Summer Institute in Statistics and Modeling in Infectious Diseases (SISMID), Rollins School of Public Health

Summer Institute in Statistics and Modeling in Infectious Diseases (SISMID), Rollins School of Public Health

Category : News/Events

Mark your calendars for the 17th annual Summer Institute in Statistics and Modeling in Infectious Diseases (SISMID). This event will be held online on July 7-11, 2025 and in-person on July 14-30, 2025. 

Since 2009, SISMID has trained thousands of infectious disease researchers in modern methods in statistical analysis and mathematical modeling. SISMID attendees choose from a range of 2.5-day modules, covering topics such as spatial statistics, evolutionary dynamics, nowcasting and forecasting, machine learning, network modeling, reproducible research, and more — all taught by experts in the field. Network with instructors and other attendees during poster evenings and improve your professional skills at lunch-and-learn sessions. 

Scholarships are available!

For more information and application instructions, visit the page linked here.


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Upcoming Events

  • Humphrey NoonTime Seminar Series April 3, 2025 at 12:00 pm – 1:00 pm Seminar Series; zoom.us… Online Location: https://zoom.us/J/95658300925Event Type: Seminar SeriesSeries: Humphrey NoonTime Seminar SeriesSpeaker: Humphrey FellowsContact Name: Deirdre RussellContact Email: dwruss2@emory.eduRoom Location: RRR_R809Link: https://zoom.us/J/95658300925the Humphrey Fellowship, a Fulbright Exchange Program proudly present a series of presentations from around the world.Participants may join via zoom or in person Pizza will be provided.
  • “UniLasso”— a novel statistical method for sparse regression April 10, 2025 at 4:00 pm – 5:00 pm Seminar Series; zoom.us… Online Location: https://zoom.us/j/92231723229Event Type: Seminar SeriesSeries: Biostatistics and BioinformaticsSpeaker: Robert Tibshirani, PhDContact Name: Mary AbosiContact Email: mabosi@emory.eduRoom Location: CNR_8030 Lawrence P. &Ann Estes Klamon room“UniLasso”— a novel statistical method for sparse regression

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