Dr. Nadav Rappoport | Medical Informatics | Best Researcher Award

Ben-Gurion University of the Negev, Israel

Professional Profiles:

👨‍🎓 Bio Summary:

Dr. Nadav Rappoport is an Assistant Professor at Ben-Gurion University in the Department of Software and Information Systems. He is the head of the Big Biomedical Data Lab, where he leads research at the intersection of artificial intelligence (AI), machine learning, and healthcare. His work focuses on analyzing large-scale biomedical datasets to enhance healthcare systems and improve patient outcomes. With an impressive academic background and numerous high-impact publications, Dr. Rappoport is a recognized leader in the field of computational biology and medical informatics.

🎓 Educational Background:

Dr. Rappoport received his B.Sc. in Computational Biology from the Hebrew University of Jerusalem in 2009. He continued his studies at the same institution, earning a Ph.D. in Computer Science in 2015. Following his Ph.D., he pursued postdoctoral research in Medical Informatics at the University of California, San Francisco (UCSF) from 2015 to 2019, where he further specialized in AI applications for healthcare.

🔍 Research Focus:

Dr. Rappoport’s research centers on developing AI and machine learning algorithms for healthcare applications. His work has focused on improving diagnostic tools and personalized medicine by leveraging large biomedical datasets. Key achievements include developing models to predict protein functions, analyzing millions of health records to define population-specific reference ranges for lab tests, and identifying genetic markers associated with preterm birth. His interdisciplinary approach bridges computational techniques with real-world clinical challenges, advancing precision medicine and healthcare efficiency.

🏆 Honors & Awards:

Dr. Rappoport has received several grants and recognitions for his pioneering research. Notably, he secured significant funding from prestigious organizations such as the European Health Data & Evidence Network (EHDEN) and the Israeli Science Foundation. His research on kidney stone formation, funded with a $700,000 grant, exemplifies his expertise in tackling complex medical problems. He also received multiple awards for his innovative AI models applied to healthcare, further establishing his reputation in the academic community.

💼 Professional Experience:

Since 2019, Dr. Rappoport has been serving as an Assistant Professor at Ben-Gurion University, where he leads research in AI and big data applications in healthcare. Prior to this, he conducted postdoctoral research at UCSF’s Bakar Institute for Computational Health Sciences. His professional journey has been marked by a commitment to interdisciplinary collaboration, demonstrated by leading large-scale projects involving over 30 researchers from various fields.

📚 Top Noted Publications :

ProteinBERT: A Universal Deep-Learning Model of Protein Sequence and Function
Authors: N. Brandes, D. Ofer, Y. Peleg, N. Rappoport, M. Linial
Journal: Bioinformatics
Citations: 478
Year: 2022

An Expanded Evaluation of Protein Function Prediction Methods Shows an Improvement in Accuracy
Authors: Y. Jiang, T.R. Oron, W.T. Clark, A.R. Bankapur, D. D’Andrea, R. Lepore, …
Journal: Genome Biology
Citations: 425
Year: 2016

Single-Cell RNA-seq Reveals Cell Type–Specific Molecular and Genetic Associations to Lupus
Authors: R.K. Perez, M.G. Gordon, M. Subramaniam, M.C. Kim, G.C. Hartoularos, S. Targ, …
Journal: Science
Citations: 244
Year: 2022

Significantly Improved COVID-19 Outcomes in Countries with Higher BCG Vaccination Coverage: A Multivariable Analysis
Authors: D. Klinger, I. Blass, N. Rappoport, M. Linial
Journal: Vaccines
Citations: 99
Year: 2020

ProtoNet 6.0: Organizing 10 Million Protein Sequences in a Compact Hierarchical Family Tree
Authors: N. Rappoport, S. Karsenty, A. Stern, N. Linial, M. Linial
Journal: Nucleic Acids Research
Citations: 55
Year: 2012

Conclusion:

Dr. Nadav Rappoport is a highly suitable candidate for a Best Researcher Award due to his innovative use of AI and big data in healthcare, his leadership in collaborative projects, and his strong funding and publication track record. His work is cutting-edge and addresses significant issues in healthcare, including personalized medicine and disease prevention. Enhancing his international collaborations and public engagement would further strengthen his candidacy for such an award.