Publications (by topic)

Lai, Y., Papadopoulos, S., Fuerst, F., Pivo, G., Sagi, J., & Kontokosta, C. E. (2022). Building retrofit hurdle rates and risk aversion in energy efficiency investments. Applied Energy, 306, 118048.

Kontokosta, C. E., Spiegel-Feld, D., & Papadopoulos, S. (2020). The impact of mandatory energy audits on building energy use. Nature Energy, 5(4), 309-316.

Kontokosta, C. E., Reina, V. J., & Bonczak, B. (2020). Energy cost burdens for low-income and minority households: Evidence from energy benchmarking and audit data in five US cities. Journal of the American Planning Association, 86(1), 89-105.

Lai, Y., & Kontokosta, C. E. (2019). Topic modeling to discover the thematic structure and spatial-temporal patterns of building renovation and adaptive reuse in cities. Computers, Environment and Urban Systems, 78, 101383.

Papadopoulos, S., Kontokosta, C. E., Vlachokostas, A., & Azar, E. (2019). Rethinking HVAC temperature setpoints in commercial buildings: The potential for zero-cost energy savings and comfort improvement in different climates. Building and Environment, 155, 350-359.

Lai, Y., & Kontokosta, C. E. (2019). The impact of urban street tree species on air quality and respiratory illness: A spatial analysis of large-scale, high-resolution urban data. Health & place, 56, 80-87.

Bonczak, B., & Kontokosta, C. E. (2019). Large-scale parameterization of 3D building morphology in complex urban landscapes using aerial LiDAR and city administrative data. Computers, Environment and Urban Systems, 73, 126-142.

Papadopoulos, S., & Kontokosta, C. E. (2019). Grading buildings on energy performance using city benchmarking data. Applied Energy, 233, 244-253.

Papadopoulos, S., Bonczak, B., & Kontokosta, C. E. (2018). Pattern recognition in building energy performance over time using energy benchmarking data. Applied Energy, 221, 576-586.

Johnson, N. E., Bonczak, B., & Kontokosta, C. E. (2018). Using a gradient boosting model to improve the performance of low-cost aerosol monitors in a dense, heterogeneous urban environment. Atmospheric environment, 184, 9-16.

Papadopoulos, S., Azar, E., Woon, W. L., & Kontokosta, C. E. (2018). Evaluation of tree-based ensemble learning algorithms for building energy performance estimation. Journal of Building Performance Simulation, 11(3), 322-332.

Kontokosta, C., Lai, Y., Bonczak, B., Papadopoulos, S., Hong, B., Johnson, N., & Malik, A. (2018). A Dynamic Spatial-Temporal Model of Urban Carbon Emissions for Data-Driven Climate Action by Cities. Bloomberg Data for Good Exchange 2018.

Reina, V. J., & Kontokosta, C. (2017). Low hanging fruit? Regulations and energy efficiency in subsidized multifamily housing. Energy Policy, 106, 505-513.

Kontokosta, C. E., & Tull, C. (2017). A data-driven predictive model of city-scale energy use in buildings. Applied energy, 197, 303-317.

Papadopoulos, S., Bonczak, B., & Kontokosta, C. E. (2017). Spatial and geographic patterns of building energy performance: A cross-city comparative analysis of large-scale data. In International Conference on Sustainable Infrastructure 2017 (pp. 336-348).

Papadopoulos, S., & Kontokosta, C. E. (2017). Big Buildings and Big Data: Do Energy Disclosure Policies Impact Energy Use over Time?. In Computing in Civil Engineering 2017 (pp. 248-255).

Kontokosta, C. E. (2016). Modeling the energy retrofit decision in commercial office buildings. Energy and buildings, 131, 1-20.

Marasco, D. E., & Kontokosta, C. E. (2016). Applications of machine learning methods to identifying and predicting building retrofit opportunities. Energy and Buildings, 128, 431-441.

Kontokosta, C. E. (2016). Energy efficiency. Issues in Science and Technology, 33(1).

Kontokosta, C., Bonczak, B., & Duer-Balkind, M. (2016). DataIQ—a machine learning approach to anomaly detection for energy performance data quality and reliability. In Proceedings of the ACEEE.

Kontokosta, C. E., & Jain, R. K. (2015). Modeling the determinants of large-scale building water use: Implications for data-driven urban sustainability policy. Sustainable Cities and Society, 18, 44-55.

Kontokosta, C., Tull, C., Marulli, D., Pingerra, R., & Yaqub, M. (2015, September). Web-Based Visualization and Prediction of Urban Energy Use from Building Benchmarking Data. In Bloomberg Data for Good Exchange Conference.

Kontokosta, C. E. (2015). A market-specific methodology for a commercial building energy performance index. The Journal of Real Estate Finance and Economics, 51(2), 288-316.

Jain, R. K., Moura, J. M., & Kontokosta, C. E. (2014). Big data+ big cities: Graph signals of urban air pollution. IEEE Signal Processing Magazine, 31(5), 130-136.

Fuerst, F., Kontokosta, C., & McAllister, P. (2014). Determinants of green building adoption. Environment and Planning B: Planning and Design, 41(3), 551-570.

Jain, R. K., Damoulas, T., & Kontokosta, C. E. (2014). Towards data-driven energy consumption forecasting of multi-family residential buildings: feature selection via the lasso. In Computing in Civil and Building Engineering (2014) (pp. 1675-1682).

Kontokosta, C. E. (2013). Energy disclosure, market behavior, and the building data ecosystem. Annals of the New York Academy of Sciences, 1295(1), 34-43.

Kontokosta, C. E. (2013). Tall buildings and Urban expansion: Tracing the evolution of zoning in the United States. Leadership and Management in Engineering, 13(3), 190-198.

Kontokosta, C. (2012). Local Law 84 Energy Benchmarking Data: Report to the New York City Mayor’s Office of Long-Term Planning and Sustainability, April.

Kontokosta, C. E. (2012). Predicting building energy efficiency using New York City benchmarking data. Proceedings of the 2012 ACEEE Summer Study on Energy Efficiency in Buildings, Washington, DC, American Council for an Energy-Efficient Economy.

Kontokosta, C. (2011). Greening the regulatory landscape: The spatial and temporal diffusion of green building policies in US cities. Journal of Sustainable Real Estate, 3(1), 68-90.

Kontokosta, C. E., Hong, B., & Bonczak, B. J. (2024). Socio-spatial inequality and the effects of density on COVID-19 transmission in US cities. Nature Cities, 1(1), 83-93.

Kontokosta, C. E., & Hong, B. (2021). Bias in smart city governance: How socio-spatial disparities in 311 complaint behavior impact the fairness of data-driven decisions. Sustainable Cities and Society, 64, 102503.

Lobo, J., Alberti, M., Allen-Dumas, M., Arcaute, E., Barthelemy, M., Bojorquez Tapia, L. A., … & Youn, H. (2020). Urban science: Integrated theory from the first cities to sustainable metropolises.

Lai, Y., & Kontokosta, C. E. (2019). Topic modeling to discover the thematic structure and spatial-temporal patterns of building renovation and adaptive reuse in cities. Computers, Environment and Urban Systems, 78, 101383.

Kontokosta, C. E., Merritt, J., & Dolder, S. (2018). Solving City Challenges Through Neighborhood Innovation Labs: Moving from Smart Cities to Informed Communities. In Smarter New York City (pp. 228-250). Columbia University Press.

Kontokosta, C. E., Hong, B., Johnson, N. E., & Starobin, D. (2018). Using machine learning and small area estimation to predict building-level municipal solid waste generation in cities. Computers, Environment and Urban Systems, 70, 151-162.

Hong, B., Malik, A., Lundquist, J., Bellach, I., & Kontokosta, C. E. (2018). Applications of machine learning methods to predict readmission and length-of-stay for homeless families: The case of win shelters in new york city. Journal of Technology in Human Services, 36(1), 89-104.

Kontokosta, C. E. (2018). Urban informatics in the science and practice of planning. Journal of Planning Education and Research, 0739456X18793716.

Sobolevsky, S., Levitskaya, E., Chan, H., Enaker, S., Bailey, J., Postle, M., … & Kontokosta, C. (2017). Impact Of Urban Technology Deployments On Local Commercial Activity. arXiv preprint arXiv:1712.00659.

Wang, L., Qian, C., Kats, P., Kontokosta, C., & Sobolevsky, S. (2017). Structure of 311 service requests as a signature of urban location. PloS one, 12(10), e0186314.

Kontokosta, C., Hong, B., & Korsberg, K. (2017). Equity in 311 reporting: Understanding socio-spatial differentials in the propensity to complain. arXiv preprint arXiv:1710.02452.

Kontokosta, C. E., Weiss, M., Snively, C., & Gulick, S. (2017). NYC311. Harvard Business School Case, 818-056.

Kontokosta, C. E. (2016). The quantified community and neighborhood labs: A framework for computational urban science and civic technology innovation. Journal of Urban Technology, 23(4), 67-84.

Kontokosta, C. E., Hong, B., & Bonczak, B. J. (2024). Socio-spatial inequality and the effects of density on COVID-19 transmission in US cities. Nature Cities, 1(1), 83-93.

Kontokosta, C. E., Hong, B., & Bonczak, B. J. (2022). Measuring sensitivity to social distancing behavior during the COVID-19 pandemic.Scientific reports, 12(1), 16350.

Hong, B., Bonczak, B. J., Gupta, A., Thorpe, L. E., & Kontokosta, C. E. (2021). Exposure density and neighborhood disparities in COVID-19 infection risk. Proceedings of the National Academy of Sciences, 118(13).

Kontokosta, C. E., Freeman, L., & Lai, Y. (2021). Up-and-Coming or Down-and-Out? Social Media Popularity as an Indicator of Neighborhood Change. Journal of Planning Education and Research, 0739456X21998445.

Johnson, N. E., Mandiola, P., Blankinship, C., Bonczak, B., & Kontokosta, C. E. (2019, December). Validating the Use of Wi-Fi Signals to Estimate Hyperlocal Urban Populations. In 2019 IEEE International Conference on Big Data (Big Data) (pp. 1650-1655). IEEE.

Lai, Y., & Kontokosta, C. E. (2018). Quantifying place: Analyzing the drivers of pedestrian activity in dense urban environments. Landscape and Urban Planning, 180, 166-178.

Traunmueller, M. W., Johnson, N., Malik, A., & Kontokosta, C. E. (2018). Digital footprints: Using WiFi probe and locational data to analyze human mobility trajectories in cities. Computers, Environment and Urban Systems, 72, 4-12.

Sobolevsky, S., Levitskaya, E., Chan, H., Postle, M., & Kontokosta, C. (2018). Impact Of Bike Sharing In New York City. arXiv preprint arXiv:1808.06606.

Wang, L., Qian, C., Kats, P., Kontokosta, C., & Sobolevsky, S. (2017). Structure of 311 service requests as a signature of urban location. PloS one, 12(10), e0186314.

Kats, P., Qian, C., Kontokosta, C., & Sobolevsky, S. (2017). Twitter Activity Timeline as a Signature of Urban Neighborhood. arXiv preprint arXiv:1707.06122.

Hong, B., Bonczak, B. J., Gupta, A., & Kontokosta, C. E. (2021). Measuring inequality in community resilience to natural disasters using large-scale mobility data. Nature Communications, 12(1), 1-9.

Kontokosta, C. E., & Malik, A. (2018). The Resilience to Emergencies and Disasters Index: Applying big data to benchmark and validate neighborhood resilience capacity. Sustainable cities and society, 36, 272-285.

Malik, A., & Kontokosta, C. (2017). Measuring Building Risk and Resilience: A Big Data Approach to Risk Analytics for Infrastructure. In American Society of Civil Engineers (ASCE) International Conference on Sustainable Infrastructure.

Kontokosta, C. E., Hong, B., & Bonczak, B. J. (2024). Socio-spatial inequality and the effects of density on COVID-19 transmission in US cities. Nature Cities, 1(1), 83-93.

Gupta, A., Van Nieuwerburgh, S., & Kontokosta, C. (2022). Take the Q train: Value capture of public infrastructure projects. Journal of Urban Economics, 129, 103422.

Sobolevsky, S., Levitskaya, E., Chan, H., Enaker, S., Bailey, J., Postle, M., … & Kontokosta, C. (2017). Impact Of Urban Technology Deployments On Local Commercial Activity. arXiv preprint arXiv:1712.00659.

Kontokosta, C. E. (2015). Do inclusionary zoning policies equitably disperse affordable housing? A comparative spatial analysis. Journal of housing and the built environment, 30(4), 569-590.

Kontokosta, C. E. (2014). Mixed‐income housing and neighborhood integration: evidence from inclusionary zoning programs. Journal of Urban Affairs, 36(4), 716-741.

Kontokosta, C. (2011). The price of victory: The Impact of the O-lympic Games on Residential Real Estate Markets [J]. Urban Study, 2, 1-18.