Speaker: Xinlu Huang

Data Scientist @Opendoor

Xinlu is a data scientists on the pricing and revenue optimization group at Opendoor in San Francisco. The team focuses on developing per-home liquidity estimation and building responsive pricing models.

Before joining Opendoor, Xinlu was a theoretical particle physicist at Stanford. She holds a Master of Music in piano performance from Peabody Conservatory and PhD in physics from Stanford.

Find Xinlu Huang at

2019 Tracks

  • ML in Action

    Applied track demonstrating how to train, score, and handle common machine learning use cases, including heavy concentration in the space of security and fraud

  • Deep Learning in Practice

    Deep learning use cases around edge computing, deep learning for search, explainability, fairness, and perception.

  • Handling Sequential Data Like an Expert / ML Applied to Operations

    Discussing the complexities of time (half track) and Machine Learning in the data center (half track). Exploring topics from hyper loglog to predictive auto-scaling in each of two half-day tracks.

    Half-day tracks