When: Friday, November 7, 3:00 PM
\nWhere: Tyler 055<\/p>\n
Abstract:<\/strong> The framework can integrate seamlessly with university research computing infrastructure, allowing researchers, faculty, and students to create and deploy their own RAG-based AI tools while maintaining full control over data privacy and compliance. It combines a curated repository of open-source components (such as vector databases, model interfaces, and authentication modules) with a standardized architecture that accelerates deployment and reduces technical barriers.<\/p>\n Bio:<\/strong> At BU, Tomlinson leads a multidisciplinary engineering team advancing research-driven innovation through production-grade software solutions, open-source frameworks, and scalable AI infrastructure. Previously, he served as Principal Engineer and Group Leader for the Embedded & Communication Systems Group at Draper Laboratory, where he directed multimillion-dollar programs in wireless communications and mission-critical systems. He earned his Ph.D. in Computer Engineering from Northeastern University, an M.S. in Electrical Engineering from Michigan State University, and a B.S. in Electrical Engineering from North Carolina A&T State University.<\/p>\n","protected":false},"excerpt":{"rendered":" When: Friday, November 7, 3:00 PM Where: Tyler 055 Abstract: This presentation introduces Boston University\u2019s Retrieval-Augmented Generation (RAG) Framework, an open-source, low-code platform developed by the Software & Application Innovation Lab (SAIL) to make large language model (LLM)\u2013powered applications accessible, reproducible, and secure across academic environments. The framework can integrate seamlessly with university research computing […]<\/p>\n","protected":false},"author":3300,"featured_media":18082,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[34,85],"tags":[],"class_list":["post-18080","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","category-seminars"],"acf":[],"_links":{"self":[{"href":"https:\/\/web.uri.edu\/cs\/wp-json\/wp\/v2\/posts\/18080","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/web.uri.edu\/cs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/web.uri.edu\/cs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/cs\/wp-json\/wp\/v2\/users\/3300"}],"replies":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/cs\/wp-json\/wp\/v2\/comments?post=18080"}],"version-history":[{"count":3,"href":"https:\/\/web.uri.edu\/cs\/wp-json\/wp\/v2\/posts\/18080\/revisions"}],"predecessor-version":[{"id":18084,"href":"https:\/\/web.uri.edu\/cs\/wp-json\/wp\/v2\/posts\/18080\/revisions\/18084"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/cs\/wp-json\/wp\/v2\/media\/18082"}],"wp:attachment":[{"href":"https:\/\/web.uri.edu\/cs\/wp-json\/wp\/v2\/media?parent=18080"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/web.uri.edu\/cs\/wp-json\/wp\/v2\/categories?post=18080"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/web.uri.edu\/cs\/wp-json\/wp\/v2\/tags?post=18080"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\nThis presentation introduces Boston University\u2019s Retrieval-Augmented Generation (RAG) Framework, an open-source, low-code platform developed by the Software & Application Innovation Lab (SAIL) to make large language model (LLM)\u2013powered applications accessible, reproducible, and secure across academic environments.<\/p>\n
\nWilliam J. Tomlinson, Ph.D., is the Director of the Software & Application Innovation Lab (SAIL) at Boston University\u2019s Rafik B. Hariri Institute for Computing and Computational Science & Engineering. A visionary technology executive and servant leader, Dr. Tomlinson brings over a decade of experience in software, hardware, and AI-integrated systems development.<\/p>\n