Bio


Professor Jain's research focuses on the development of data-driven and socio-technical solutions to sustainability problems facing the urban built environment. His work lies at the intersection of civil engineering, data analytics and social science. Recently, his research has focused on understanding the socio-spatial dynamics of commercial building energy usage, conducting data-driven benchmarking and sustainability planning of urban buildings and characterizing the coupled dynamics of urban systems using data science and micro-experimentation. For more information, see the active projects on his lab (Stanford Urban Informatics Lab) website.

Academic Appointments


  • Assistant Professor, Civil and Environmental Engineering

Honors & Awards


  • Science, Engineering and Education for Sustainability (SEES) Fellow, National Science Foundation (2014)

Professional Education


  • PhD, Columbia University, Civil Engineering
  • MS, Columbia University, Civil Engineering
  • BS, University of Texas at Austin, Civil, Environmental & Architectural Engineering

Projects


  • Data-driven Sustainable Upgradation of Dharavi Informal Settlement (Mumbai, India), Stanford University

    Location

    Mumbai, India

    Collaborators

    • Ronita Bardhan, Assistant Professor, Indian Institute of Technology - Bombay

Stanford Advisees


All Publications


  • 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 Nutkiewicz, A., Yang, Z., Jain, R. K. ELSEVIER SCI LTD. 2018: 1176–89
  • Understanding building occupant activities at scale: An integrated knowledge-based and data-driven approach Sonta, A. J., Simmons, P. E., Jain, R. K. ELSEVIER SCI LTD. 2018: 1–13
  • A review of occupant energy feedback research: Opportunities for methodological fusion at the intersection of experimentation, analytics, surveys and simulation APPLIED ENERGY Khosrowpour, A., Jain, R. K., Taylor, J. E., Peschiera, G., Chen, J., Gulbinas, R. 2018; 218: 304–16
  • DUE-B: Data-driven urban energy benchmarking of buildings using recursive partitioning and stochastic frontier analysis ENERGY AND BUILDINGS Yang, Z., Roth, J., Jain, R. K. 2018; 163: 58–69
  • OESPG: Computational Framework for Multidimensional Analysis of Occupant Energy Use Data in Commercial Buildings JOURNAL OF COMPUTING IN CIVIL ENGINEERING Sonta, A. J., Jain, R. K., Gulbinas, R., Moura, J. M., Taylor, J. E. 2017; 31 (4)
  • Data-driven planning of distributed energy resources amidst socio-technical complexities Nature Energy Jain, R. K., Qin, J., Rajagopal, R. 2017

    View details for DOI 10.1038/nenergy.2017.112

  • Towards Automated Inference of Occupant Behavioral Dynamics Using Plug-Load Energy Data Sonta, A. J., Simmons, P. E., Jain, R. K., Lin, K. Y., ElGohary, N., Tang, P. AMER SOC CIVIL ENGINEERS. 2017: 290–97
  • A Data Integration Framework for Urban Systems Analysis Based on Geo-Relationship Learning Yang, Z., Gupta, K., Gupta, A., Jain, R. K., Lin, K. Y., ElGohary, N., Tang, P. AMER SOC CIVIL ENGINEERS. 2017: 467–74
  • Modeling the determinants of large-scale building water use: Implications for data-driven urban sustainability policy SUSTAINABLE CITIES AND SOCIETY Kontokosta, C. E., Jain, R. K. 2015; 18: 44-55
  • BizWatts: A modular socio-technical energy management system for empowering commercial building occupants to conserve energy APPLIED ENERGY Gulbinas, R., Jain, R. K., Taylor, J. E. 2014; 136: 1076-1084
  • The impact of combined water and energy consumption eco-feedback on conservation ENERGY AND BUILDINGS Jeong, S. H., Gulbinas, R., Jain, R. K., Taylor, J. E. 2014; 80: 114-119
  • Big Data plus Big Cities: Graph Signals of Urban Air Pollution IEEE SIGNAL PROCESSING MAGAZINE Jain, R. K., Moura, J. M., Kontokosta, C. E. 2014; 31 (5): 130-136
  • 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 Jain, R. K., Smith, K. M., Culligan, P. J., Taylor, J. E. 2014; 123: 168-178
  • Network Ecoinformatics: Development of a Social Ecofeedback System to Drive Energy Efficiency in Residential Buildings JOURNAL OF COMPUTING IN CIVIL ENGINEERING Gulbinas, R., Jain, R. K., Taylor, J. E., Peschiera, G., Golparvar-Fard, M. 2014; 28 (1): 89-98
  • 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 Jain, R. K., Gulbinas, R., Taylor, J. E., Culligan, P. J. 2013; 66: 119-127
  • Investigating the impact eco-feedback information representation has on building occupant energy consumption behavior and savings ENERGY AND BUILDINGS Jain, R. K., Taylor, J. E., Culligan, P. J. 2013; 64: 408-414
  • Block Configuration Modeling: A novel simulation model to emulate building occupant peer networks and their impact on building energy consumption APPLIED ENERGY Chen, J., Jain, R. K., Taylor, J. E. 2013; 105: 358-368
  • Assessing eco-feedback interface usage and design to drive energy efficiency in buildings ENERGY AND BUILDINGS Jain, R. K., Taylor, J. E., Peschiera, G. 2012; 48: 8-17