© 2016 by Stanford Urban Informatics Lab

External citation information: [Google Scholar] [ResearchGate]

Journal Publications

21. Sonta, A. J., Jain, R. K. (in press). Building Relationships: Using Embedded Plug Load Sensors for Occupant Network Inference. IEEE Embedded Systems Letters. [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

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 LearningIn 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]