Max Benabou

Technical Solutions Engineer @ Epic | Stanford ‘25

Martinez, California, United States

About

Hi! I'm a recent graduate of Stanford University working as a Technical Solutions Engineer at Epic Systems. There, I help healthcare organizations maximize their use of their electronic health record in order to improve patient outcomes and provider satisfaction. I first developed an interest in engineering as I explored neuroscience and medicine in college; wanting to learn the tools to make an impact in these fields, I pursued a B.S. in Biomedical Computation (a mix of CS and Bioengineering). Outside of the classroom, I led independent research projects and co-authored a paper on the neural circuitry of alcohol addiction, fostered a neuroscience community on campus as President of the Stanford Undergraduate Neuroscience Society, and advocated for patients' health as a Patient Navigator at Arbor Free Clinic. I'm always excited to connect with others who are also interested in the intersection of healthcare, neuroscience, and innovation. Feel free to reach out!

Experience

  • Technical Solutions Engineer at Epic
    Aug 2025 - Present · 11 mos

    Drive AI feature implementation, regulatory reporting, and technical troubleshooting on the ambulatory team for the EHRs of two large health systems. Engage in operational calls and support implementation as the model owner of Epic’s End of Life Care Index, which assists clinician decision-making for palliative care.

  • Undergraduate Researcher in Giardino Lab at Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine
    Jan 2022 - Jun 2025 · 3 yrs 6 mos

    Research the role of sex differences and neuropeptides in addictive behaviors and stress/reward responses using mice. For the summer of 2023, I was awarded a Bio-X Undergraduate Fellowship to do full-time research.

  • Bioengineering REU Summer Intern @ Brains in Silicon Lab at Stanford Department of Electrical Engineering
    Jun 2024 - Aug 2024 · 3 mos

    Coded a model of a sequence-selective neuronal dendrite that can undergo long-term potentiation and long-term depression given a set of sequence inputs to research the impact of dendritic learning on the ability for individual spines to correctly respond to sequence-selective inputs.

  • IntroSem Course Development Assistant (CDA) at Stanford University
    Sep 2022 - Dec 2022 · 4 mos

    Created practice questions for each lecture's content, provided office hours, and managed the course Canvas site for "The Neuroscience of Stress and Reward: Circuit Fundamentals of Emotional Arousal," a freshman introductory seminar.

  • RSL REU Summer Intern @ McNab Lab at Stanford Radiology
    Jun 2022 - Aug 2022 · 3 mos

    Worked with Dr. Erpeng Dai and Dr. Jennifer McNab to research efficacy differences in four brain co-registration algorithms (FLIRT, ANTs, BBRegister with an FSL initialization, and BBRegister with an SPM initialization) across three age groups (babies, adults, and elders). Outside of research, I learned about the radiology field through lectures on imaging modalities and new developments, lab visits, and faculty lunches.