Steve Mei

About Steve Mei

Healthcare IT leader with 10+ years of experience driving transformative data-driven solutions across the healthcare ecosystem (provider, payer, and public health) and the technology sector. I specialize in leveraging data science and advanced analytics to solve complex challenges and capitalize on opportunities in value-based care, R&D innovation, and enterprise-wide digital transformation. My core expertise spans:Biomedical Data Science & Informatics: Harnessing data to advance precision medicine and improve patient outcomes.AI & Machine Learning: Developing and deploying cutting-edge AI tools (e.g, for mental health) to enhance clinical decision-making and operational efficiency. Genomics & Clinical Pharmacology: Applying data analytics to accelerate drug discovery, optimize therapies, and support regulatory submissions (e.g, FDA approvals). Health IT & Interoperability: Architecting and implementing robust IT infrastructures and data exchange solutions (e.g, EHR migrations, HIE) to enable seamless data sharing and improve care coordination. Strategic Leadership & Program Management: Leading cross-functional teams and managing large-scale initiatives (e.g,$400M federal cloud migration,$200M telemedicine data migration) to achieve strategic objectives and deliver tangible results. I am passionate about pioneering the use of data science to revolutionize healthcare, improve patient lives, and drive sustainable innovation. As a strategic and visionary leader, I am dedicated to fostering a culture of excellence and delivering impactful solutions that shape the future of healthcare.

Experience

1. Healthcare Digital Strategy Partner

   HIMSS

   Jan 2025 — Present

Education

• Stanford University

  Machine Learning and Statistics

• Massachusetts Institute of Technology

  Biostatistics and Computer Science

• Coursera

  DeepLearning.AI TensorFlow Developer

  2021

• Coursera

  AI for Medicine

  2021

• University of Chicago

  Master’s Degree - discontinued PhD, Bioinformatics, genomics, and genetics

• University of California, San Francisco

  Deep Learning (Applied Machine Learning)

• Columbia University

  Statistics

• Northwestern University - Kellogg School of Management

  Leading with Analytics and Artificial Intelligence

• The University of Hong Kong

  MBBS