Rim Hur

About Rim Hur

Engineer and pharmacologist trained at UC Berkeley, Genentech, and UCSF. I work at the intersection of healthcare, data science, and clinical research, applying quantitative and machine-learning methods to improve treatment decisions and real-world outcomes.My work spans:• AI/ML and causal-inference projects (SuperLearner, TMLE) using UCSF EHR data• Machine-learning tools for antibiotic resistance and treatment timing• AI/ML-based clinical research at Kaiser Permanente• Deep-learning and PK/PD modeling from UCSF PhD training• Contributions to FDA-sponsored quantitative pharmacologyRecent Publications• Hur, Rim, and Robert Rushakoff. 2025.\"Machine Learning for Causal Inference in Hospital Diabetes Care: TMLE Analysis of Selection Bias in Diabetic Foot Infection Treatment—A Cautionary Tale\" Diabetology 6, no. https://doi.org/10.3390/diabetology61•••22• Hur, Rim, Stephine Golik, and Yifan She. 2024.\"Leveraging Large Data, Statistics, and Machine Learning to Predict the Emergence of Resistant E. coli Infections\" Pharmacy 12, no. https://doi.org/10.3390/pharmacy12••••53

Experience

1. Senior Engineer

   Innovative Consulting Inc (ICI)

   Aug 2015 — Present

   Provide Process Automation Engineering solutions as a consultant engineer. I combine my experience as an automation engineer and my clinical expertise to understand and complete large scale projects with scientists, engineers, and clinicians in the health care / pharmaceutical / biotech industry.

Education

• University of California, San Francisco

  M.S. Bioengineering (Machine Learning; PhD candidate) completed in 2019; PharmD completed in 2014.

• University of California, Berkeley

  M.S. Mechanical Engineering(Design/Controls/Dynamics; PhD Candidate); B.S. Materials Sci/Engineering

• University of California, Berkeley, Haas School of Business

  Master of Business Administration - MBA

• Cornell University

  B.S. not completed and transferred to UC Berkeley; Robert J. and Virginia P. Bauer Scholarship, Mechanical Engineering