School of Medicine


Showing 1-5 of 5 Results

  • Behzad Naderalvojoud

    Behzad Naderalvojoud

    Postdoctoral Scholar, Biomedical Informatics

    BioBehzad Naderalvojoud is a Postdoctoral Research Fellow at Stanford Center for Biomedical Informatics Research. He received his Ph.D. degree in Computer Science at Hacettepe University, Turkey, in 2020. He is immersed in the fields of machine learning, deep learning, natural language understanding, and Big data analytics and works on health knowledge discovery platforms that transfer Big Health data from volume-based to value-based by generating relational knowledge leading to innovative treatments, predictive therapeutic outcomes, and early diagnosis. He was the leader of many industrial AI projects in the fields of healthcare intelligence and information management in the Eureka cluster programs.

    Dr. Naderalvojoud has published several papers in the field of natural language understanding by working on word sense disambiguation, sentiment analysis, neural word embeddings, and deep learning models through national and international projects.

    He is currently working on the funded NLM grant project "Advancing Knowledge Discovery for Postoperative Pain Management" under the supervision of Dr. Tina Hernandez-Boussard. He develops descriptive, predictive, and analytical tools using OMOP CDM for postoperative pain research to facilitate timely generation of evidence across multiple populations and settings.

  • Madelena Ng

    Madelena Ng

    Postdoctoral Scholar, Biomedical Informatics

    BioMadelena is a postdoctoral scholar at the Stanford Center for Biomedical Informatics Research (BMIR). Her research aims to illuminate the evolving ethical and practical challenges among digital and emerging technologies (e.g., web- and app-based population health research, clinical AI solutions, blockchain for health data). Her work in the Boussard Lab focuses on discerning key factors for clinical AI solutions to flourish in practice—from the readiness of the datasets for machine learning research to the operational principles that are required for successful clinical deployment.