I love exploring new technologies. For the last year, I’ve been using generative AI to build CountOn - an entirely new type of shopping experience where we use LLMs to summarize the knowledge of trusted experts in order to help people make better purchase decisions. Prior to CountOn, I spent five years at Amazon where I led sustainable customer research and helped launch The Climate Pledge (Amazon's commitment to be net zero carbon by 2040). Before that, I was a scientist at the National Renewable Energy Laboratory where I did some of the earliest research in augmented reality shopping tools, smart transportation, and home energy management systems.
Steve Isley
Ph.D. trained research scientist with deep expertise in sustainable consumption and applied generative AI
Research Expertise
About
Publications
Foresee: A user-centric home energy management system for energy efficiency and demand response
Applied Energy / Nov 01, 2017
Jin, X., Baker, K., Christensen, D., & Isley, S. (2017). Foresee: A user-centric home energy management system for energy efficiency and demand response. Applied Energy, 205, 1583–1595. https://doi.org/10.1016/j.apenergy.2017.08.166
The effect of near-term policy choices on long-term greenhouse gas transformation pathways
Global Environmental Change / Sep 01, 2015
Isley, S. C., Lempert, R. J., Popper, S. W., & Vardavas, R. (2015). The effect of near-term policy choices on long-term greenhouse gas transformation pathways. Global Environmental Change, 34, 147–158. https://doi.org/10.1016/j.gloenvcha.2015.06.008
An application of the Analytic Hierarchy Process for prioritizing user preferences in the design of a Home Energy Management System
Sustainable Energy, Grids and Networks / Dec 01, 2018
Kadavil, R., Lurbé, S., Suryanarayanan, S., Aloise-Young, P. A., Isley, S., & Christensen, D. (2018). An application of the Analytic Hierarchy Process for prioritizing user preferences in the design of a Home Energy Management System. Sustainable Energy, Grids and Networks, 16, 196–206. https://doi.org/10.1016/j.segan.2018.07.009
User-preference-driven model predictive control of residential building loads and battery storage for demand response
2017 American Control Conference (ACC) / May 01, 2017
Jin, X., Baker, K., Isley, S., & Christensen, D. (2017, May). User-preference-driven model predictive control of residential building loads and battery storage for demand response. 2017 American Control Conference (ACC). https://doi.org/10.23919/acc.2017.7963592
Online purchasing creates opportunities to lower the life cycle carbon footprints of consumer products
Proceedings of the National Academy of Sciences / Aug 15, 2016
Isley, S. C., Stern, P. C., Carmichael, S. P., Joseph, K. M., & Arent, D. J. (2016). Online purchasing creates opportunities to lower the life cycle carbon footprints of consumer products. Proceedings of the National Academy of Sciences, 113(35), 9780–9785. https://doi.org/10.1073/pnas.1522211113
Using augmented reality to inform consumer choice and lower carbon footprints
Environmental Research Letters / May 01, 2017
Isley, S. C., Ketcham, R., & Arent, D. J. (2017). Using augmented reality to inform consumer choice and lower carbon footprints. Environmental Research Letters, 12(6), 064002. https://doi.org/10.1088/1748-9326/aa6def
An Evolutionary Model of Industry Transformation and the Political Sustainability of Emission Control Policies
Jan 01, 2013
An Evolutionary Model of Industry Transformation and the Political Sustainability of Emission Control Policies. (2013). RAND Corporation. https://doi.org/10.7249/tr1308
Dirty dishes or dirty laundry? Comparing two methods for quantifying American consumers' preferences for load management in a smart home
Energy Research & Social Science / Jan 01, 2021
Aloise-Young, P. A., Lurbe, S., Isley, S., Kadavil, R., Suryanarayanan, S., & Christensen, D. (2021). Dirty dishes or dirty laundry? Comparing two methods for quantifying American consumers’ preferences for load management in a smart home. Energy Research & Social Science, 71, 101781. https://doi.org/10.1016/j.erss.2020.101781
Assessment of Carbon Dioxide Emission Metric Systems for an Aircraft Certification Standard
Journal of Aircraft / Mar 01, 2014
Lim, D., Kirby, M., Nam, T., Burdette, G., Yutko, B., Hansman, R. J., Mozdzanowska, A., & Bonnefoy, P. A. (2014). Assessment of Carbon Dioxide Emission Metric Systems for an Aircraft Certification Standard. Journal of Aircraft, 51(2), 559–570. https://doi.org/10.2514/1.c032279
Homeowner Preference Elicitation
Proceedings of the 3rd ACM International Conference on Systems for Energy-Efficient Built Environments / Nov 16, 2016
Christensen, D., Isley, S., Baker, K., Jin, X., Aloise-Young, P., Kadavil, R., & Suryanarayanan, S. (2016, November 16). Homeowner Preference Elicitation: A Multi-Method Comparison: Poster Abstract. Proceedings of the 3rd ACM International Conference on Systems for Energy-Efficient Built Environments. https://doi.org/10.1145/2993422.2996409
Electronic Surveillance of Mobile Devices: Understanding the Mobile Ecosystem and Applicable Surveillance Law
Jan 01, 2015
Balkovich, E., Prosnitz, D., Boustead, A., & Isley, S. (2015). Electronic Surveillance of Mobile Devices: Understanding the Mobile Ecosystem and Applicable Surveillance Law. RAND Corporation. https://doi.org/10.7249/rr800
Modernizing the U.S. Air Force Base Level Automation System
Jan 01, 1981
Modernizing the U.S. Air Force Base Level Automation System: A Report to the U.S. Air Force. (1981). National Academies Press. https://doi.org/10.17226/19728
An Overview of Technologies for Individual Trip History Collection: Mobility Decision Science Pillar SMART Mobility Consortium
Jan 04, 2019
Kwasnik, T., Carmichael, S. P., & Isley, S. C. (2019). An Overview of Technologies for Individual Trip History Collection: Mobility Decision Science Pillar SMART Mobility Consortium. Office of Scientific and Technical Information (OSTI). https://doi.org/10.2172/1490251
Assessing the impact of farmer field schools on fertilizer use in China
Mar 01, 2015
Burger, N., Fu, M., Gu, K., Jia, X., B Kumar, K., & Mingliang, G. (2015). Assessing the impact of farmer field schools on fertilizer use in China. International Initiative for Impact Evaluation. https://doi.org/10.23846/ow31216
The Trip Itinerary Optimization Platform: A Framework for Personalized Travel Information
Nov 21, 2017
Kwasnik, T., Carmichael, S. P., Arent, D. J., Sperling, J., & Isley, S. (2017). The Trip Itinerary Optimization Platform: A Framework for Personalized Travel Information. Office of Scientific and Technical Information (OSTI). https://doi.org/10.2172/1410410
Aircraft Valuation: A Network Approach to the Evaluation of Aircraft for Fleet Planning and Strategic Decision Making
10th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference / Jun 25, 2010
Justin, C., Garcia, E., & Mavris, D. (2010, June 25). Aircraft Valuation: A Network Approach to the Evaluation of Aircraft for Fleet Planning and Strategic Decision Making. 10th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference. https://doi.org/10.2514/6.2010-9061
Helping Law Enforcement Use Data from Mobile Applications: A Guide to the Prototype Mobile Information and Knowledge Ecosystem (MIKE) Tool
Jan 01, 2017
Balkovich, E., Prosnitz, D., Isley, S., Boustead, A., & Triezenberg, B. (2017). Helping Law Enforcement Use Data from Mobile Applications: A Guide to the Prototype Mobile Information and Knowledge Ecosystem (MIKE) Tool. RAND Corporation. https://doi.org/10.7249/rr1482
Education
Ph.D., Policy Analysis / June, 2014
Georgia Institute of Technology
MS, Aerospace Engineering / June, 2010
University of Washington
BS, Aerospace Engineering / June, 2005
Experience
CountOn
CEO / October, 2022 — February, 2024
CountOn helps people shop their values - no matter what they are. We use AI to summarize trusted product knowledge and deliver it into your regular shopping experience via a browser extension. The vision is a platform that delivers the highest quality, personalized, values-aligned recommendations into every shopping experience. In addition to being the CEO, I'm also the lead developer. I have implemented generative AI features (such as Retrieval Augmented Generation) using OpenAI, Pinecone (a vector database), and LangChain.
Amazon
Senior Research Scientist / October, 2016 — January, 2022
I led sustainable customer research for five years: dozens of people in usability studies, 100's in mobile diary studies, 10k+ in surveys, 10M+ in online A/B experiments, and 100M+ in search and purchase behavior. In 2019 I helped launch The Climate Pledge and was the company's first subject matter expert on carbon offsets in support of the $100M Right Now Climate Fund. I led a project using ML to identify sustainable products and built a new sustainable shopping experience that generated over $100 million in incremental revenue. This involved collecting training data by building a Mechanical Turk task (Javascript, JQuery, CSS/HTML), preprocessing and cleaning that data (RedShift, SQL, R), training ML models (S3, SageMaker, XGBoost & other algorithms), batch processing big data, generating recommendations, and conducting A/B tests.
National Renewable Energy Laboratory
Behavioral Scientist / July, 2014 — October, 2016
At NREL, I introduced behavioral science research techniques to teams throughout the lab. I built an augmented reality Android app (Java, Vuforia SDK, and OpenGL ES) that incorporated carbon information into consumer good purchasing decisions and performed a randomized controlled trial at a local grocery store. The app provided personalized recommendations and led to a decrease in the average carbon footprint of purchased products and to healthier food choices. My work in smart home energy management systems contributed to a 2018 R&D 100 award (given annually by R&D Magazine, the award honors the 100 most innovative technologies of the past year). I was also involved with the design, programming, and testing of an Android app that monitors transportation related choices and suggested alternatives. This involved creating and running user-interface tests using Amazon Mechanical Turk. The experiments were coded in Javascript (with jQuery, Backbone, and Bootstrap).
The RAND Corporation
Assistant Policy Analyst / September, 2010 — April, 2016
As an assistant policy analyst I navigated RAND's internal labor market. This involved networking with colleagues, getting on projects, and billing hours.
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