Dara Rouholiman

I am currently a ML research engineer at Stanford AIM Lab where I work with patients, doctors, and scientists to apply and evaluate generative and predictive models in anesthesia and perioperative medicine.

I previously helped develop an at-home health-monitoring hardware called COR and worked on helping the state of Connecticut allocate resources in addressing opioid overdose epidemic with a prediction model. My career started as a Clinical Research Associate at Stanford School of Medicine, where I ran studies evaluating digital health devices and tools and helped organize Medicine X in 2014 and 2015, and a day-long workshop at the White House in 2016.

Recent News

• 15 Mar 2025: 📄 LLMs’ clinical calculations evaluation paper published in Nature's npj digital med

  Our paper on large language models’ clinical calculations performance is published in Nature’s npj digital medicine! Our study showed how bad LLMs are at clinical calculations, so we had to build a set of task-specific clinical calculation tools and show how giving LLMs the task-specific tools–medical calculators–reduce their incorrect calculations to below 5% (from 64% without the tools).

• 05 Oct 2024: 📚 Lead Instructor, Stanford Technology in Healthcare Fall Internship

  Co-designed a four-session virtual curriculum of advanced, graduate-level seminars with hands-on lab sessions on Clinical Data Structures and Algorithms for interns.

• 04 Mar 2024: 🎤 Poster Presentation at World Congress of Anesthesiology 2024

  Presented our study on Open-Source Large Language Models in Anesthesia and Perioperative Medicine: ASA-Physical Status Evaluation. Our findings Underscore the significant potential of open-source Large Language Models like Mixtral in transforming anesthesia and perioperative medicine.