Matthew A. Hammer

As of Fall 2015, I am an assistant professor in the Department of Computer Science at University of Colorado Boulder.

I am a co-director of the CU Programming Languages and Verification group (CUPLV).

Research Interests

(Also see my drafts and publications page).

Research on programming languages provides invaluable lenses that connect human understanding with computational phenomena.

In particular, I'm interested in designing PL-based abstractions for settings in which humans and computers cooperate to create and process information.

Interactive computations
reside in an open world, where future states are explored collaboratively with an external user. Common examples include spreadsheets, development environments, video games and media processing (graphics and sound).

See also: The Hazelgrove project: Foundational semantics for interactive programming.
Our Hazel paper, Toward Semantic Foundations of Program Editors (SNAPL 2017)
Our Hazelnut paper (POPL 2017)
Our HZ prototype and live demo (POPL 2017 Artifact)

Our Languages of Play paper (in submission)

Incremental computations
consume and produce information whose content or structure changes slowly over time by small changes. In these settings, programs exploit cached work from the past to respond more efficiently than naive re-computation that is oblivious to past work.

Many prior programming-language-based approaches to incremental computation, including self-adjusting computation, assume a non-interactive model. As it turns out, efficient interactive computation often requires a demand-driven approach to caching past computation.

See also: The Adapton project: Foundational semantics for incremental computations.
Our Typed Adapton paper (in submission)
Our Incremental Computation with Names paper (OOPSLA 2015)
Our Adapton paper (PLDI 2014)
Incremental computation (wikipedia)
Interactive computation (wikipedia)

Secure multi-party computation
consists of computation performed by mutually-distrusting agents; together, they cooperatively compute functions over their private data, while only ever learning certain prearranged results and while remaining otherwise oblivious to the computational steps necessary to produce them.

See also: Our Wysteria paper (OAKLAND 2014)
Our Knowledge Inference paper (PLAS 2013)
Secure multi-party computation (wikipedia)

Publications List


Kyle Headley (PhD student, since Fall 2015)
Monal Narasimhamurthy(PhD student, since Fall 2016)
Jared Wright (PhD student, since Fall 2016)


Semester Number Title
2017 Spring CSCI 7000 Advanced programming language techniques for incremental computation
2016 Fall CSCI 5535 / ECEN 5533 Fundamentals of Programming Languages
2016 Spring CSCI 7000 Programming Language Design for Interaction
2015 Fall CSCI 5535 / ECEN 5533 Fundamentals of Programming Languages

Funded Projects

Online Verification-Validation (PI)

Short biography

Before joining CU, I was a postdoc researcher working with Michael Hicks, Jeff Foster, David Van Horn and the PLUM group at the University of Maryland. As a PhD student, I was advised by Umut Acar at the University of Chicago as well as a visiting student at the Max Planck Institute for Software Systems in Kaiserslautern, Germany.

As a student intern, I spent summers at IBM Research in Almaden and Intel Research in Santa Clara. I received my B.S. in 2005 from the University of Wisconsin with a major and honors in computer science.