Monae McPherson
Houston
Summary
Accomplished Clinical AI Research Scientist at Baylor St. Luke's Medical Center, specializing in machine learning and healthcare analytics. Secured $2.1M in NIH funding and developed a sepsis prediction model with an AUC of 0.92. Proven team leader with expertise in Python and a commitment to improving patient outcomes through innovative solutions.
Overview
8
8
years of professional experience
4
4
Certifications
Work History
Clinical AI Research Scientist & Attending Physician
Baylor St. Luke's Medical Center
Houston
06.2023 - Current
- Delivered internal medicine care to improve patient outcomes.
- Led AI research team developing diagnostic algorithms for early disease detection.
- Designed sepsis prediction model identifying cases 12 hours before onset (AUC 0.92).
- Secured $2.1M NIH research funding.
- Collaborated on EHR data structuring improvements.
- Mentored junior researchers and prepared scientific publications.
Internal Medicine
Johns Hopkins Hospital
Baltimore
08.2020 - 06.2023
- Managed complex inpatient and outpatient cases.
- Integrated predictive analytics into triage workflows.
- Reduced hospital readmissions by 18% through quality initiatives.
- Led resident research in clinical decision support systems.
Machine Learning Engineer
Google Health
Mountain View
06.2019 - 06.2020
- Developed deep learning models for radiographic image classification.
- Improved pulmonary nodule detection sensitivity by 14%.
- Built HIPAA-compliant cloud healthcare analytics pipelines.
- Collaborated with clinicians and engineers on AI health solutions.
Clinical Informatics Consultant
Mayo Clinic
Rochester
06.2018 - 06.2019
- Built predictive models for chronic disease management.
- Implemented NLP tools for physician note data extraction.
- Reduced manual chart review workload by 35%.
- Led cross-functional healthcare improvement initiatives.
Education
Ph.D. - Artificial Intelligence & Machine Learning in Healthcare
Johns Hopkins University
01.2023
Doctor of Medicine -
Harvard Medical School
01.2020
Bachelor of Science - Biomedical Engineering
Massachusetts Institute of Technology
Cambridge, Massachusetts01.2016
Skills
- Python and R
- Java and C
- SQL and data modeling
- TensorFlow and PyTorch
- Keras and Scikit-learn
- Pandas and NumPy
- Apache Spark and Hadoop
- AWS and Google Cloud Platform
- Microsoft Azure
- Epic EHR and Cerner
- HL7 and FHIR standards
- Machine learning
- Deep learning
- Healthcare analytics
- Project management
- Team leadership
- Critical thinking
Certifications And Licensure
- USMLE – All Steps Passed
- Board Certified in Internal Medicine
- Certified Professional in Healthcare Information and Management Systems (CPHIMS)
- HIPAA Compliance Certification
Accomplishments
American Medical Association (AMA),
Certification
United States Medical Licensing Examination (USMLE) – passed all steps
Affiliations
NIH R01 grant – AI for early sepsis detection, $2.1M
Medical Training - Residency
Internal Medicine, Johns Hopkins Hospital, Baltimore, MD (08/2020 – 06/2023): Oversaw the care of complex inpatient and outpatient populations, incorporated predictive analytics into triage processes to improve efficiency, spearheaded a quality improvement project that lowered hospital readmission rates by 15%, and served as the resident research lead focusing on clinical decision support systems.
Timeline
Clinical AI Research Scientist & Attending Physician
Baylor St. Luke's Medical Center
06.2023 - Current
Internal Medicine
Johns Hopkins Hospital
08.2020 - 06.2023
Machine Learning Engineer
Google Health
06.2019 - 06.2020
Clinical Informatics Consultant
Mayo Clinic
06.2018 - 06.2019
Ph.D. - Artificial Intelligence & Machine Learning in Healthcare
Johns Hopkins University
Doctor of Medicine -
Harvard Medical School
Bachelor of Science - Biomedical Engineering
Massachusetts Institute of Technology