I am currently a data engineer on the Siri Search Data team at Apple, working on modeling efforts for improving Siri Search data quality.
I graduated from Harvard College in May 2020 with a joint degree in Computer Science and Statistics. I am generally interested in all things AI/ML, especially probabilistic (Bayesian) models, computational cognitive science and interpretable ML. I am fortunate to have collaborated with Finale Doshi-Velez, Hima Lakkaraju and Sam Gershman.
You can reach me at wanqian at alumni dot harvard dot edu. This is a forwarding address which redirects to my personal email account.
|Summer 2020||I was a machine learning research intern at Nuro, a self-driving startup focused on autonomous goods delivery.|
|May 2020||I wrote my senior thesis on (i) specifying interpretable priors and (ii) evaluating variational approximations for Bayesian neural networks. I was advised by Finale Doshi-Velez (Computer Science) and Alexander Young (Statistics). My thesis was awarded a Hoopes Prize.|
|Summer 2019||I was a data science intern at Apple, where I worked on anomaly detection for Siri Search analytics.|
|Summer 2018||I was a software engineering intern at TCV, a venture capital firm, where I worked on data-driven approaches for automating sourcing efforts.|
- NeurIPSIncorporating Interpretable Output Constraints in Bayesian Neural NetworksIn Advances in Neural Information Processing Systems, 2020.[Accepted as spotlight paper.]
- ThesisMaking Decisions Under High Stakes: Trustworthy and Expressive Bayesian Deep LearningSenior Thesis, Harvard University, 2020.(PDF below contains post hoc corrections for minor errata.)
- PLOS CBDiscovery of Hierarchical Representations for Efficient PlanningPLOS Computational Biology, 2020.
- ICML WorkshopOutput-Constrained Bayesian Neural NetworksIn 36th International Conference on Machine Learning Workshop on Uncertainty and Robustness in Deep Learning, 2019.