معرفی
Noah Simon is an Associate Professor in the Department of Biostatistics at the University of Washington School of Public Health. His research focuses on high-dimensional statistical methods, machine learning, and their applications in biomedicine. He develops computational tools for genomic and clinical data analysis, including penalized regression techniques and adaptive clinical trial designs.
Education:
- B.A. Mathematics, Pomona College (2008)
- Ph.D. Statistics, Stanford University (2013), advised by Robert Tibshirani
Research Interests:
Dr. Simon specializes in high-dimensional estimation, algorithm optimization, and clinical trial methodology. His work addresses challenges in biomarker discovery, imaging-based diagnostics, and genomic data analysis. Key areas include sparse-group lasso regularization, adaptive enrichment designs for personalized medicine, and scalable computational methods for big data.
Grants & Funding:
- NIH Director's Early Independence Award ($250k/year, 2014–2019)
- Amazon and Google Cloud Computing Grants for biomarker research
Awards:
- Forbes 30 Under 30 in Science (2015)
- NSF Graduate Research Fellowship Honorable Mention (2010)
- Weiland Fellowship (2011–2013)
Advising:
He mentors PhD and MS students in biostatistical methodology and data science, with current advisees including Jean Feng, Brayan Ortiz, and Jeremy Roth. Notable collaborations include work on neural activity detection via calcium imaging (SCALPEL) and nonparametric variable importance assessment using neural networks.
Lab & Affiliations:
Based at the Hans Rosling Center for Population Health, his group develops open-source software (e.g., sgl, standGL) and contributes to biomedical data science initiatives at UW.
