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Research
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Posts
Explaining Residential Electricity Consumption with Satellite Imagery and GANs
Published:
Some of our research combining residential electricity consumption and satellite imagery. Work done in collaboration with Terry Conlon, Jay Taneja, Vijay Modi in the Quadracci Sustainable Engineering Lab(QSEL) & Systems Towards Infrastructure Monitoring & Analytics (STIMA) Lab. Link Here
Blurry no more?! Using Deep Learning to Harmonize Satellite Imagery Across Resolutions
Published:
Checkout how I spent Summer 2019 as an Applied Science Intern at Descartes Labs. This work was done in collaboration with Clyde Wheeler. Link Here
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
Paper Title Number 1
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1). http://academicpages.github.io/files/paper1.pdf
Paper Title Number 2
Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf
Paper Title Number 3
Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3). http://academicpages.github.io/files/paper3.pdf
talks
Challenges and Gaps during Energy Disruptions
Published:
This was a panel discussion on the challenges and gaps which may occur or arise with energy disruptions. Energy disruptions may include climate change or new technologies and or regulations.
Decision Support Metrics for Electricity Planning
Published:
This talk demonstrated a two-stage electricity planning approach. Building locations and merging algorithms were used to apporximate residential locations, used as demand nodes for network planning. Given residential nodes, electricity access metrics (low voltage wire length, medium voltage wire length, transformer density and the cost of electrification) are estimated for wards in Kenya. These metrics highlight opportunities for varying electricity technologies (solar, minigrid, full-scale grid).
Using Remote Sensed Data to Understand & Predict Residential Electricity Demand
Published:
Won Best Poster Award
Opportunities and Challenges for Machine Learning in the African Electricity Sector
Published:
This session highlighted impactful work at the intersection of climate change, electricity, and machine learning in a variety of African contexts. Topics addressed will include energy access, load forecasting, and data mining for electricity system data. Watch session HERE
Learning to segment from misaligned and partial labels
Published:
Presented our accepted paper at ACM COMPASS 2020.
Leveraging demand data for improved energy access planning
Published:
The webinar can be watched here
How Remote Sensing Can Be of Value to the Energy Sector
Published:
Abstract: Recent work has demonstrated how one can use daytime satellite imagery to assist the prediction of individual residential building consumption levels upon connection. Using six years of longitudinal data of electricity consumption for a large cross-section of grid customers from Kenya, we apply convolutional neural networks (CNNs) to daytime satellite images to predict expected levels of residential electricity consumption for individual customers throughout the country.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.