I am currently pursuing a PhD in computer science at the University of Washington's Paul G. Allen School of Computer Science & Engineering. I hold an M.S. in Applied Statistics and an M.S. in Information Science from the University of Michigan, where I worked with Christopher Brooks in the Educational Technology Collective (etc). I also hold a B.A. with Highest Honors in Philosophy from the University of Michigan. I have experience in machine learning research and software development at Google, GoPro, ProQuest, and the Penn Center for Learning Analytics. Previously, I served for five years in Miami-Dade Country Public Schools and KIPP New Orleans Schools.
My current research is at the intersection of fairness and privacy in machine learning. My other research interests include methods for making machine learning reliable, fair, and privacy-preserving; human-centered machine learning; novel applications of deep learning; and reproducibility.
While my early research focused on machine learning and statistical inference applications in education, my main research focus is on core and applied machine learning.
Awards and honors for my past work include a Best Paper Award at the International Conference on Learning Analytics and Knowledge (LAK), the Margaret Mann Award, the UMSI Professional Practice Fellowship, and the William K. Frankena Prize.
I have been fortunate to be affiliated with the following conferences and journals as a reviewer or PC member.
- Conferences: ICLR (2021), ICML (2020, 2021), IJCAI-PRICAI (PC 2020), CHI (2019, 2020), ACM Learning@Scale (2017, 2018), ACM Conference on Computer-Supported Collaborative Work (2018), International Conference on Learning Analytics and Knowledge (2018, PC 2019 - 2021), International Conference on Educational Data Mining (PC 2020, 2021).
- Journals: Neural Networks, IEEE Intelligent Systems, IEEE Transactions on Neural Networks and Learning Systems, Journal of Learning Analytics, Journal of Computers and Education.