External citation information: [Google Scholar] [ResearchGate]
Journal Publications
49. Excell, L.E., & Jain, R.K. (2023). Examining the impact of energy efficiency retrofits and vegetation on energy performance of institutional buildings: An equity-driven analysis. Applied Energy. 121722. [Link]
48. Aras, R. L., Ouellette, N. T., & Jain, R. K. (2023). Quantifying the pedestrian access potential of suburban street network retrofits. Environment and Planning B: Urban Analytics and City Science, 23998083231190974. [Link]
47. Andrews, A., & Jain, R. K. (2023). Evaluating building decarbonization potential in US cities under emissions based building performance standards and load flexibility requirements. Journal of Building Engineering, 107375. [Link]
46. Verma, A., Gupta, V., Nihar, K., Jana, A., Jain, R. K., & Deb, C. (2023). Tropical climates and the interplay between IEQ and energy consumption in buildings: A review. Building and Environment, 110551. [Link]
45. Dougherty, T. R., & Jain, R. K. (2023). TOM. D: Taking advantage Of Microclimate Data for Urban Building Energy Modeling. Advances in Applied Energy, 100138. [Link] [Data + Code]
44. Nihar, K., Nutkiewicz, A., & Jain, R. K. (2023). Natural ventilation versus air pollution: assessing the impact of outdoor pollution on natural ventilation potential in informal settlements in India. Environmental Research: Infrastructure and Sustainability. [Link] [Data + Code]
43. Miotti, M., Needell, Z. A., & Jain, R. K. (2023). The impact of urban form on daily mobility demand and energy use: Evidence from the United States. Applied Energy, 339, 120883. [Link] [Data]
42. Aras, R. L., Ouellette, N. T., & Jain, R. K. (2023). A barrier too far: Understanding the role of intersection crossing distance on bicycle rider behavior in Chicago. Environment and Planning B: Urban Analytics and City Science, 23998083221147922. [Link]
41. Dougherty, T., & Jain, R. K. (2022). Invisible walls: Exploration of microclimate effects on building energy consumption in New York City. Sustainable Cities and Society, 104364. [Link] [Data] [Code]
40. Andrews, A., & Jain, R. K. (2022). Beyond Energy Efficiency: A clustering approach to embed demand flexibility into building energy benchmarking. Applied Energy, 327, 119989. [Link]
39. Su, L., Nie, T., Ho, C. O., Yang, Z., Calvez, P., Jain, R. K., & Schwegler, B. (2022). Optimizing Pipe Network Design and Central Plant Positioning of District Heating and Cooling System: A Graph-Based Multi-Objective Genetic Algorithm Approach. Applied Energy, 325, 119844. [Link]
38. Dong, B., Liu, Y., Mu, W., Jiang, Z., Pandey, P., Hong, T., Jain, R.K., Sonta, A., & Zhou, X. (2022). A Global Building Occupant Behavior Database. Scientific data, 9(1), 1-15. [Link]
37. Andrews, A., Roth, J., Jain, R. K., & Mathieu, J. L. (2022). Data-driven examination of the impact energy efficiency has on demand response capabilities in institutional buildings. Journal of Engineering for Sustainable Buildings and Cities, 3(2), 024501. [Link]
36. Nutkiewicz, A., Rao, N., Mastrucci, A., & Jain, R. K. (2022). Cool roofs can mitigate cooling energy demand for informal settlement dwellers. Renewable and Sustainable Energy Reviews, 112183. [Link]
35. Nutkiewicz, A., Choi, B., & Jain, R. K. (2021). Exploring the influence of urban context on building energy retrofit performance: A hybrid simulation and data-driven approach. Advances in Applied Energy, 100038. [Link] [Code] [Open Access]
34. Shivaram, R., Yang, Z., & Jain, R. K. (2021). Context-aware Urban Energy Analytics (CUE-A): A framework to model relationships between building energy use and spatial proximity of urban systems. Sustainable Cities and Society, 102978. [Link]
33. Lei, S., Mathieu, J. L., & Jain, R. K. (2021). Performance of Existing Methods in Baselining Demand Response From Commercial Building HVAC Fans. Journal of Engineering for Sustainable Buildings and Cities, 2(2), 021002. [Link]
32. Roth J., Chadalawada J., Jain R.K., & Miller C. (2021). Uncertainty Matters: Bayesian Probabilistic Forecasting for Residential Smart Meter Prediction, Segmentation, and Behavioral Measurement and Verification. Energies, 14(5):1481. [Link]
31. Sonta, A., Dougherty, T., & Jain, R. K. (2021). Data-driven optimization of building layouts for energy efficiency. Energy & Buildings, 238, 110815. [Link]
30. Aras R.L., Ouellette N.T., & Jain R.K (2021). Automated identification of urban substructure for comparative analysis. PLoS ONE. 16(1): e0245067. [Link] [Data+ Code]
29. Roth, J., Martin, A., Miller, C., & Jain, R. K. (2020). SynCity: Using open data to create a synthetic city of hourly building energy estimates by integrating data-driven and physics-based methods. Applied Energy, 280, 115981. [Link]
28. Sonta, A., & Jain, R. K. (2020). Learning socio-organizational network structure in buildings with ambient sensing data. Data-Centric Engineering, 1, E9. doi:10.1017/dce.2020.9 [Link] [Data+ Code]
27. Roth, J., Brown, H., & Jain, R. K. (2020). Harnessing Smart Meter Data for a Multitiered Energy Management Performance Indicators (MEMPI) Framework: A Facility Manager Informed Approach. Applied Energy, 276, 115435. [Link]
26. Azar, E., O'Brien, W., Carlucci, S., Hong, T., Sonta, A., Kim, J., Andargie, M.S., Abuimara, T., El Asmar, M., Jain, R. K., & Ouf, M. M. (2020). Simulation-aided occupant-centric building design: A critical review of tools, methods, and applications. Energy and Buildings, 224, 110292. [Link]
25. Ruhlandt, R. W. S., Levitt, R., Jain, R. K., & Hall, D. (2020). One approach does not fit all (smart) cities: Causal recipes for cities' use of “data and analytics”. Cities, 104, 102800. [Link]
24. Roth, J., Lim, B., Jain, R. K., & Grueneich, D. (2020) Examining the feasibility of using open data to benchmark building energy usage in cities: a data science and policy perspective. Energy Policy, 139, 111327. [Link] [Data+ Code]
23. Ruhlandt, R. W. S., Levitt, R., Jain, R. K., & Hall, D. (2019). Drivers of Data and Analytics Utilization within (Smart) Cities: A Multimethod Approach. Journal of Management in Engineering, 36(2), 04019050. [Link]
22. Jin, M., Jain, R.K., Spanos, C., Jia, Q., Norford, L. K., Kjaergaard, M., & Yan, J. (2019). Energy-cyber-physical systems. Applied Energy, 256. [Link] [Invited Editorial]
21. Sonta, A. J., Jain, R. K. (2020). Building Relationships: Using Embedded Plug Load Sensors for Occupant Network Inference. IEEE Embedded Systems Letters. 12(2). [Link]
20. Jain, R.K., & Abraham, D. (2019). Special Collection Announcement: Computational Approaches to Enable Smart and Sustainable Urban Systems. ASCE Journal of Computing in Civil Engineering, 33 (6). [Link] [Invited Editorial]
19. Srivastava, C., Yang, Z., & Jain, R.K. (2019). Understanding the adoption and usage of data analytics and simulation among building energy management professionals: A nationwide survey. Building & Environment, 157, 139-164. [Link] [Data+ Code] [Press]
18. Gupta, G., Yang, Z., & Jain, R.K. (2019). Urban Data Integration Using Proximity Relationship Learning for Design, Management, and Operations of Sustainable Urban Systems. ASCE Journal of Computing in Civil Engineering, 33 (2). [Link] [Data+ Code]
17. Nutkiewicz, A., Jain, R. K., & Bardhan, R. (2018). Energy modeling of urban informal settlement redevelopment: Exploring design parameters for optimal thermal comfort in Dharavi, Mumbai, India. Applied Energy, 231, 433-445. [Link]
16. Nutkiewicz, A., Yang, Z., & Jain, R. K. (2018). Data-driven Urban Energy Simulation (DUE-S): A framework for integrating engineering simulation and machine learning methods in a multi-scale urban energy modeling workflow. Applied Energy, 225, 1176-1189. [Link] [*WINNER OF BEST PAPER AWARD*]
15. Sonta, A. J., Simmons, P. E., & Jain, R. K. (2018). Understanding building occupant activities at scale: An integrated knowledge-based and data-driven approach. Advanced Engineering Informatics, 37, 1-13. [Link] [ResearchGate][Code]
14. Khosrowpour, A., Jain, R.K., Taylor, J.E., Peschiera, G., Chen, J., & Gulbinas, R. (2018). A review of occupant energy feedback research: Opportunities for methodological fusion at the intersection of experimentation, analytics, surveys and simulation, Applied Energy, 218, 304-316 [Link]
13. Yang, Z., Roth, J., & Jain, R. K. (2017). DUE-B: Data-driven Urban Energy Benchmarking of Buildings using Recursive Partitioning and Stochastic Frontier Analysis. Energy and Buildings, 163, 58-69. [Link] [ResearchGate]
12. Jain, R.K., Qin, J., & Rajagopal R. (2017). Data-driven planning of distributed energy resources amidst socio-technical complexities. Nature Energy. [Link] [Editorial] [SharedIt - pdf]
11. Sonta, A.J., Jain, R. K., Gulbinas, G., Moura, J.M., & Taylor, J.E. (2017). OESPg: Computational Framework for Multidimensional Analysis of Occupant Energy Use Data in Commercial Buildings. ASCE Journal of Computing in Civil Engineering, 31(4). [Link] [GScholar] [ResearchGate]
10. 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. [Link] [GScholar] [ResearchGate]
9. Jain, R. K., Moura, J. M., & Kontokosta, C. E. (2014). Big data+ big cities: Graph signals of urban air pollution [exploratory sp]. IEEE Signal Processing Magazine, 31(5), 130-136. [Link] [GScholar] [ResearchGate]
8. Gulbinas, R., Jain, R. K., & Taylor, J. E. (2014). BizWatts: A modular socio-technical energy management system for empowering commercial building occupants to conserve energy. Applied Energy, 136, 1076-1084. [Link] [GScholar] [ResearchGate]
7. Jeong, S. H., Gulbinas, R., Jain, R. K., & Taylor, J. E. (2014). The impact of combined water and energy consumption eco-feedback on conservation. Energy and Buildings, 80, 114-119. [Link] [GScholar] [ResearchGate]
6. Jain, R. K., Smith, K. M., Culligan, P. J., & Taylor, J. E. (2014). Forecasting energy consumption of multi-family residential buildings using support vector regression: Investigating the impact of temporal and spatial monitoring granularity on performance accuracy. Applied Energy, 123, 168-178. [Link] [GScholar] [ResearchGate]
5. Jain, R. K., Gulbinas, R., Taylor, J. E., & Culligan, P. J. (2013). Can social influence drive energy savings? Detecting the impact of social influence on the energy consumption behavior of networked users exposed to normative eco-feedback. Energy and Buildings, 66, 119-127. [Link] [GScholar] [ResearchGate]
4. Jain, R. K., Taylor, J. E., & Culligan, P. J. (2013). Investigating the impact eco-feedback information representation has on building occupant energy consumption behavior and savings. Energy and Buildings, 64, 408-414. [Link] [GScholar] [ResearchGate]
3. Chen, J., Jain, R. K., & Taylor, J. E. (2013). Block Configuration Modeling: A novel simulation model to emulate building occupant peer networks and their impact on building energy consumption. Applied Energy, 105, 358-368. [Link] [GScholar] [ResearchGate]
2. Gulbinas, R., Jain, R. K., Taylor, J. E., Peschiera, G., & Golparvar-Fard, M. (2013). Network ecoinformatics: Development of a social ecofeedback system to drive energy efficiency in residential buildings. Journal of Computing in Civil Engineering, 28(1), 89-98. [Link] [GScholar] [ResearchGate]
1. Jain, R. K., Taylor, J. E., & Peschiera, G. (2012). Assessing eco-feedback interface usage and design to drive energy efficiency in buildings. Energy and Buildings, 48, 8-17. [Link] [GScholar] [ResearchGate]
Conference Proceedings
24. Andrews, A., & Jain, R. K. (2022, November). Exploring use cases for an hourly building energy benchmarking platform: the 8760 proof-of-concept platform in New York City, NY. In Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (pp. 303-304). [Link]
23. Dougherty, T.R., Huang, T., Chen, Y., Jain, R.K. and Rajagopal, R. (2021). SCHMEAR: scalable construction of holistic models for energy analysis from rooftops. In Proceedings of the 8th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (pp. 111-120). [Link]
22. Miotti, M., & Jain, R. (2021). Modeling aggregate human mobility patterns in cities based on the spatial distribution of local infrastructure. In Proceedings of the 54th Hawaii International Conference on System Sciences (p. 1819). [Nominated for Best Paper Award] [Link]
21. Dougherty, T. R., Sonta, A., & Jain, R. K. (2020). Intelligent network topology based post-pandemic reintroduction policies for offices. In Proceedings of the 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (pp. 258-261). [Link]
20. Sonta, A. J. & Jain, R. K. (2019). Data-Driven Building Layout Optimization for Energy Efficiency. In Proceedings of the 11th International Conference on Applied Energy (ICAE2019), Västerås, Sweden.
19. Shivaram, R., & Jain, R. K. (2019). A Framework For Estimating The Impacts of Land Use Change on Urban Energy Self-Sufficiency. In Proceedings of the 11th International Conference on Applied Energy (ICAE2019), Västerås, Sweden.
18. Roth, J., Bailey, A., Choudhary, S., & Jain, R. K. (2019). Spatial and Temporal Modeling of Urban Building Energy Consumption Using Machine Learning and Open Data. In Proceedings of the 2019 ASCE International Conference on Computing in Civil Engineering, Atlanta, GA, USA. [Link] [ResearchGate]
17. Sonta, A.J., & Jain, R. K. (2019). Optimizing Neighborhood-Scale Walkability. In Proceedings of the 2019 ASCE International Conference on Computing in Civil Engineering, Atlanta, GA, USA. [Link] [ResearchGate]
16. Yang, Z., Gupta, K., & Jain, R. K. (2018). DUE-A: Data-driven Urban Energy Analytics for understanding relationships between building energy use and urban systems. In Proceedings of the 10th International Conference on Applied Energy (ICAE2018), Hong Kong, China. [Link]
15. Sonta, A. J., & Jain, R. K. (2018). Inferring occupant ties: automated inference of occupant network structure in commercial buildings. In Proceedings of the 5th Conference on Systems for Built Environments (BuildSys '18), Shenzen, China. [Link] [ResearchGate]
14. Roth, J., & Jain. R.K. (2018). Data-Driven, Multi-metric, and Time-Varying (DMT) Building Energy Benchmarking Using Smart Meter Data. In Proceedings of the 25th International Workshop on Intelligent Computing in Engineering (EG-ICE 2018), Lausanne, Switzerland. [Link] [ResearchGate]
13. Nutkiewicz, A., Yang, Z., & Jain, R. K. (2017). Data-driven Urban Energy Simulation (DUE-S): Integrating machine learning into an urban building energy simulation workflow. In Proceedings of the 9th International Conference on Applied Energy (ICAE2017), Cardiff, UK. [Link]
12. Debnath, R., Bardhan, R., & Jain, R. K. (2017). A Data-Driven and Simulation Approach for Understanding Thermal Performance of Slum Redevelopment in Mumbai, India. In Proceedings of the 2017 Building Simulation Conference (IBPSA 2017), San Francisco, CA, USA. [Link]
11. Yang, Z., Gupta, K., Gupta, A., & Jain, R. K. (2017). A Data Integration Framework for Urban Systems Analysis Based on Geo-Relationship Learning. In Proceedings of the ASCE International Workshop on Computing in Civil Engineering 2017, Seattle, WA, USA. [Link]
10. Sonta, A, Simmons, P., & Jain, R. K. (2017). Towards Automated Inference of Occupant Behavioral Dynamics Using Plug-Load Energy Data. In Proceedings of the ASCE International Workshop on Computing in Civil Engineering 2017, Seattle, WA, USA. [Link]
9. Yang, Z., Roth, J., & Jain, R. K. (2016). Data-driven benchmarking of building energy performance at the city scale. In Proceedings of the 2nd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics, Burlingame, CA, USA. [Link]
8. Gulbinas, R., & Jain, R. K. (2016). Towards the development of a visual data exploration tool to augment decision-making in urban building energy efficiency programs. In Proceedings of the 16th International Conference on Computing in Civil and Building Engineering, Osaka, Japan.
7. Jain, R. K., Gulbinas, R., Moura, J., & Taylor, J. (2015). A Spatial Analysis of Occupant Energy Efficiency by Discrete Signal Processing on Graphs. In Proceedings of the 2015 ASCE International Workshop on Computing in Civil Engineering, Austin, TX, USA. [Link]
6. Muthumanickam, A., Jain, R. K., Taylor, J., & Bulbul, T. (2014). Development of a Novel BIM-Energy Use Ontology. In Proceedings of the 2014 ASCE Construction Research Congress, Atlanta, GA, USA. [Link]
5. Jain, R. K., Damoulas, T., & Kontokosta, C. (2014). Towards Energy Consumption Forecasting of Multi-Family Residential Buildings using Machine Learning: Feature Selection via The Lasso. In Proceedings of the 2014 ASCE International Conference on Computing in Civil and Building Engineering, Orlando, FL, USA. [Link]
4. Jain, R. K., Smith, K., Culligan, P., & Taylor, J. (2013). Exploring Energy Consumption Forecasting for Multi-Family Residential Buildings Using Support Vector Regression. In Proceedings of the 8th Conference on Sustainable Development of Energy, Water and Environment Systems, Dubrovnik, Croatia.
3. Gulbinas, R., Jain, R. K., & Taylor, J. (2013). A Commercial Building Eco-Feedback System for Quantifying Organizational and Social Network Effects on Conservation. In Proceedings of the 5th International Conference on Applied Energy, Pretoria, South Africa. [Invited for Special Issue in Applied Energy journal]
2. Jain, R. K., Taylor, J., & Culligan, P. (2013). Examining the Role Information Representation in Eco-Feedback Systems has on Building Occupant Energy Consumption Behavior. In Proceedings of the 2013 CSCE Conference, Montreal Canada.
1. Gulbinas, R., Jain, R. K., Taylor, J., & Fard, M.G. (2012). Web-Based Eco-Feedback Visualization Of Building Occupant Energy Consumption in Support of Quantifying Social Network Effects on Conservation. In Proceedings of the 2012 ASCE International Conference on Computing in Civil Engineering, Clearwater Beach, FL, USA. [Link]