Research project · 2023–2024
Measuring change
from space.
Nighttime lights and vegetation indices as evidence of change. A closer look at what a measurement can tell us—and what it leaves uncertain.
- Remote sensing
- VIIRS data
- Measurement
Columbia University / New York
Hello, I’m
I’m a Columbia student interested in reliable machine learning, thoughtful evaluation, and software that people can use.
Computer Science & Mathematics Statistics minor
01 / Selected work
Research project · 2023–2024
Nighttime lights and vegetation indices as evidence of change. A closer look at what a measurement can tell us—and what it leaves uncertain.
Web application · 2026
A calendar for hackathons and competitions, with deadlines, filters, and the context behind each listing.
02 / Publication & experience
Conference paper · 2024 · Coauthor
Fifth International Conference on Computer Vision and Data Mining (ICCVDM 2024)
A collaborative study of vehicle classification using deep learning and multisensor fusion.
C networking, memory tracing, and course-server work, with attention to how implementation choices affect reliability.
Forecasting and modeling explorations focused on what can be inferred from incomplete data and how uncertainty affects interpretation.
Work with nighttime lights and vegetation indices as evidence of change, examining the gap between a measured signal and the conditions it represents.
03 / NOTES & IDEAS
6 min read
A practical reading method built around claims, evidence, and transfer—not exhaustive summaries.
Read essay5 min read
Questions to ask when a single benchmark number stands in for a much larger evaluation story.
Read essay4 min read
Lessons from working with VIIRS nighttime lights: proxies are powerful when their limits remain visible.
Read essayGet in touch
For research conversations, project questions, or professional opportunities.