Elana J Fertig, PhD, FAIMBE

Dr. Fertig advances a new predictive medicine paradigm for oncology by converging systems biology with translational technology development. Her computational cancer biology research is inspired by her background as a NASA fellow in weather prediction. She aims to invent computational techniques that use multi-platform high-throughput precancer and tumor datasets to forecast the cellular and molecular pathways of future cancer progression and therapeutic resistance. An authority in computational oncology, Dr. Fertig has been a leader in establishing spatial multi-omics technologies, matrix factorization, and transfer learning as current mainstays in bioinformatics. Her combined expertise in computational oncology, chaos theory, nonlinear dynamics, and tumor immunotherapy ensure translational relevance and mechanistic validation of computational findings. Beyond algorithm development, Dr. Fertig’s transdisciplinary expertise enables her to lead large-scale, team-science projects adapting cutting-edge molecular profiling technologies to human clinical trials to uncover new therapeutic interception pathways. Her transdisciplinary research has made her a sought after mentor and recognized leader of new training paradigms that converge oncologists, pathologists, basic biologists, computational investigators, and engineers to advance the next generation of computationally-driven oncology care.

Dr. Fertig is a Professor of Oncology and Division and Associate Cancer Center Director in Quantitative Sciences, Co-Director of the Convergence Institute, and Co-Director of the Single-Cell Training and Analysis Center at Johns Hopkins University. She has secondary appointments in Biomedical Engineering and Applied Mathematics and Statistics, affiliations in the AI-X Foundry, Institute of Computational Medicine, Center for Computational Genomics, Machine Learning, Mathematical Institute for Data Science, and the Center for Computational Biology and is a Daniel Nathans Scientific Innovator and MD Cancer Moonshot Senior Scholar. Prior to entering the field of computational cancer biology, Dr Fertig was a NASA research fellow in numerical weather prediction.

Dr. Fertig’s research is featured in over numerous peer-reviewed publications, R/Bioconductor packages, and competitive funding portfolio as PI and co-I. Notably, she led the team that won the HPN-DREAM8 algorithm to predict phospho-proteomic trajectories from therapeutic response in cancer cells and was elected to the College of Fellows American Institute for Medical and Biomedical Engineering (AIMBE) in 2022. She serves on the editorial boards of PLoS Computational Biology, Cell Systems, ImmunoInformatics, and Cancer Research Communications.