Â鶹ÊÓƵ

Senior, double major in Computer Science and Mathematics

Will begin graduate school at MIT in fall 2026.

Advisor: Rafael Frongillo (Â鶹ÊÓƵ), (MIT)

Voting theory is the study of making collective decisions given agents’ preferences. A voting rule is a map from a collection of voters' rankings over candidates to a winner. Common examples include plurality, instant runoff, and ranked pairs. There are several normative ideals that a given voting rule should satisfy, and different voting rules seek to implement different principles. In the United States, debates surrounding the merits of different voting rules have intensified in recent years. These debates have led to a flurry of both theoretical and empirical research studying the behavior of voting rules, often coming to contradictory conclusions. But to make informed policy decisions, it is important to resolve these differences and understand the resulting implications for both candidates and voters. As a result, I plan to research the structural causes of these discrepancies, and the incentives of both voters and candidates to strategically place themselves on an ideological spectrum.

Senior, double major in Computer Science and Mathematics

Will begin graduate school at UC San Diego in fall 2026

Advisor: Emily Jensen

My GRFP proposal was based on my senior thesis research, which came about through a collaboration with Prof. Cody Scarborough’s EMRG research group. Our work studies how electrical circuits can be designed to generate short, high-frequency electromagnetic pulses used in medical imaging, radar, and communications systems. One circuit design that has shown success is the nonlinear transmission line (NLTL). These circuits are inexpensive, made of widely available components, and very reliable because they have no moving parts. However, tuning the design of NLTLs to generate pulses with desired properties is not well understood due to their nonlinear dynamics. Our work uses numerical optimization together with tools from partial differential equations and lattice dynamical systems to determine what pulses can be generated by NLTLs, and how to systematically tune circuit parameters to achieve them.

1st Year Computer Science PhD Student

Advisor:Ramin Ayanzadeh
Lab: Quantum Architecture, Systems, and Applications Research Lab (QUASAR)

My research will be on the development of a compilation framework for heterogeneous quantum architectures that integrates diverse qubit technologies. Currently, there are various quantum technologies being researched to implement qubits. These range from superconducting qubits, to trapped ion, to neutral atoms and photonics. Current quantum systems are constrained by platform-specific trade-offs between factors like gate speed, coherence times, and connectivity. One promising direction in quantum computing is to design systems that combine various hardwares. However, this introduces the problem of cross-platform circuit compilation. My goal is to research current qubit technologies and develop a hardware-aware compiler for heterogeneous systems that can balance the benefits and drawbacks of each hardware during qubit routing, mapping, and circuit optimization.

Senior, Computer Science

Will begin graduate school at Carnegie Mellon University in fall 2026.

Advisor: Bradley Hayes
Lab: