Workshop on Data-Driven Mathematical and Statistical Modeling for Graduate Students

July 12-16, 2021

This five-day virtual workshop will introduce graduate students to topics in mathematical and statistical modeling that are needed to carry out advanced research in a data-driven context. Important aspects of model formulation and selection, parameter estimation, sensitivity analysis and uncertainty quantification, including synergies with machine learning, will be covered in a series of mini-tutorials. The tutorials will include projects that participants will work on in groups, presenting their results on the final day of the workshop. Researchers from outside of academia (national labs, government agencies, industry) will present a series of case studies demonstrating how advanced mathematical and statistical research is used to address problems in these sectors. The workshop will also include a set of career development activities and professional development panel discussions. Participants will leave the workshop with a greater understanding of the skills needed to address mathematical and statistical problems in a data rich context whether in academia, government, or industry.


Applicants must be currently enrolled full-time in a US-based mathematics, statistics (or related) graduate program. Participants are expected to have access to high-speed internet and a computer with R and/or Matlab. Participants must also make a commitment to participate in the full workshop.

Application Process:

  • Applications are due by 5 pm Eastern Daylight Time on May 31st, 2021
  • The application form is available¬†HERE
  • Note: upload your unofficial graduate transcript(s) and a copy of your cv or resume at the end of the form.

If you have questions about your eligibility or other aspects of the workshop, please contact Mansoor Haider ( and/or Emily Griffith (