Hamed, Ahmed Abdeen

Ahmed Abdeen Hamed

Assistant Teaching Professor, Northeastern University & Head of Clinical Data Science/Network Medicine & AI at the Sano Centre for Computational Medicine and Personalized Healt

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CSDE Research Areas:

Demographic Measurements and Methods
Health of People and Populations

Over the past decade, Ahmed Abdeen Hamed has dedicated himself to academic training, cultivating a robust foundation that seamlessly integrates into both his academic and industrial pursuits in Data Science. His primary research objectives revolve around addressing intricate challenges in clinical data science and network medicine, deploying computational solutions to advance the understanding of complex diseases, such as cancer, from clinical, genetic, and pharmaceutical standpoints. Within the academic realm, his ambition extends beyond personal growth. He is committed to democratizing knowledge in problem-solving, machine learning, and artificial intelligence, not only for the local student community but also for scientists and professionals within my field. His journey has been marked by leadership in diverse research projects, particularly in the field of Biomedical literature mining. Notably, a project closely aligned with the proposed venture involved mining the Biomedical literature to uncover drug-disease links and algorithmically ranking their chemical molecules based on specificity. During his tenure as an R&D scientist in the pharmaceutical industry, he designed and implemented an algorithm, leading to academic publications and eventual patenting under US Patent 10,978,178 in 2021. This groundbreaking work laid the foundation for his subsequent endeavors in Drug Repurposing. The relevance of this research became glaringly evident with the onset of the global Covid-19 pandemic. While the world sought effective treatments for the novel Coronavirus, he delved into the Biomedical literature to identify potential drug options for Covid-19 treatment. The outcomes of this research materialized into seminal publications introducing computational medicine methods and algorithms for identifying repurposed drug combinations in Covid-19 treatment. Notably, some of these discovered combinations, now known as Paxlovid, were manufactured by Pfizer, underscoring the translation of research into tangible market solutions. Funded by the United States of America and the FNP, this research not only responded to a global crisis but also laid the groundwork for broader applications, extending into diseases like cancer and Alzheimer’s. Since November 2022, he has been closely observing the rise of Generative AI and its remarkable capabilities in answering questions, fact-checking, and detecting fake science. During this period, he has actively engaged in assessing the credibility of content generated by tools like ChatGPT and Google Bard. Additionally, his research has expanded into computational medicine, exploring how Generative AI can accelerate drug discovery for complex diseases such as cancer.