SURP Class of 2021
Bryant Dean
Bryant Dean is a rising senior at Morehouse College. He has experience teaching STEM to elementary school students, and is adept at programming. He is hoping this program will answer some of the questions he has about dark matter, black holes, general relativity, and the wider universe.
Duy Hoang
Duy Hoang is a rising senior at Carnegie Mellon. He has conducted research with Prof. Diana Parno's group, where he contributed simulations and modeling to the COHERENT collaboration. He is excited to explore how AI can further our understanding of the Higgs Boson.
Bristy Islam
Bristy Islam is a rising senior at Penn State. She is passionate about astronomy, with academic experience in pure mathematics, coding, and robotics. She is excited to delve into applied mathematics and AI at the intersection of astrophysics.
Meris Sipp
Meris Sipp is a rising senior at Carnegie Mellon. They have utilized computational physics in both astrophysics and particle physics applications. They hope this program will prepare them to pursue a Ph.D. in astrophysics.
Zivan Vasquez
Zivan Vasquez is a rising senior at Carnegie Mellon. He has research experience in astrophysics and condensed matter physics. He is excited to see how machine learning can be applied to the field of cosmology.
Zivan conducted statistical astrophysics research with professors Dodelson and Schafer.
Runxuan Wang
Runxuan Wang is a rising senior at Carnegie Mellon. He has participated in undergraduate research in biological physics, investigating antimicrobial peptides, and in particle physics, focusing on b-quark jets. He recognizes AI as the key to progressing physics research, and is excited to further his understanding of fundamental physics.
Jonah Warner
Jonah Warner is a rising senior at Penn State. He has a wide understanding of mathematics and physics concepts, and an even wider breadth of physics-related interests. He is hoping delving into research with this program will inspire him to narrow his focus between the many subfields that fascinate him.
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.
