Jorge Silveyra | Photo by Adam Atkinson
What I study and why: I focus on tackling energy insecurity for low-income households. Programs like the Low Income Home Energy Assistance Program (LIHEAP) help, but we lack effective tools to optimally allocate resources. My research uses computational approaches and machine learning (ML) to enhance resource distribution and reduce energy inequality.
In the U.S., economic disparities worsen energy insecurity, making it hard for low-income families to pay their energy bills or afford energy-efficient upgrades. My work involves using the urban building energy model (UBEM) and ML techniques to analyze data and predict the impact of various strategies. This helps policymakers optimize fund allocation, aiming for long-term benefits and fairer energy policies that promote socioeconomic stability and sustainability.
This fall, I’m teaching: Database Management Systems and Principles of Data Science. I’m super excited to teach both CS majors and non-majors. It’s awesome to help students with no CS background learn new concepts, and I’m looking forward to meeting the majors and growing together.
What students can expect from me: My classes are very interactive, challenging (in a good way), and casual. I believe a great class allows students to discover new things on their own with guidance from me. I’m thrilled when my students accomplish tasks they thought were impossible or uncover skills they didn’t know they had. I strive to be involved with my students as individuals and be part of their journeys throughout their college years.
Getting to know me: I love video games! Zelda, Mario, and many others—feel free to challenge me to a Mario Kart race. You’ll probably see me at the gym, so please say hi! You might also spot me on the D&L Trail on weekends—I’m always up for cycling with friends!
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