Computational & Systems Immunology Seminar Series 2021-2022

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. Speakers are invited to share their insights into the state-of-the-art trends and their advice on navigating a systems immunology career.

Subscribe to the CSI Seminars email list to receive news and updates through the interface at https://mailman.stanford.edu/mailman/listinfo/csi-seminars.

Students can optionally register for credit in this attendance-based seminar: IMMUNOL 310: Seminars in Computational and Systems Immunology.

Seminars are on Tuesdays at 4:00 - 5:00 PM PDT in LKSC LK130 (no hybrid option available). Registration is not required.

The 7/29/22 seminar will be held via Zoom. Please register to receive an individual login link.

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

  • 6/21/22 Ryan Corces, PhD, Gladstone Institutes at UCSF, "Understanding the noncoding genome at single-cell resolution"

    Due to technical issues, no recording is available.
  • 6/28/22 X. Shirley Liu, PhD, Dana Farber Cancer Institute, "Integrating genomics and computation for cancer target and drug discovery"

    Recording available until 07/07/22 - SUNet ID required

  • 7/05/22
    No seminar scheduled
  • 7/12/22 Gabi Fragiadakis, PhD, UCSF, "Profiling human immune states using single-cell methods"
  • 7/19/22 Dorothy (Dori) Schafer, PhD, UMass Chan Medical School, "Innate immune mechanism-dependent regulation of brain circuits"
    [ZOOM WEBINAR] - Register here
  • 7/26/22 Fereshteh Jahaniani, PhD and Pete Kane, Stanford Research to the People, "Multi-omics data integration and machine learning for integrative cancer care and patient-centered approach: Precision Oncology when there are no more option"
  • 8/02/22 Kieran Campbell, PhD, University of Toronto, "Machine learning methods for the analysis of single-cell highly multiplexed imaging and transcriptomic data"
  • 8/09/22 Soumya Raychaudhuri, MD, PhDHarvard Medical School, Brigham and Women’s Hospital, Broad Institute of Harvard and MIT