Workshop on Translational Research on Data Heterogeneity

Hosted by the Department of Statistics and Data Science, Washington University in St. Louis, with support from National Science Foundation Grants DMS-1951980 and DMS-2406154

In this digital age, large-scale data offer many new opportunities, holding great promises for researchers and decision-makers to understand important variations among sub-populations, explore associations between features and rare outcomes (e.g., rare diseases or extreme events), and make optimal personalized recommendations in areas of immediate practical relevance such as precision medicine and social programs. There exist formidable computational and statistical challenges in the analysis of heterogenous data. Some of the key barriers include scalability to data size and dimensionality, deep exploration of heterogeneity and structures in the data, need for robustness and replicability, and the ability to make sense of incomplete observations (e.g., due to censoring).  The workshop will serve as a platform for bringing some of the leading scholars in statistics and data science to exchange new research ideas and train the next-generation data scientists in the analysis of heterogeneous data. The workshop will convene interdisciplinary researchers to discuss the forefront of heterogeneous data analysis and identify emerging areas for future research, emphasizing both methodology and applications.

The workshop will feature keynote speakers, invited talks, poster session and career panel for junior researchers. Graduate students, postdocs, and participants from under-represented groups are particularly welcome.

For the most up-to-date information about this event, please visit the official website for the workshop here:

For a full schedule of events, please click the following link: program2024.pdf (


Keynote Speakers:

  • Jianqing Fan, Princeton University
  • Bhramar Mukherjee, University of Michigan

Program Committee:

  • Xuming He, Washington University in St. Louis
  • Kengo Kato, Cornell University
  • Roger Koenker, University College London
  • Snigdha Panigrahi, University of Michigan
  • Lan Wang, University of Miami
  • Qi Zheng, University of Louisvill


Registration is now closed.