Sean Hallgren

Sean Hallgren is a Professor in Computer Science and Engineering, specializing in quantum algorithms and computational complexity. His research spans both theoretical and applied aspects of quantum computing, cryptography, and mathematical optimization.

Research Interests

Hallgren's work focuses on:

• Quantum algorithm design and complexity
• Cryptographic reductions under quantum models
• Number-theoretic problems in cryptography
• Quantum linear algebra techniques
• Computational complexity of combinatorial problems

Recent Publications

Hallgren's 15 most recent articles (5 shown) demonstrate expertise in quantum algorithm limitations, cryptographic hardness reductions, and isogeny-based cryptography. His 2023 study in Quantum analyzed the Macaulay matrix approach for solving polynomial systems using quantum linear solvers.

Grants & Projects

Current and past projects include:

• Exponential Speedups and Limitations of Quantum Computation (U.S. Navy, 2018–)
• NSF Convergence Accelerator: Scalable Quantum Artificial Intelligence for Discovery (2020–2023)
• SaTC: CORE: Small: Classical and quantum algorithms for number-theoretic cryptography (2020–2025)
• AF: Small: Quantum Algorithms and Complexity (2016–2020, PI)