Ben Glicksberg

About Ben Glicksberg

I lead a team that works directly at the nexus of health data science and machine learning leveraging various modalities of patient data to enable precision medicine at scale. We leverage a variety of multi-omic biomedical data, including: Electronic Health Records (EHR), clinical text, genomics, physiological waveforms, and images. We develop machine learning techniques to mine and effectively fuse these data for various tasks including predictive modeling, disease phenotyping, drug repurposing, and drug discovery. I am also interested in how we can transform messy real-world clinical data into robust evidence for regulatory decision-making.To promote generalizability of EHR work, I have developed open source software leveraging the OMOP common data model (romop.ucsf.edu, patientexplorer.ucsf.edu, & patientexplorer.cancergenetrust.com)Full publication list: & hl=enPersonal Github: https://github.com/BenGlicksberg/Prior Lab Guthub: https://github.com/Glicksberg-Lab/

Experience

1. Scientific Advisor

   Character Biosciences

   Feb 2025 — Present

Education

• Icahn School of Medicine at Mount Sinai

  Doctor of Philosophy (Ph.D.), Neurobiology and Neurosciences

  2012 — 2017

• Skidmore College

  BA, Neuroscience

  2006 — 2010

• University of California, San Francisco

  Post-doc, Clinical Informatics

  2017 — 2019

Skills

• Animal Models
• Research
• Neuroscience
• Western Blotting
• Electronic Medical Record (Emr)
• Biostatistics
• Lifesciences
• Bioinformatics
• Genetics
• Deep Learning
• Human Genetics
• Data Science
• Scientific Writing
• Pcr
• Health Informatics
• Irb
• Spss
• Life Sciences
• Machine Learning