Now Accepting Applications for 2023 Lyman Fellowship

26 Oct, 2022

Now Accepting Applications for 2023 Lyman Fellowship

The Peter Lyman Graduate Fellowship in new media, established in the memory of esteemed UC Berkeley Professor Peter Lyman, provides a stipend to a UC Berkeley Ph.D. candidate to support the writing of his or her Ph.D. dissertation on a topic related to new media. The fellowship is supported by donations from Professor Barrie Thorne, Sage Publications and many individual friends and faculty.

Applications for summer 2023 are now open. To apply for the Lyman Fellowship, please fill in this form by February 1, 2023.

Some preference will be given to those doing research related to children and youth, to BCNM Designated Emphasis students, and to projects that focus on women, BIPOC, LGBTQ+, Global South, ability diverse, and socioeconomically disadvantaged peoples as makers and users of new media. If relevant, please explain how your project foregrounds one or more of these communities. Originality and quality of research are, however, the primary criteria.

The amount of the stipend depends on the size of the fund. In 2022 the fellowship amount was $6,000.00.

You must be a UC Berkeley Ph.D. student who has passed their qualifying exams to apply.

Previous fellows include Julia Irwin. In light of the U.S. military’s twenty-first-century embrace of pattern recognition techniques for automating image interpretation and targeting procedures, Julia examines how pattern recognition became the dominant mode of optical perception in institutional settings. It inquires into the conditions that enabled human sight to be conceived as an automatable entity and the politics inherent in the process of translating perceptual experience into a machine-readable and -executable format. Taking cues from the field of computer vision today, Julia identifies three modalities of vision—proprioceptive sensing, object detection, and behavior pattern recognition—and historicizes each. The objects of study are twentieth-century industrial, military, and academic programs for training human visual perception for institutional purposes that have, implicitly and explicitly, informed the design and deployment of today’s software. A methodological and critical intervention into contemporary discourse on computer vision bias, which emphasizes algorithms’ simultaneous black-boxed and agential nature, Julia’s conceptual and media history demonstrates the ways in which the mechanisms of pattern recognition are present in proto-algorithmic form in these earlier instances of trained human vision. Studying them can render today’s opaque systems more legible.

Fore more information on their projects, and to see the complete list of Lyman Fellows, check out our Lyman Fellowship page.

Questions? Email lara [​at​]