SURP Class of 2023
Ankita Dasgupta
Ankita Dasgupta is a rising Sophomore at Penn State. She studies Astrophysics and Astronomy and is part of the Schreyer’s Honors College. She has research experience in observational astrophysics. Her research at CMU has focused on building and comparing dark matter simulations made by N-body and AI. She believes that AI stands as a vital instrument for physicists to explore the intricacies of our universe. Ankita’s project with Dr. Rupert Croft aims to remove some of the computational constraints in size and resolution in cosmological simulations using AI. The AI is trained on N-Body generates high resolution simulations 10,00 times faster than traditional methods! She nurtures a deep interest in Astrophysics, Statistics and Coding and aims to apply her newfound AI/ML skills in her future projects.
Elise Kesler
Elise Kesler is a rising senior at the University of Michigan, Ann Arbor, where she studies physics and astronomy. She believes AI has the capability to transform cosmology research, and is particularly thrilled by its application in the domains of dark energy and galactic evolutionary research. Having gained more familiarity with AI under the guidance of Professor Antonella Palmese, she hopes to continue applying it to her research in graduate school and beyond. Outside of the realm of physics, she enjoys yoga, writing, and playing with her cat and dog.
Mulundano Machiya
Mulundano Machiya is a rising junior from Xavier University of Louisiana who is studying physics with a double minor in computer science and mathematics. He has had experience in both an environmental physics research group and a computational chemistry lab. These experiences really engaged him to understand computation and its application to his field. Throughout his undergraduate career, Mulundano has been extremely interested in quantum physics, especially with its applications in quantum computation. This was emphasized with Mulundano’s work in the program, under Dr Michael Widom from the CMU Physics Department and Dr Xiao Liang from the Pittsburg Supercomputing Center, focused on the simulation of the ground state of Rydberg atom arrays using convolutional neural networks. The SURP was his first connection to machine learning, and it has unlocked a new area of exploration for him because of its potential to bridge gaps in fields like quantum simulation. He hopes to carry on expanding on the work he has started in the SURP and make further connections between quantum computation and machine learning.
Aleczander Paul
Aleczander Paul is a rising senior at the University of Hawaii at Manoa. He has research experience in particle physics at his home institution, and is excited to learn how machine learning can be used in those types of experiments during this SURP. He believes that machine learning is a great tool to aid physicists in furthering our understanding of the universe, and hopes to take what he learns during his research here and apply it to future research projects. With Dr. Valentina Dutta as his advisor, he trained an AI model called ParticleNet to separate background processes from dark matter signals on simulated data for the Light Dark Matter Experiment (LDMX), with the hopes that the model can be used on the experimental data to identify dark matter signal events if/when they are produced by the fixed-target experiment.
Jose Wui
Jose is a rising senior at the University of Texas at Austin. He is a computational physics major with a certificate in computer science. As a young boy, he was mesmerized by the ubiquity of physics in everyday life. He rediscovered his passion for it in high school and now hopes to pursue a PhD in physics. He was previously involved in Magnetic Resonance Force Microscopy and optical physics research. For this summer, he will be conducting research in the field of computational crystal structure prediction under the guidance of Professor Noa Marom. In his spare time, Jose enjoys playing the piano and the guitar (not at the same time), singing, and dancing hip-hop.
Aiken Xie
Aiken is a rising junior at Carnegie Mellon majoring in physics. He is very excited to work with Prof. Cremonesi and the CMS experiment. Aiken will be using AI in the search for dark matter in reconstruction of physical quantities from data collected from the detectors at the Large Hadron Collider. He is also hoping this experience will help him gain more insight into life as a graduate student and figure out if graduate school is the right choice for 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.
