School of Medicine


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  • Thomas Barba, MD, PhD

    Thomas Barba, MD, PhD

    Postdoctoral Scholar, Biomedical Informatics

    BioI am a postdoctoral scholar with a medical background in Internal Medicine and a degree in Immunology from the University of Lyon (France). As a practitioner in hospital medicine, I am mainly interested in rare autoimmune diseases such as systemic lupus erythematosus (SLE).

    My postdoctoral project in Prof Olivier Gevaert's laboratory aims at developing deep learning tools that take advantage of data fusion procedures to assist clinical decision-making in the management of complex diseases.

  • Ahmet Görkem Er

    Ahmet Görkem Er

    Graduate Visiting Researcher Student, Biomedical Informatics

    BioAhmet Görkem Er is a visiting student researcher as a Fulbright Ph.D. Dissertation Research Grantee at Stanford. He holds an M.D. degree with a double specialty of internal medicine and infectious diseases and clinical microbiology and is pursuing a Ph.D. in medical informatics at Middle East Technical University (Turkey). He is interested in machine learning approaches in healthcare and working on multi-scale data fusion and radiogenomics in Gevaert's Lab.

  • Sajjad Fouladvand, PhD, MSc

    Sajjad Fouladvand, PhD, MSc

    Postdoctoral Scholar, Biomedical Informatics

    BioSajjad Fouladvand, PhD, MSc is a postdoctoral scholar at Stanford Center for Biomedical Informatics Research. Dr. Fouladvand's research career thus far has been focused on developing and applying artificial intelligence (AI) algorithms to solve real-world healthcare problems. Prior to Stanford, he worked at the Institute for Biomedical Informatics at the University of Kentucky (UK) while completing his PhD in Computer Science. During this time, he also received training at Mayo Clinic’s Department of Artificial Intelligence and Informatics as an intern.

    While at UK as a PhD candidate, he developed a deep learning model based on transformer and Long Short-Term Memory (LSTM) models to analyze multi-stream healthcare data for prediction of opioid use disorder (OUD). While at Mayo Clinic as an intern, he created a LSTM based framework to predict progression from cognitively unimpaired to mild cognitive impairment in an aging population. In his new role at Stanford, Dr. Fouladvand is involved in conducting AI and healthcare data science research in close collaboration with clinicians, scientists, and healthcare systems with access to deep clinical data warehouses and broad population health data sources.

  • Zepeng Huo

    Zepeng Huo

    Postdoctoral Scholar, Biomedical Informatics

    BioConducting research on Foundation Models for medicine

  • 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.