Update biography.md

Author: ejfertig

biography.md

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 ## 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 advances a new predictive medicine paradigm for oncology by converging systems biology with multi-omics 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 blend multi-platform high-throughput with mechanistic mathematical modeling and artificial intelligence methods to forecast the cellular and molecular pathways of tumor progression and therapeutic response over time. Her combined expertise in computational oncology, chaos theory, nonlinear dynamics, and tumor immunotherapy ensures translational relevance and mechanistic validation of computational findings. Dr. Fertig has been a leader in establishing spatial multi-omics technologies, matrix factorization, and transfer learning as current mainstays in bioinformatics. 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 biospecimen research and clinical trials to uncover new therapeutic interception pathways. Beyond the lab, she is a recognized leader in developing new training paradigms that converge oncologists, pathologists, basic biologists, computational investigators, and engineers to advance the next generation of computationally-driven cancer research.
 
-As of December, 2024 Dr. Fertig is the Director of the <a href="https://www.igs.umaryland.edu">Institute for Genome Sciences</a> and a Professor of Medicine in the Division of Oncology at University of Maryland, Baltimore. Previously, she was a Professor of Oncology and <a href="https://oncologyqs.jhmi.edu/about/" target="_blank">Division and Associate Cancer Center Director in Quantitative Sciences</a>, Co-Director of the <a href="https://convergence.jh.edu" target="_blank">Convergence Institute</a>, and Co-Director of the Single-Cell Training and Analysis Center at Johns Hopkins University where she had 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 was 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 as a graduate student in Applied Mathematics and Scientific Computation at University of Maryland, College Park.
+In December, 2024 Dr. Fertig was named the <a href="https://www.igs.umaryland.edu">Institute for Genome Sciences</a> and the Dean E. Albert Reece Endowed Professor in the School of Medicine at the University of Maryland School of Medicine and Associate Cancer Center Director of Quantitative Sciences at the University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center at the University of Maryland, Baltimore. Prior to joining the faculty of the University of Maryland, she was a Professor of Oncology and Division and Associate Cancer Center Director in Quantitative Sciences and Co-Director of the Convergence Institute at Johns Hopkins University. Prior to entering the field of computational cancer biology, Dr Fertig was a NASA research fellow in numerical weather prediction as a graduate student in Applied Mathematics and Scientific Computation at University of Maryland, College Park. Dr. Fertig’s research is featured in <a href="https://scholar.google.com/citations?user=nfCAUr8AAAAJ&hl=en&oi=ao">numerous peer-reviewed publications</a>, open-source software packages, and competitive funding portfolio as PI and co-I. She was elected to the College of Fellows American Institute for Medical and Biomedical Engineering (AIMBE) in 2022, serves on the editorial boards of Genome Medicine, Cell Systems, Clinical Cancer Research, and Cancer Research Communications, and as co-chair of the AACR Data Science Task Force.
 
 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 Genome Medicine, Cell Systems, ImmunoInformatics, and Cancer Research Communications.