My name is Yuan Cui (崔元), and I also go by Charles. I work with data and try to make a positive social impact with my work. Here’s my story.
2020 - present: Northwestern University
Following my passion for computer science, I joined the CS Ph.D. program at Northwestern. I started out grad school stuyding the intersection of economics and computation. I spent my first one and a half years taking theoretical computer science courses as well as many Ph.D. level of economics courses. Loving the abstract beauty of math and theories but yearning for solving more applied and social-impact centered problems, I pivoted to doing more appplied research in human-computer interaction, data science, and algorithms. In addition, I sought opportunities to develop expertise in tech-for-social-impact work and deepen my knowledge of the research-to-practice pipeline.
2020 - present: Mechanism Design for Social Good (MD4SG)
At the start of grad school, I began participating in MD4SG, a multi-institutional research initiative of interdisciplinary scholars and practitioners aiming to improve access and create opportunities for historically underserved communities. After participating in the Environment and Data Economies working groups for a year, my collaborators and I hosted a tutorial on data externalities at the ACM FAccT conference. I later lead the Data Economies group and eventually became a co-organizer for the entire MD4SG initiative to manage its operations and design new programs. MD4SG gave me the opportunity to do theoretical work with a social impact flavor, taught me how to have effective discussions and conduct research with people from interdisciplinary backgrounds, and introduced me to a community of scholars who are striving to study the societal implications of sociotechnical systems.
Summer 2022: Data Science for Social Good (DSSG) @ Carnegie Mellon University
In order to gain insights into the practical applications of computer science in real-world problems, I worked at the Data Science for Social Good summer fellowship program at Carnegie Mellon University under the supervision of Rayid Ghani and Kit Rodolfa, where we partnered with the 988 Suicide & Crisis Lifeline and built a machine learning pipeline based on historical call data to help the lifeline make routing decisions that would allow them to answer more calls. In addition to receiving extensive technical training on practical machine learning projects, I learned valuable lessons from interacting with our partner organization and with weekly speakers from government agencies and nonprofit organizations. The real world doesn’t work like a textbook—organizations face so many constraints, and we have to communicate to understand their pain points. I learned about how crucial it is to be able to articulate the necessity of data-driven solutions to decision makers at the top who may not have the same technical know-how and vocabulary that engineers do.
Summer 2023: Graduate Student Fellow @ Stanford RegLab
At the same time, I developed leadership, management, and communication skills outside of my academic work.
Consulting: Advanced Degree Consulting Aliance (ADCA), Impact Consulting Chicago
I gained consulting and project management experience while serving as the Vice President of University and Alumni relatons at ADCA, as well as co-founding Impact Consulting Chicago and serving as the Head of Business Development. Under these roles, I managed several pro bono consulting projects for social-impact starups in the space of elderly care, financial lteracy education, and sustainable clothing.
Leadership Development: Center for Leadership
After serving in leadership positions at different organzations, I wanted to more delibrately develop my leadership skills. I participated in the leadership coaching program, the fellowship program, and later served as a team lead in the fellowship program at the Center for Leadership. I deepened my understanding of my own leadership style, identified and acted on areas of improvement, and developed a “leadership as service” mindset.
2016 - 2020: Oberlin College
I majored in mathematics and computer science. Mathematics showed me a powerful way of seeing and understanding the world, and I felt in love with it instantly. I took as many math and theoretical computer science classes as I could, and studied abroad at Budapest Semesters in Mathematics. I did research with multiple professors on topics including economics and computation, primality testing, and machine learning. My undergraduate thesis examined how simple modifications of the deferred acceptance matching algorithm affects perceived fairness and strategic behavior of school applicants. I graduatd with high honor and as a member of Phi Beta Kappa. I’m grateful for the tight-knit Oberlin community woven together with love and compassion, and I was fortunate to be mentored by Jack Calcut, Ben Linowitz, and Sam Taggart. I learned the technical and reasoning skills to analyze problems with quantitative rigor. I also learned the importance of community building and mentorship.