Saeed’s academic journey reflects his dedication to innovation and interdisciplinary learning. He earned his Ph.D. in Computer Science from Haifa University , where he conducted pioneering research on machine learning, information retrieval, and recommender systems. During his postdoctoral fellowships at Stanford University and Haifa University, he expanded his expertise in deep learning, natural language processing (NLP), and healthcare applications of AI. His educational background also includes a Master’s degree in Computer Science and a Bachelor’s degree in the same field from Technion – Israel Institute of Technology, graduating with honors.
Professional Experience💼
Saeed’s professional journey is marked by impactful roles across academia and industry . At Northeastern University, he leads research on precision medicine, leveraging AI to detect and prevent diseases. His industry tenure includes roles as a Data Scientist and Researcher at Cognitech Smart AI, Dynamic Yield, and General Motors, where he developed AI-driven solutions for healthcare, recommender systems, and NLP. Saeed also has experience as a software engineer at Attunity and AMDOCS, designing large-scale systems with a focus on quality and performance. These experiences underscore his ability to translate theoretical AI concepts into practical, scalable applications.
Research Interests🏥
Saeed’s research interests lie at the intersection of AI and healthcare . His work focuses on the use of AI for early disease detection, multi-modal data integration, and improving diagnostic accuracy. He specializes in deep learning, NLP, large language models (LLM), and image processing to create advanced systems for precision medicine. His vision is to revolutionize healthcare through technology, making diagnosis and treatment more efficient and accessible. Saeed also has significant interest in explainable AI and its application to improve the interpretability and trustworthiness of AI systems.
Awards and Recognitions🏆
Saeed has received several accolades for his contributions to AI and healthcare . He has been a keynote and plenary speaker at major international conferences, including the “3rd International Conference on AI, ML, Data Science, and Robotics” in Rome (2023) and the “Public Health and Healthcare Management Conference” in Dubai (2023). He also chairs special sessions, such as the “Artificial Intelligence and Multimodal Data for Improving Disease Care” at the International Conference on Medical and Health Sciences. These roles highlight his leadership and impact in the global AI community.
Publications📚
“Analysis and Visualization of Confounders and Treatment Pathways Leading to Amputation and Non-Amputation in Peripheral Artery Disease Patients Using Sankey Diagrams”
- Year: 2025-01-21
- DOI: 10.3390/biomedicines13020258
“Evaluating Neural Network Performance in Predicting Disease Status and Tissue Source of JC Polyomavirus from Patient Isolates Based on the Hypervariable Region of the Viral Genome”
- Year: 2024-12-25
- DOI: 10.3390/v17010012
“Artificial Intelligence and Digital Pathology for Histologic Growth Pattern Classification in Lung Adenocarcinoma”
- Year: 2024-11-25 (Preprint)
- DOI: 10.20944/preprints202411.1804.v1
“Digital Pathology and Ensemble Deep Learning for Kidney Cancer Diagnosis: Dartmouth Kidney Cancer Histology Dataset”
- Year: 2024-11-21 (Preprint)
- DOI: 10.20944/preprints202411.1615.v1
“Gastric Cancer Detection with Ensemble Learning on Digital Pathology: Use Case of Gastric Cancer on GasHisSDB Dataset”
- Year: 2024-08-12
- DOI: 10.3390/diagnostics14161746
“Segmenting Tumor Gleason Pattern Using Generative AI and Digital Pathology: Use Case of Prostate Cancer on MICCAI Dataset”
- Year: 2024-06-28 (Preprint)
- DOI: 10.20944/preprints202406.2019.v1
“Multi-Scale Digital Pathology Patch-Level Prostate Cancer Grading Using Deep Learning: Use Case Evaluation of DiagSet Dataset”
- Year: 2024-06-18
- DOI: 10.3390/bioengineering11060624
“Ensemble Deep Learning-Based Image Classification for Breast Cancer Subtype and Invasiveness Diagnosis from Whole Slide Image Histopathology”
- Year: 2024-06-14
- DOI: 10.3390/cancers16122222
“Enhancing Prostate Cancer Diagnosis with a Novel Artificial Intelligence-Based Web Application”
- Year: 2023-11-30
- DOI: 10.3390/cancers15235659
Conclusion🌟
Dr. Saeed Amal is a highly suitable candidate for the Research for Best Researcher Award. With a strong foundation in AI for healthcare, an impressive publication record, and a clear demonstration of leadership in the scientific community, he embodies the qualities of an outstanding researcher. Enhancing public engagement and focusing on broader societal impacts can further bolster his profile for such recognitions.