Chris Martens

Associate Professor
Khoury College of Computer Sciences
College of Arts, Media, and Design
Northeastern University

Ph.D. in Computer Science
Carnegie Mellon University

Email: c.martens at
Office: Meserve 138 (Boston campus)
Pronouns: they/them

Research Interests

I am interested in elegant computational abstractions that support creative practices. Since I view programming and mathematics as creative practices, this is a purposefully broad scope, but my prior work has been situated in the context of game design, interactive narrative authoring, online governance (such as privacy policy development), and programming language specification.

My goal is to enable practitioners in these domains to do two things: (1) rapid prototyping and idea generation that explores large design spaces; (2) sound informal reasoning about the computational content of designs that can be translated to formal, machine-checkable proof.

Towards these goals, I rely on and contribute to two main disciplinary foundations: Programming Languages (PL) and Generative Methods. Within PL, my work focuses on connections between logic and computer science, such as (dependently) typed functional programming, logic programming, and logical frameworks. Generative methods include practices from game development and art that involve specifying and exploring design spaces algorithmically; my work in this arena includes generative visual art, solver-aided design tools, procedural game generation (i.e. "program synthesis for games"), and computational models of narrative structure (e.g. narrative planning).

I am also increasingly interested in category-theoretic and algebraic accounts of computation (particularly for interactive programs).

At Northeastern, I am affiliated with the Programming Research Laboratory (PRL) and Games at Northeastern.

POEM Group

My research group, called POEM (Principles of Expressive Machines), includes the following students and collaborators:

  • Emma Tosch, Ph.D. (postdoc, Northeastern University)
  • Luis Garcia (Ph.D. student, Northeastern University)
  • Sasha Azad (Ph.D. student, NCSU)
  • Chinmaya Dabral (Ph.D. student, NCSU)
  • Abhijeet Krishnan (Ph.D. student, NCSU; co-advised with Arnav Jhala)



  • In Spring 2024, I am teaching a mini course on Logical Frameworks.
  • In Spring 2023, I taught Generative Game Design (GAME 4460/GSND 4660).
  • In Fall 2022, I taught Programming Languages for Virtual Worlds (CS 7480).
  • Before that, I taught classes at NCSU.

Latest Publications

If you can't find a PDF here, please feel free to email me for it! You might also try my Google Scholar profile.

Probabilistic Logic Programming Semantics For Procedural Content Generation.
Abdelrahman Madkour, Chris Martens, Steven Holtzen, Casper Harteveld and Stacy Marsella.
In Artificial Intelligence in Interactive Digital Entertainment (AIIDE '23), Salt Lake City, Utah, October 2023.

Towards Procedural Generation of Constructed Languages for Games.
Aaron Cai and Chris Martens.
In Experimental AI in Games (EXAG '23), Salt Lake City, Utah, October 2023.

Modeling Game Mechanics with Ceptre.
Chris Martens, Alexander Card, Henry Crain, and Asha Khatri.
In IEEE Transactions on Games, July 2023.

Exploring Consequences of Privacy Policies with Narrative Generation.
Chinmaya Dabral, Emma Tosch, and Chris Martens.
In Workshop on Programming Languages and the Law (ProLaLa @ POPL '23), Boston, MA, January 2023.

Older publications



Explorable Formal Models of Privacy Policies and Regulations.
Funding source: NSF CAREER Award (2019-2024)
People: Emma Tosch, Luis Garcia, Chinmaya Dabral
Aims: We are developing techniques to represent privacy policies and regulations that are both formal and explorable, permitting users and policy crafters to answer 'what if'? questions about specific scenarios in addition to providing provable guarantees. We are formalizing privacy documents and scenarios using a relational programming model known as Answer Set Programming (ASP) as a lightweight semantic modeling framework, in which we have build a narrative planner that generates partial-ordered event structures from agent intentions and capabilities. We are augmenting ASP and narrative planning with support for answering queries, generating scenarios that reveal privacy loopholes, generating counterexamples to global correctness conditions, suggesting repairs for broken policies, and enabling the exploration of hypothetical scenarios by policy developers and users.

Past projects