Andrew K. Hirsch

Andrew K. Hirsch is an Assistant Professor in the Department of Computer Science and Engineering at the University at Buffalo, SUNY, where he is a core member of the Databases and Programming Languages research group. His work bridges programming language theory and practical system design, focusing on choreographic programming and information-flow security.

Research Interests: His research centers on programming languages for decentralized and concurrent systems, particularly choreographic programming—a paradigm where a global program is compiled into distributed components. He investigates type systems, process polymorphism, and secure communication protocols. Additionally, he works on information-flow security, formalizing declassification policies, and using interaction trees for mechanized security proofs.

Publication Trends: His recent publications (2023–2025) reflect a strong focus on expressive choreographic languages with features like first-class locations, process polymorphism, and macro-based DSLs. Earlier works explore computational effects, authorization logic, and secure semantics—showing a consistent trajectory in language-based security and concurrency.

• Scientific Awards: No specific awards are mentioned in the provided text.

Advising and Grants: He advises multiple doctoral and master’s students, including Michael Piskozub, Alexander Bohosian, and Keith Allen Mason Lary. His research is supported by an NSF grant titled "SHF: SMALL: Open Choreographies via Session Types," which funds his work on extending choreographic programming to interact with external systems. He integrates student learning through the UB CSE Experiential Learning and Research (EL/R) program.

Labs and Teams: He helps lead the Databases and Programming Languages group at the University at Buffalo. He has developed tools like Choret (a Racket-based choreographic DSL) and the Pirouette compiler. His projects, including Open Choreographies and the Pirouette Language Compiler, are publicly available on GitHub, indicating active collaboration and open research practices.