(For a full list see below).
Equitensors integrate heterogeneous city data, adjusting for fairness, to produce reusable, integrated features that can improve accuracy and fairness over training using a single dataset.
An Yan, Bill Howe
We introduced FairST, a fairness-aware demand prediction model for spatiotemporal urban applications, with emphasis on new mobility.
An Yan, Bill Howe
EquiTensors: Learning Fair Integrations of Heterogeneous Urban Data
An Yan, Bill Howe
SIGMOD 2021
Fairness-Aware Demand Prediction for New Mobility
An Yan, Bill Howe
AAAI 2020
FairST: Equitable Spatial and Temporal Demand Prediction for New Mobility Systems
An Yan, Bill Howe
SIGSPATIAL 2019 (short paper)
Fairness in Practice: A Survey on Equity in Urban Mobility
An Yan, Bill Howe
Data Engineering (September 2019)