Dilkina, Bistra

Machine learning approaches for estimating commercial building energy consumption

Robinson, C., Dilkina, B., Hubbs, J., Zhang, W., Guhathakurta, S., Brown, M. A., & Pendyala, R. M. (2017) · Applied Energy

Building Energy and Comfort OptimizationBuilding energy efficiency and sustainability

Cited by 482

Computational sustainability: computing for a better world and a sustainable future

Gomes, C., Dietterich, T., Barrett, C., Conrad, J., Dilkina, B., Ermon, S., Fang, F., Farnsworth, A., Fern, A., Fern, X., et al. (2019) · Communications of the ACM

Innovation, Sustainability, Human-Machine SystemsGreen IT and Sustainability

Cited by 126

megaSDM: Integrating dispersal and time-step analyses into species distribution models

Shipley, B. R., Bach, R., Do, Y., Strathearn, H., McGuire, J. L., & Dilkina, B. (2022) · Ecography

Species Distribution and Climate ChangeEcology and Vegetation Dynamics Studies

Cited by 80

Estimating residential energy consumption in metropolitan areas: A microsimulation approach

Zhang, W., Robinson, C., Guhathakurta, S., Garikapati, V. M., Dilkina, B., Brown, M. A., & Pendyala, R. M. (2018) · Energy

demographic modeling and climate adaptationEnergy, Environment, and Transportation Policies

Cited by 68

Infrastructure Resilience for Climate Adaptation

Gupta, A., Robinson, C., & Dilkina, B. (2018) · Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies

Infrastructure Resilience and Vulnerability AnalysisFlood Risk Assessment and Management

Cited by 6