Upcoming Events

Webinar Series

Upcoming

  • April 27, 2023, 1-2:30pm Eastern Time: Qiqi Deng, "A Brief introduction for drug development and how biostatistician can contribute".  Registration Link

Archive

  • October 27th,, 2021, 1-2:30pm Eastern Time: Nesime Tatbul, Topic: anomaly detection with time series data
  • August 24th, 2021, 2-3:30pm Eastern Time: Jean Feng, Topic: Deep Learning
  • September, 28th, 2021, 1-2:30pm Eastern Time:  Byron Jaeger, Topic: Github
  • June 23, 2021, 1-2:30pm Eastern Time: Andreas Ziegler (video), Topic: Calibration in Machine Learning. (Passcode: Ja646%VA)      
  • May 25, 2021, 1-2:30pm Eastern Time: Polo Chau (Video), Topic: Interpretable AI
  • April 29, 2021, 2-3:30pm Eastern Time: Brian Lee Yung Rowe (Video), Topic: Automation and Reproducibility. 
  • March 31, 2021. 2-3:30PM Eastern time: Naomi Brownstein (Video), Topic: Clustering and Clusterability. 
  • February 25th 2021, 2-3:30pm Eastern Time: Beth Wolf (Video):   Topic: Variable Importance in ML. 
    • January 2021 webinar, Dr. Helen Zhang (Video), Topic: Data Science teams. 

    JSM 2020 [Now Virtual]

    JSM 2020 will include paper sessions, poster sessions, and round tables.
    It will also include the SLDS annual business meeting.
    Conference website: https://ww2.amstat.org/meetings/jsm/2020/
    The conference was previously planned to be held in Philadelphia, Pennsylvania  (August 1-6). It will now be a virtual conference with details TBA.

    SLDS 2020 [Cancelled]

    Date: May-June 2020
    Conference Website: https://asaslds.github.io/SLDS2020/

    Past Events

    StatFest 2019 (Houston, TX)

    Location: University of Texas Health Science Center at Houston
    Date: September 21
    Register: https://community.amstat.org/cmis/events/statfest/statfest-2019

    JSM 2019 - SLDS Section Business Meeting

    (details forthcoming)

    2nd Midwest Statistical Machine Learning Colloquium (May 13th, 2019) at Iowa State University

    Filtering On: Community


    There are no events currently scheduled for Statistical Learning and Data Science Section