| A data-driven predictive model of city-scale energy use in buildings CE Kontokosta, C Tull Applied Energy 197, 303-317, 2017 | 250 | 2017 |
| Extending Bayesian structural time-series estimates of causal impact to many-household conservation initiatives E Schmitt, C Tull, P Atwater The Annals of Applied Statistics 12 (4), 2517-2539, 2018 | 19 | 2018 |
| EnergyViz: Web-based Eco-visualization of Urban Energy Use from Building Benchmarking Data CE Kontokosta, C Tull Proceedings of the International Conference on Computing in Civil and …, 2016 | 12 | 2016 |
| Web-Based Visualization and Prediction of Urban Energy Use from Building Benchmarking Data C Kontokosta, C Tull, D Marulli, R Pinggera, M Yaqub Bloomberg Data for Good Exchange Conference, 2015 | 11 | 2015 |
| How Much Water Does Turf Removal Save? Applying Bayesian Structural Time-Series to California Residential Water Demand C Tull, S Eric, P Atwater SIGKDD: Data Science for Food, Energy and Water, 2016 | 10 | 2016 |
| Transforming how water is managed in the West P Atwater, C Tull, E Schmitt, J Lopez, D Atwater, V Adibhatla Bloomberg Data for Good Exchange Conference, 2016 | | 2016 |
| Spatial Analysis of Commercial Waste Haulers and Waste Generation Rates in NYC (Report) C Kontokosta, A Malik, C Tull NYC Business Integrity Commission, 2015 | | 2015 |
