Work Experience

Cruise LLC, San Francisco, CA

Senior Data Scientist | Aug. 2023 – present

• Safety metrics development and autonomus vehicle performance evaluation.

Cruise LLC, San Francisco, CA

PhD Intern, Data Scientist | Jun. 2022 – Sep. 2022

• Leveraged my skills in SQL and Python to develop data miners and visualizers that can efficiently filter and present driving scenarios from multiple BigQuery tables.
• Decomposed driving into mutually exclusive, collectively exhaustive scenarios, and derived scenario coverage probabilities and confidence intervals.
• Employed PCA and T-SNE to reduce the dimensionality of the feature space and used multiple comparison techniques to assess the realism of different scenarios.
• Applied high dimensional unsupervised anomaly detection algorithms including isolation forest to compute the realism score for driving scenarios.
• Helped the simulation team to identify unrealistic scenarios based on the computed realism score.

This work has been featured in my manager Geoffrey Chi-Johnston’s presentation at KDD 2022 with the title: Applications of data science for autonomous vehicles.

Bayer U.S. LLC, Whippany, NJ

Statistician Intern | Jun. 2021 – Sep. 2021

• Investigated and compared adaptive two-stage design algorithms (Jones, Tournoux-Facon and Parashar designs) that incorporate biomarker status using simulated dataset induced by real clinical trial data. The adaptive two-stage design algorithms could help to identify the targeting population that might benefit from the drug, so that less drug development will be stopped in phase II due to treatment effect dilution.
• Enhanced the robustness of the current algorithms by improving the type I error and power calculation, as well as optimizing the search strategy.
• Utilized RCpp to write a more efficient searching algorithm and implemented the improved algorithms to an R package and R shiny app.

This work is presented in a poster session at JSM 2022.