School of Medicine


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  • Alison Callahan

    Alison Callahan

    Postdoctoral Research fellow, Biomedical Informatics

    Bio Alison Callahan is a postdoctoral scholar at the Stanford Center for Biomedical Informatics and a member of the Shah Lab. Her research involves developing and applying informatics methods that enable translational discoveries in biomedicine.

    Her research projects include RegenBase, a collaboration with the Miami Project to Cure Paralysis and Department of Computer Science at the University of Miami. RegenBase uses semantic technologies to aggregate and analyze experimental data in spinal cord injury research.

    Alison completed her PhD in the Department of Biology at Carleton University in Ottawa, Canada. Her doctoral research focused on developing HyQue, a framework for representing and evaluating scientific hypotheses, and applying this framework to discover genes related to aging. She was also a developer for Bio2RDF, an open-source project to build and provide the largest network of Linked Data for the life sciences.

  • Yen Sia Low

    Yen Sia Low

    Postdoctoral Research fellow, Biomedical Informatics

    Bio I use machine learning methods, guided by epidemiological study designs, to study disease patterns and patient outcomes from electronic health records (including text) and administrative claims data. Research interests: propensity score matching, patient similarity, adverse drug reactions

  • Maryam Panahiazar

    Maryam Panahiazar

    Postdoctoral Research fellow, Biomedical Informatics

    Bio Dr. Maryam Panahiazar (Mary) was a Postdoctoral Research Associate in Medical Informatics group at the Mayo Clinic College of Medicine. During her appointment at Mayo Clinic she was working on personalized and translational medicine using machine learning and semantic web technology for clinical decision making, response therapy and recommendation engines. She has several years of research experience in machine learning, data mining, biomedical knowledge representation, semantic web and ontology development. She has been a key member in NIH R01 grant on semantics and services enabled problem solving environment, which have pioneered techniques for semantic web in life sciences. Mary ?s research interest and expertise lies in applying informatics in healthcare and life sciences. She participated in the NIH training program where she worked on semantic similarity and data integration for NLM resources. She also was Research Associate at kno.e.sis center where she worked on data integration, ontology development, semantic annotation and question answering system. She contributed as program committee members of several conferences and reviewer for many journals and conferences.

  • Suzanne Tamang

    Suzanne Tamang

    Postdoctoral Research fellow, Biomedical Informatics

    Bio Suzanne Tamang is a Postdoctoral Scholar and National Library of Medicine Fellow at Stanford University, where she is part of the Center for Biomedical Informatics Research and a member of the Shah Lab. Her work focuses on the development and dissemination of methods to mine digital health data for health system improvement. At Stanford, she collaborates on projects with the Clinical Excellence Research Center, the Stanford Cancer Institute, Stats for Good, and with the Department of Clinical Epidemiology at Aarhaus University in Denmark.

    Suzanne received a Ph.D. in Computer Science from the City University of New York. Her thesis was on unsupervised learning methods for modeling chronic diseases dynamics. As a graduate student, she received a NSF fellowship, the Earnest Malve Student Leadership Award, and was a Provost?s Digital Innovation Grant recipient. She has developed top ranking system submissions for NIST sponsored challenges on automated knowledge base population, and her research has been published at various health, medical and computer science conferences including ASCO, KDD, ICML, AAAI, NAACL, SIGIR, Academy Health and APHA.

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