Anshul Tambay
Anshul Tambay is a Technical Program Manager with the UW Scientific Software Engineering Center (SSEC) at the eScience Institute. He aims to develop open-source infrastructure that bolsters research across a variety of disciplines.
Prior to joining SSEC, Anshul worked as a Data Analyst at Northwestern University’s Center for Neighborhood Engaged Research and Science, focusing on community violence intervention programs in Chicago. His other experience includes working in support at a tele-health software company and on a development study in Ethiopia, evaluating a mobile phone-based experience sampling method of measuring time use. Anshul received his B.A. in Economics and Mathematics from Grinnell College in Iowa.
Outside of work, Anshul enjoys pickup sports, reading longform journalism, and cooking. He is a passionate supporter of Bay Area sports and Leeds United and interested in learning more about statistical inference in sports.
![The speaker's profile picture](/media/avatars/Anshul_Tambay_eScience_headshot_o6euNI0.jpg)
Sessions
Generative AI systems built upon large language models (LLMs) have shown great promise as tools that enable people to access information through natural conversation. Scientists can benefit from the breakthroughs these systems enable to create advanced tools that will help accelerate their research outcomes. This tutorial will cover: (1) the basics of language models, (2) setting up the environment for using open source LLMs without the use of expensive compute resources needed for training or fine-tuning, (3) learning a technique like Retrieval-Augmented Generation (RAG) to optimize output of LLM, and (4) build a “production-ready” app to demonstrate how researchers could turn disparate knowledge bases into special purpose AI-powered tools. The right audience for our tutorial is scientists and research engineers who want to use LLMs for their work.