Stanford University
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Erik Limpitlaw
Digital Collections Licensing Librarian, Acquisitions Department
Current Role at StanfordMy primary responsibility of the Digital Collections Licensing Librarian is to review and negotiate e-resource licenses and related documents on behalf of Stanford University Libraries (SUL) with publishers, resource aggregators, data sources and other service providers. I primarily work on the negotiation of document terms but am often brought into pricing negotiations with vendors as well as work with vendors in creating terms which have not historically worked with academia.
I work to ensure that the terms of these agreements meet SUL and Stanford University’s policies and requirements, that their terms of use are consistent with the needs of Stanford faculty, students, and staff, and that the cost meets SUL’s funding capabilities and is the best available negotiated price.
I also recommend to Associate University Librarians (AUL) for Collections, the Deputy University Librarian and/or the University Librarian whether a proposed license is acceptable and whether there are any issues and risks to consider. I am currently reviewing distinguishing terms across licensing various e-resources such as datasets and streaming media and improving internal document and licensing workflows.
I also serve, as needed and as appropriate, on SUL committees or other groups addressing Stanford’s e-resource needs, planning, and evaluation. I also serve as the liaison for e-resource matters to the relevant counterparts in Stanford’s Coordinate Libraries (Crown Law, Lane Medical, and Graduate School of Business). -
Eric Lin
Clinical Assistant Professor (Affiliated), Psych/General Psychiatry and Psychology (Adult)
Staff, Psychiatry and Behavioral SciencesBioEric Lin, MD, is a Clinical Assistant Professor (Affiliated) of Psychiatry and Behavioral Sciences at Stanford University School of Medicine and an addiction psychiatrist at VA Palo Alto. His academic work focuses on artificial intelligence, large language models, machine learning, and psychiatry, with particular interest in the clinical evaluation, safety, and governance of AI systems used in mental health care and related psychological contexts.
Dr. Lin studies how AI systems should be assessed when they interact with patients, clinicians, or psychologically vulnerable users. His work addresses the limitations of benchmark-driven evaluation and the need for clinically meaningful approaches to AI evaluation that incorporate psychiatric expertise, real-world clinical complexity, and post-deployment risk. His broader interests include psychopathology, personality assessment, psychoanalytic and psychodynamic models of mind, and the translation of complex clinical judgment into rigorous evaluation frameworks for emerging technologies.
Dr. Lin completed psychiatry residency at Yale University, where he trained in the Neuroscience Research Training Program, and later completed a medical informatics fellowship through VA Boston, with research at Harvard Medical School/McLean Hospital on computational and digital approaches to psychiatric phenotyping. He is board certified in psychiatry and clinical informatics. His clinical and teaching work in addiction psychiatry grounds his interest in psychiatric complexity, risk assessment, care navigation, and pragmatic implementation of AI tools in health care. He is interested in collaborations across psychiatry, computer science, human-centered AI, health policy, digital mental health, and responsible technology development.
