Jessica Forde

Jessica is a data scientist at Qadium where she works on datamicroscopes, a Bayesian nonparametrics library in Python. Prior to Qadium, she was a researcher at Columbia University's Center for Computational Learning Systems studying smart building technology with New York HVAC system datasets. As a masters student in Statistics at Columbia, she has applied machine learning to problems such as sustainability, declassified government documents, and electronic health records. In her spare time, Jessica contributes to Density, an open-source Columbia-student website providing real-time estimates of study space availability based on wireless router data. She also organizes the monthly Women in Machine Learning brown bag lunch with researchers at Microsoft.