Summary
Edgar Vidal is a PhD student and researcher in astrophysics at Tufts University who blends simulation-based inference and machine learning to accelerate inference for galaxy evolution and transient detection in large surveys like LSST. With hands-on experience from ZTF candidate vetting to nightly telescope observing and developing spectral analysis tools for Type Ia supernovae, he pairs practical observational skills with computational rigor. He has a background in nanophotonics research and a track record of award-winning ML-for-astronomy work from competitive hackathons. Outside academia he brings seven years of service and management experience in the restaurant sector, which informs his operational discipline and team leadership. Based in Greater Boston, Edgar focuses on building scalable, cost-effective data pipelines that make next-generation survey science more efficient and reproducible.
7 years of coding experience