Data Solution Design Studio

Data Solution Design Studio 

When entrepreneurs talk about their vision for data, people can be overly confident in their intuition, their data can be less than ready to tackle the problems they envisioned, they may lack tangible metrics to quantify the desired outcome, or they may not know about the existence of newer tools and methods. A data scientist can help shape these visions into actionable projects with tangible outcomes.

The Data Design Studio works on data ideas that serve the public and translate them into concrete data science projects. Overall, students will learn to consult domain experts by quickly understanding the context, setting concrete milestones, managing expectations, defining success metrics, validating data sources, and writing out detailed project briefs. Our goal is to help realize the potential for the public good with data science.

Students should know that this class will emphasize exercising their creativity, observation, and communication rather than cutting-edge technologies and algorithms. You will connect weekly with the project owner to flesh out details around the project while learning practical consulting skills in class.

Learning Objectives

  • Students will assist others to articulate their vision by formalizing their ideas with mathematical rigor backed by data
  • Students will learn to set achievable and relevant milestones with a reasonable deadline for time-sensitive projects
  • Students will learn to manage expectations around data science projects and learn to trade off perfection vs speed
  • Students will learn to create maintainable models and documentation meant for a wide audience with different backgrounds.

Student Information

The Data Solution Design Studio accepts students (interns) during the fall and spring semesters. During the academic semester, interns may receive course credit and a grade (letter or Pass/Fail) by registering for the course section under Mentored Research GR5398. Course syllabus, projects, and registration instructions are shared at the beginning of each semester. 


David Rios, Ph.D.

Tian Zheng, Ph.D.

Wayne T. Lee, Ph.D. (past instructor) 


We work with partners in the public and private sectors on projects that enable students to apply their research and data science. Are you interested in partnering with us? Complete the Studio Partnership Proposal Form.  Below is a partial list of projects our students have worked on (click the “+” to expand): 


Fall 2021

What: Can business strategies be inferred from music streaming data? Can we create a tool that would project revenue for future productions? 

Fall 2021

What: How are our health and wellness programs for aging New Yorkers doing?

Fall 2021

What: Giving citizens more clarity as to where and how NYCHA's money is being spent.

Fall 2021

What: Better access and understanding of NYC and NYS procurement algorithms.

Fall 2021

What: To determine whether a probabilistic genotyping software (PGS) is properly calibrated using Bayesian data analysis methods such as record linkage and to assess whether uncertainty is properly quantified and handled in likelihood ratio (LR) results.

Spring 2022 

What: To quantitatively measure the impact of Asian Americans for Equality (AAFE) programs vis-a-vis the charity’s overall goals.