Computational & Systems Immunology Seminar Series 2022-2023

Past CSI Seminar Series

Seminars & Events

Effective modeling, acquisition and mining of data have become crucial for solving important problems in immunology. This seminar series explores novel molecular and computational approaches to interrogating outstanding questions in immunology and related fields. 

This summer we are shifting the focus of the course from covering a breadth of computational approaches to going deep on an emerging topic or area of interest.

The topic this summer will focus on large language models (LLMs) and their use/potential in immunology.  The overarching goal is to have introduced some of the underlying principles of large language models and explore through student projects uses and applications in immunology. 

Summer session starts on June 26th and ends in mid Aug. The class  will meet on Tuesdays from 4:30-5:50 in LKSC130.  The course will be a mix of talks and hands-on work/projects with a fluid curriculum that will be informed by those choosing to attend or participate in the class.  

Lectures will cover an overview of large language models  (LLMs) and their potential uses in immunology, considerations when fine-tuning or adapting LLMs, evaluating LLMs and learnings/considerations from the application of llms in other clinical and pharmaceutical settings.

Stay informed by subscribing to the CSI Seminars email list through the interface at https://mailman.stanford.edu/mailman/listinfo/csi-seminars.

Students can register for credit: IMMUNOL 310: Seminars in Computational and Systems Immunology.

Teaching team: Nikesh Kotecha, Ananth Ganesan, Daniel Goncharov, and Purvesh Khatri.

The class will meet on Tuesdays at 4:30 - 5:50 PM PDT in LKSC 130 (no hybrid option available).  You don’t need to register for the class but we encourage you to participate in the hands on work if you plan to attend.

On 7/25 - we'll have Tao Tu and Vivek Natarajan from Google to talk about Foundation Models for Biomedicine.

Recordings may be available up to 7 days post event with SUNet ID log in.