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

Contact

  • rishee.jain@stanford.edu
    University - Faculty Department: Civil and Environmental Engineering Position: Assistant Professor

Additional Info

  • Mail Code: 4020

Links

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

2018-19 Courses

Stanford Advisees

All Publications

  • Understanding the adoption and usage of data analytics and simulation among building energy management professionals: A nationwide survey BUILDING AND ENVIRONMENT Srivastava, C., Yang, Z., Jain, R. K. 2019; 157: 139–64

    View details for DOI 10.1016/j.buildenv.2019.04.016

    View details for Web of Science ID 000471114800014

  • Urban Data Integration Using Proximity Relationship Learning for Design, Management, and Operations of Sustainable Urban Systems JOURNAL OF COMPUTING IN CIVIL ENGINEERING Gupta, K., Yang, Z., Jain, R. K. 2019; 33 (2)

    View details for DOI 10.1061/(ASCE)CP.1943-5487.0000806

    View details for Web of Science ID 000457272200001

  • DUE-A: Data-driven Urban Energy Analytics for understanding relationships between building energy use and urban systems Yang, Z., Gupta, K., Jain, R. K., Yan, J., Yang, H. X., Li, H., Chen ELSEVIER SCIENCE BV. 2019: 6478–83

    View details for DOI 10.1016/j.egypro.2019.01.114

    View details for Web of Science ID 000471031706128

  • 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

    View details for DOI 10.1016/j.apenergy.2018.05.023

    View details for Web of Science ID 000438181000090

  • 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

    View details for DOI 10.1016/j.aei.2018.04.009

    View details for Web of Science ID 000438320300001

  • 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

    View details for DOI 10.1016/j.apenergy.2018.02.148

    View details for Web of Science ID 000430994500026

  • 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

    View details for DOI 10.1016/j.enbuild.2017.12.040

    View details for Web of Science ID 000428485100006

  • Inferring Occupant Ties Automated Inference of Occupant Network Structure in Commercial Buildings Sonta, A. J., Jain, R. K., Ramachandran, G. S., Batra, N. ASSOC COMPUTING MACHINERY. 2018: 126–29

    View details for DOI 10.1145/3276774.3276779

    View details for Web of Science ID 000458157100016

  • 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)

    View details for DOI 10.1061/(ASCE)CP.1943-5487.0000663

    View details for Web of Science ID 000399894800017

  • 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

    View details for Web of Science ID 000425807900035

  • Intestinal Enteroendocrine Lineage Cells Possess Homeostatic and Injury-Inducible Stem Cell Activity Cell Stem Cell Yan, K., Gevaert, O., Zheng, G., Anchang, B., Probert, C., et al 2017; 21 (1): 78 - 90.e6

    Abstract

    Several cell populations have been reported to possess intestinal stem cell (ISC) activity during homeostasis and injury-induced regeneration. Here, we explored inter-relationships between putative mouse ISC populations by comparative RNA-sequencing (RNA-seq). The transcriptomes of multiple cycling ISC populations closely resembled Lgr5+ISCs, the most well-defined ISC pool, but Bmi1-GFP+cells were distinct and enriched for enteroendocrine (EE) markers, including Prox1. Prox1-GFP+cells exhibited sustained clonogenic growth in vitro, and lineage-tracing of Prox1+cells revealed long-lived clones during homeostasis and after radiation-induced injury in vivo. Single-cell mRNA-seq revealed two subsets of Prox1-GFP+cells, one of which resembled mature EE cells while the other displayed low-level EE gene expression but co-expressed tuft cell markers, Lgr5 and Ascl2, reminiscent of label-retaining secretory progenitors. Our data suggest that the EE lineage, including mature EE cells, comprises a reservoir of homeostatic and injury-inducible ISCs, extending our understanding of cellular plasticity and stemness.

    View details for DOI 10.1016/j.stem.2017.06.014

    View details for PubMedCentralID PMC5642297

  • 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

    View details for Web of Science ID 000425807900056

  • 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

  • Data-driven Urban Energy Simulation (DUE-S): Integrating machine learning into an urban building energy simulation workflow Nutkiewicz, A., Yang, Z., Jain, R. K., Yan, J., Wu, J., Li, H. ELSEVIER SCIENCE BV. 2017: 2114–19

    View details for DOI 10.1016/j.egypro.2017.12.614

    View details for Web of Science ID 000452901602041

  • Poster Abstract: Towards City-Scale Building Energy Performance Benchmarking Yang, Z., Roth, J., Jain, R. K., ACM ASSOC COMPUTING MACHINERY. 2016: 241–42

    View details for DOI 10.1145/2993422.2996408

    View details for Web of Science ID 000433381300040

  • Data-Driven Benchmarking of Building Energy Performance at the City Scale Yang, Z., Roth, J., Jain, R. K., ACM ASSOC COMPUTING MACHINERY. 2016

    View details for DOI 10.1145/3007540.3007541

    View details for Web of Science ID 000391514000001

  • Poster abstract: A data-driven design framework for urban slum housing - Case of Mumbai Debnath, R., Bardhan, R., Jain, R. K., ACM ASSOC COMPUTING MACHINERY. 2016: 239–40

    View details for DOI 10.1145/2993422.2996406

    View details for Web of Science ID 000433381300039

  • 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

    View details for DOI 10.1016/j.scs.2015.05.007

    View details for Web of Science ID 000367397500005

  • 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

    View details for DOI 10.1016/j.apenergy.2014.07.034

    View details for Web of Science ID 000345725800104

  • 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

    View details for DOI 10.1016/j.enbuild.2014.05.013

    View details for Web of Science ID 000343949400011

  • 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

    View details for DOI 10.1109/MSP.2014.2330357

    View details for Web of Science ID 000346043600014

  • 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

    View details for DOI 10.1016/j.apenergy.2014.02.057

    View details for Web of Science ID 000336017400017

  • 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

    View details for DOI 10.1061/(ASCE)CP.1943-5487.0000319

    View details for Web of Science ID 000333446100009

  • 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

    View details for DOI 10.1016/j.enbuild.2013.06.029

    View details for Web of Science ID 000327904200013

  • 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

    View details for DOI 10.1016/j.enbuild.2013.05.011

    View details for Web of Science ID 000323629100043

  • 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

    View details for DOI 10.1016/j.apenergy.2012.12.036

    View details for Web of Science ID 000316831800036

  • 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

    View details for DOI 10.1016/j.enbuild.2011.12.033

    View details for Web of Science ID 000302669300002