Hi, I'm My :D (*Rush Hour 3* scene is how you remember my name. Hint: it is *Mi*)

About Me

I am a rising fourth-year Ph.D. student in the Computer Science Department at the University of Virginia, advised by Professor Ferdinando Fioretto. My research interest is the integration of constrained optimization and machine learning, with a focus on differentiable optimization.

I received my Bachelor’s in Applied Math from the University of California, Berkeley in 2015. After graduating, I was fortunate to join Trusting Social’s team as a Data Scientist, working on e-KYC services and AI-based credit scores. My team built data mining and machine learning solutions using big social networking data, as well as facial and image recognition products for major banks and businesses in Vietnam.

I was raised in a traditional Vietnamese household, which has fostered my love for everything related to Asia, including its culture, destinations, people, food, and art. In my free time, I enjoy cooking, working on DIY projects, practicing Chinese ink painting, swing dancing, and trekking.

Recent Updates

  • [April, 2024] I received a Travel Award from ACM FaccT 2024 Committee.
  • [April, 2024] Our paper End-to-End Learning for Fair Multiobjective Optimization Under Uncertainty got accepted to UAI 2024! Check out the paper here
  • [March, 2024] Our paper Learning Fair Ranking Policies via Differentiable Optimization of Ordered Weighted Averages got accepted to ACM FaccT 2024! Check out the paper here.
  • [December, 2024] A new preprint titled Analyzing and Enhancing the Backward-Pass Convergence of Unrolled Optimization. Check out the paper here.
  • [September, 2023] Our paper An Analysis of the Reliability of AC Optimal Power Flow Deep Learning Proxies was accepted in IEEE PES Innovative Smart Grid Technologies. Check out the paper here.
  • [August, 2023] Our lab moved to University of Virginia!
  • [July, 2023] I passed SU’s Qualifying Exam 2.
  • [March, 2023] Our paper Backpropagation of Unrolled Solvers with Folded Optimization was accepted at IJCAI.
  • [January, 2023] I will TA for CIS 351, Data Structures.
  • [August, 2022] I will TA for CIS467, Introduction to Artificial Intelligence.
  • [January, 2023] A new preprint titled Context-Aware Differential Privacy for Language Modeling. Check out the paper here.
  • [March, 2022] Our collaboration work Learning Solutions for Intertemporal Power Systems Optimization with Recurrent Neural Network with Professor Kyri Baker from University of Colorado, Boulder is accepted to PMAPS 2022.
  • [February, 2022] A new preprint titled A Fairness Analysis on Private Aggregation of Teacher Ensembles. Check out the paper here.
  • [January, 2022] I passed SU’s Qualifying Exam 1.
  • [September, 2021] Paper titled Differentially Private Empirical Risk Minimization under the Fairness Lens is accepted to Neurips 2021.

Contact Information

The best way to contact me is via email: fqw2tz@virginia.edu

222 Rice Hall, 85 Engineer’s Way, Charlottesville, VA 22904