Program Overview

Massive datasets are revolutionizing fields like genomics, imaging, healthcare and public health. To unlock the potential of big data, and turn it into actionable knowledge, we need a skilled workforce. The Big Data Summer Immersion at Yale (BDSY) is designed to equip the next generation of student and leaders to tackle the challenges of health Big Data.

Key Program Features:

• Didactic Lectures: Each morning faculty and graduate students from statistics, biostatistics, epidemiology and computer science are going to present core concepts in health big data.
• Mentored Research Projects: Immerse yourself in real-world data analysis projects guided by expert faculty. The projects will be in three areas: Infectious Disease Modeling, Genomics and Causal Inference.
• Journey Lectures: Learn about different data science careers through these non-technical talks.
• Learn from health researchers: Health researchers will share how they use big data and modeling to answer substantive questions of interest
• Professional Development: Gain valuable insights into career paths, graduate school applications and networking opportunities.
• Research Symposium: Showcase your work and learn from your peers at the concluding symposium.
• Social Events: We will explore hikes, shorelines, museums and libraries at the beautiful Yale campus.
• Data Ethics: This year’s offering will focus on teaching core concepts around responsible use of data and methods towards achieving data ethics.

Collaborate with Experts:

Throughout the program, you’ll have the unique opportunity to interact with distinguished faculty and graduate students from the YSPH departments of Biostatistics, Statistics, Epidemiology, as well as experts from Yale’s Engineering and Computer Science departments. Complementing the quantitative expertise will be narratives and case-studies shared by clinical and public health researchers.

By participating in BDSY, you’ll gain a deep understanding of what a career in biostatistics looks like and be well-prepared to contribute to the future of data-driven innovation in healthcare and public health.