Rohan Arni
High Technology High School
Lincroft, NJ
Deep Learning for Classification of Fast Radio Bursts
Rohan Arni, 17, of Morganville, developed a machine-learning model to analyze fast radio bursts (FRBs) for his Regeneron Science Talent Search space science project. FRBs are mysterious cosmic flashes of radio waves that last milliseconds, and sometimes repeat.
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In his project, Rohan used data from the Canadian Hydrogen Intensity Mapping Experiment, a radio telescope that maps the sky for FRBs. His model classified repeating and non-repeating FRBs with 98% accuracy. It also identified hidden properties in the data, which Rohan analyzed to conclude that repeating FRBs tend to be closer to Earth and have smaller frequency ranges. This suggests that repeaters and non-repeaters come from different places in the universe.
Presently, scientists don’t know much about FRBs and where they come from. Information from Rohan’s project could provide a tool to interpret new and available data, helping astronomers learn more about FRBs and their origins.
The child of Sunitha and Raghvender Arni, Rohan attends High Technology High School (Lincroft). He worked with researchers at Harvard University on developing NeuroDiffEq, a library for physics-informed neural networks used by researchers worldwide.
Beyond the Project
Rohan is president of his school’s robotics and coding club and has coached over 100 younger students in STEM fundamentals. He also volunteers with the Monmouth County Historical Association as a tour guide.
FUN FACTS: Rohan hates to leave a shopping cart in the middle of the parking lot and makes it a point to put it back where it belongs. He likes to think his gesture will make someone’s life easier.
