My Projects
A LiDAR-based Evaluation of Rooftop Solar Potential in DeLand, Florida
The state of Florida, with access to abundant sunlight, is well positioned to transition from fossil fuel dependency to solar energy. Encouraging residential solar panel installations, particularly in small cities like DeLand, is a crucial aspect of this transition. Light Detection and Ranging (LiDAR) surveys enable detailed maps of residential neighborhoods, thereby permitting homeowners to…
Detecting Repeating Radar-like Signals from Alien Worlds
The Search for Extraterrestrial Intelligence (SETI) endeavors to find evidence of advanced alien life in the Universe through signatures of their technologies. Historically, SETI programs have focused mainly on the discovery and follow-up of one-off narrowband (\(\sim\) 1 Hz bandwidth), hard-to-explain events. In contrast, repeating broadband signals analogous to radar offer an…
Mapping Historical Crop Yields across India
Maps offer an intuitive means to represent the spatial distribution of data, helping users understand the geographic context and relationships between different locations. With human-induced climate change a reality, understanding evolutionary patterns in nationwide crop yields is essential to ensure food sustainability. India is the world’s second-largest producer of rice, wheat, sugarcane…
Geomechanics for CO\(_2\) Sequestration
Carbon sequestration involves capturing CO\(_2\) from factories or directly from the air and storing it underground as a supercritical fluid. Geologic carbon capture and storage is required to meet global carbon neutrality goals, with over 30 gigatons of CO\(_2\) storage needed in the US alone by 2050. However, subsurface carbon storage comes with a catch. One may artificially induce…
Predicting Fertilizer Input for Rice Cultivation in India
Home to over 1.38 billion people, India is tackling a severe hunger crisis. Though the country has achieved self-sufficiency in grain production, nearly 14% of the population is still undernourished. India’s agricultural landscape is primarily rural, where widespread poverty, low literacy rates, and poor infrastructure lead to questions over its sustainability. Indiscriminate use of fertilizers…
Convolutional Neural Networks for Signal Classification in Radio Astronomy
Radio waves from human technologies frequently interfere with searches for exotic astrophysical phenomena, yielding hordes of false positives in downstream signal detection pipelines. Discerning astronomical signals of interest from a pile of false positives presents a “needle in a haystack” challenge demanding significant human time investment. Implementing interference blocking at telescope…