Khoury faculty members Daniel Wichs, right, and Jonathan Ullman, second from right, look at a computer screen that four other researchers are viewing.

Algorithms and Theory at Khoury College of Computer Sciences

Advancing knowledge about the foundations of computing

The Algorithms and Theory research area at Khoury College focuses on fundamental questions in computer science, developing knowledge that supports progress in any specialty: for instance, determining what it means for something to be computable, what kind of computations can be made, investigating whether in principle sets of procedures — algorithms — can be created for a type of problem, and analyzing those algorithms’ characteristics.

In this way, algorithms and theory research supports computer science across a range of other areas such as fueling cryptography, AI, and data science, areas where practitioners building tools need to know that the foundational theory their work depends on is sound, what the limits are, and what’s feasible.

Meet our faculty

Pushing the boundaries of what’s possible

Insights from Khoury College algorithms and theory research have an impact on many aspects of computing. In particular, theory research has helped discover how cryptography can help keep information you look up from a resource private, with the potential that someday you could use a search engine but it wouldn’t see what you’re doing — a potential revolution in privacy.

Study of algorithms can help ground core work in software development. By looking at the general and abstract characteristics of a computational problem, you can assess its complexity and what the limits may be to creating algorithms to tackle it. In this way, Khoury College is helping build the foundation for better approaches to building programs and tools, pushing the boundaries of what is feasible technically through better understanding of theoretical limits.

Sample research areas

  • Approximation algorithms
  • Computational complexity
  • Cryptography
  • Distributed computing
  • Cybersecurity and privacy
  • Learning theory
  • Network algorithms

Khoury researchers: At the forefront

Jonathan Ullman discusses his goals of designing effective data systems that don’t compromise individuals’ privacy.
Daniel Wichs’ research is a novel approach to authenticating data in the cloud with digital signatures while ensuring it’s secure.

Highlights and accomplishments

Faculty awards and achievements

Best paper

  • 2025 STOC: Soheil Behnezhad
  • 2024 SODA: Soheil Behnezhad
  • 2023 STOC: Daniel Wichs, Wei-Kai Lin, Ethan Mook
  • 2008 CCC: Emanuele Viola

Best student paper

  • 2023 ITCS: Lunjia Hu
  • 2022 ALT: Lunjia Hu

Career award

  • 2018 Sloan Fellow: Daniel Wichs

Projects

How can we trust data driven systems in high-stakes applications? Khoury faculty are addressing this challenge by developing the theoretical and conceptual foundations of trust in AI, machine learning, and data science. This work addresses problems like privacy of the data that drives these systems, reliably quantifying their uncertainty and making sound decisions from their outputs, and hardening these systems to be robust even to malicious attackers.

Can we privately search the internet without revealing our query to the search engine? Khoury faculty are working on novel methods to encrypt data while enabling third parties to perform private computations over it. These technologies have the potential to allow for innovative applications from secure internet search to secure data analytics, vastly increasing our privacy on the internet.

Can we understand the limits of efficient computation? This question is one of the grand challenges in computer science and mathematics, which profoundly shapes the computer systems we use daily. Computer systems must navigate around computationally intractable problems, while modern cryptography depends on problems that we believe are computationally hard. Khoury faculty approach this challenge by forging new connections between computational problems and establishing unconditional impossibility results within restricted yet far-reaching models.

Related labs and groups

Faculty members

  • Wolfgang Gatterbauer

    Associate Professor

    Wolfgang Gatterbauer is an associate professor at Khoury College. He works on the theory of scalable data management, with the goal of expanding data management systems and enabling them to support novel functionalities.

    Read bio

  • Zhengzhong Jin

    Assistant Professor

    Zhengzhong Jin is an assistant professor at Khoury College. He is interested in cryptography, teaching courses on the subject, and researching a proof system to delegate heavy computation to an untrusted server while ensuring the computation is correct.

    Read bio

  • Huy Lê Nguyen

    Associate Professor

    Huy Lê Nguyen is an associate professor at Khoury College. He researches the design and analysis of algorithms, with an emphasis on algorithmic techniques for machine learning and massive data sets.

    Read bio

  • Hongyang Zhang

    Assistant Professor

    Hongyang Zhang is an assistant professor at Khoury College. He researches at the nexus of machine learning, algorithms, and statistics, and has helped to develop techniques for neural networks, data augmentation, and transfer learning.

    Read bio