I explore problems of interest using a mix of both theoretical and practical tools. Among many technical interests, I enjoy computational geometry and topology, robotics, high performance scientific computing, machine learning theory, and algorithm design for parallel and distributed systems.
This is joint work with Brandon Howard (who is first author), Aspen Tapley, John Dorgan, and Scott Calabrese Barton. Helped develop the foundational probabilistic modeling and asymptotic analysis applied to polymer functionalization.
Successfully defended my dissertation, titled Morphing Graphs on the Sphere, with my committee being comprised of Jeff Erickson (advisor), Timothy Chan, Sariel Har-Peled, and Therese Biedl.
Working on scalable networking algorithms and systems software for Google Cloud.
Invited by Yanwen Luo to speak about morphing graphs on the sphere at the Geometry/Topology seminar at Oklahoma State University!
Spoke in Kanazawa, Japan, at the 41st International Symposium on Computational Geometry (SoCG 2025)! Joint work with my advisor, Jeff Erickson.
Working towards the first polynomial-time algorithm that computes a continuous crossing-free transformation (a morph) between two isomorphic planar embeddings on the sphere. Initial work tackles triangulations, with upcoming work generalizing to arbitrary planar graphs.
This is joint work with Brandon Howard (who is first author), Aspen Tapley, John Dorgan, and Scott Calabrese Barton.
My contributions support the probabilistic modeling of polymer functionalization and the asymptotic analysis used to obtain a simpler analytical model.
Note: The authorship of the linked paper is listed in decreasing order of contribution. This differs from TCS publications, where names are listed in alphabetical order.
Formulated an efficient, fast algorithm for computing cyclic edit distance between strings by reducing the problem to planar maximum flow.
Researched adaptive spacetime meshing algorithms for solving systems of hyperbolic partial differential equations (PDEs) using discontinuous Galerkin finite element methods with Bob Haber and advisor Jeff Erickson.
Working on the Unified Traffic Engineering (UTE) team to further scale Google's global B4 network.
Worked on the Unified Traffic Engineering (UTE) team to make Google’s global B4 software-defined WAN network significantly more robust against single arc and Shared Risk Link Group (SRLG) failures.
Engineered an internal distributed supervised machine learning service based on TensorFlow enabling non-engineers to train, evaluate, and deploy models purely through SQL queries.
Worked with a Secret Clearance in the GNC department developing missile guidance policies, target state estimators, and distributed high-performance software tools.
Worked on drone guidance algorithms and pose estimation using classical (pre-deep learning) computer vision techniques.
Advanced algorithms course for upper-level undergraduate and graduate students. Topics include advanced dynamic programming, graph algorithms, randomized algorithms, approximation algorithms, linear programming, and computational complexity.
Core foundational course covering formal models of computation (finite automata, context-free grammars, Turing machines, undecidability, NP-Hardness) and rigorous algorithm design (divide and conquer, dynamic programming, graph algorithms).
Core foundational course covering proofs, logic, combinatorics, introductory graph theory, and introductory algorithms.
Course for aerospace engineering students to learn numerical methods; includes topics such as numerically solving ordinary and partial differential equations, multi-dimensional root finding, basics of numerical optimization, and applying these skills to aerospace-relevant problems.
Doctoral research focused on graph algorithms and computational geometry & topology. I also developed a strong interest in randomized algorithms.
Researched adaptive spacetime meshing algorithms for solving systems of hyperbolic partial differential equations (PDEs) using discontinuous Galerkin finite element methods.
Focused on robotics (with an emphasis in computer vision and control systems), aerodynamics, and computational mechanics.