SURP Class of 2022
Gabrielle-Marie Cosmiano
Gabrielle-Marie Cosmiano is a rising junior at the University of Pittsburgh. She is passionate about physics and astronomy, with academic experience in both physics and pure mathematics. She is excited to dive into the world of machine learning and learn more about the field of cosmology. She also hopes that this program prepares and inspires her to pursue a Ph.D. in either physics or mathematics.
Gabrielle-Marie's Poster
Rose Hudson
Rose Hudson is a rising senior at Penn State. She is an enthusiastic astrophysicist but holds a wide variety of interests, having previous experience in a psychology lab and working towards medical school. Her SURP experience is helping her branch into biophysics under Professor Fangwei Si. She enjoys exploring new and collaborative approaches to whichever field she's working in.
Manami Kanemura
Manami Kanemura is a rising fifth-year at Northeastern. She sees potential in machine learning applied to physics, especially particle physics. After experiencing research in particle physics and deep learning, she is thrilled to explore how deep learning can deepen our understanding of The Standard Model and help us find new physics.
Joyce Lin
Joyce Lin is a rising senior at Carnegie Mellon. She was previously involved in astrophysics research resulting in a publication about a computational method to detect features in strong gravitationally lensed images. She hopes that this program will teach her about how machine learning can be applied in astrophysics and be used in the search for information about dark matter. In her spare time, she enjoys visiting a local cat cafe and volunteers at the local senior center near CMU.
Setayesh Nekarae
Setayesh is a 5th year undergraduate student at UCLA. At her home institution, she has been involved in biophysics and condensed matter research. This summer she will be involved in computation work as it relates to the higgs-boson pair production under the guidance of Prof. Alison and Prof. Kuusela. In her free time she enjoys baking, hiking and taking long naps.
This material is based upon work supported by the National Science Foundation under the NSF AI Planning Institute for Data-Driven Discovery in Physics, grant number PHY2020295. Any opinions, findings, and conclusions or recommendations expressed on this website are those of the participants and do not necessarily reflect the views of the National Science Foundation or the participating institutions.
