Undergraduate Research & Scholarships

Aren Martinian

In the past few years, neural networks have gone from obscure to ubiquitous. This technology is shockingly versatile, but conceptually ill-understood: there is a large gap between practice and theory, and much has yet to even be conjectured. For example, scientists are baffled by the overfitting paradox. Overfitting is usually a problem when programmers model a complex system such as the brain. Programmers must base their model on finitely many examples of that system’s behavior. Traditionally, programs that perfectly replicate these examples forget the underlying system. Surprisingly, large neural networks […]

Joshua Ho

Particle physicists seek to understand particles and the physical laws governing their interactions by building particle colliders. These colliders provide a large amount of data, and due to the probabilistic nature of particle physics, researches are turning towards ML to model complex physical processes. With the rise of foundational models like ChatGPT, particle physicists have been inspired to create a large scale, general purpose model that has been trained on a vast amount of data to serve as a strong starting point for various specific tasks, that can be fine-tuned […]

Keon Abedi

This project will investigate how the frequency of a mutation changes over time when in the presence of correlated environmental noise. This is an open question in the biophysics of evolutionary dynamics, which seeks a quantitative framework for Darwin’s theory of natural selection. The core idea of evolution is that a mutation’s frequency tends to increase over generations when it offers an advantage to its hosts. For example, in an environment with antibiotics, mutations conferring antibiotic resistance are strongly favored and can quickly become prevalent across a bacterial population; we […]

Stephen Chen

Since proteins carry out the majority of work in living cells, how a cell operates is heavily determined by the relative abundances of different proteins at any given time. These relative abundances are largely determined by gene expression levels: the extent to which a gene is “activated.” Predicting gene expression levels from noncoding DNA sequence is a major unsolved problem in computational biology. Recently, machine learning (ML) has emerged as one of the most effective tools for this task. While significant work has been done with human genomes, much work […]

Matthew Liu

Understanding how and why proteins evolve is vital to grasping the fundamental biological processes governing everything from disease treatment to evolutionary biology. Classical sequence-based models of protein evolution make unrealistic assumptions ignoring behavior like coevolution of amino acids, which limits their explanatory power. Capturing such complex interactions requires a deep understanding of protein structure and how sites interact. To do this, my project introduces the first structure-based model of its kind for protein evolution, adapting models from protein design to contribute to a novel literature on deep models of protein […]

Tony Li

Wearable computers have become ubiquitous in our daily lives. Concurrently, the paradigm of edge computing has emerged as a pivotal framework, enabling computational tasks to be performed closer to the data source. Together, a burgeoning field of edge computing offloading techniques was born. My research concentrates on the algorithmic analysis aspect of computation offloading, which enables low-latency data transmission, efficient and convenient data storage, and secure and extensible data computation. Recently, multiple innovative computation offloading techniques have been developed, but the majority emphasize solely on their interested theoretical computation efficiency […]

Hong Joo Ryoo

As a SURF fellow, my research project focuses on testing the effectiveness of a proposal presented in a previous paper for quantum computations of scattering observables when three-body intermediate states are involved. The proposal offers a strategy to deal with the finite system size and periodic spatial volume limitations that current quantum computation strategies face. We aim to investigate the impact of boundary conditions on the extraction of hadronic and Compton-like scattering amplitudes and quantify the systematic uncertainty that arises. By applying the proposed improvement strategy based on the reduced […]

Raela Richie

Kīlauea Volcano has exhibited both effusive and explosive behavior over several centuries, with recent studies suggesting that a 1790AD eruption that killed hundreds of native Hawaiians was not an isolated event. Despite the likelihood of future explosive eruptions, we do not understand what changes in the volcanic plumbing system or magma chemistry cause these shifts in eruptive style. This project will use the relationship between pressure and CO2 density in pockets of CO2-rich fluid trapped within growing crystals to constrain the depths of magma storage at Kīlauea during the last […]

Berenise Rangel

Volcanic eruptions present a major hazard to society, both in terms of infrastructure destruction through lava flows, and their influence on the Earth’s atmosphere and climate. Mauna Loa, HI, has the largest volume of any volcano on Earth, and is currently in its fastest growing ‘shield phase’ (meaning numerous lava flows have erupted over the last millenia, and many more are expected).Given the rapid growth and clear hazards presented by this volcano, it is absolutely vital to understand the magmatic plumbing system supplying lava to the surface. I will determine […]

Ellie Mak

Approximately 85% of the Universe’s mass consists of an invisible non-atomic material called dark matter. It has shaped our Universe, including the formation and evolution of galaxies, and without it, humans would not exist. However, despite both its centrality in cosmology and decades of experimentation, the microscopic characteristics of dark matter particles are still unknown. This project focuses on detecting the products of possible dark matter self-annihilation in the Galaxy to reveal its origin and particle characteristics; however, the large and uncertain astrophysical backgrounds pose a challenge. GAPS is a […]