Seth Cooper
(he/him)
Associate Professor
Research interests
- Scientific discovery games
- Serious games
- Crowdsourcing games
- Citizen science
- Novel interfaces for problem-solving
- Automated tools for assisting game design and development
- Computational structural biochemistry
Education
- PhD in Computer Science and Engineering, University of Washington
- MS in Computer Science and Engineering, University of Washington
- BS in Electrical Engineering and Computer Science, University of California, Berkeley
Biography
Seth Cooper is an associate professor in the Khoury College of Computer Sciences at Northeastern University, based in Boston.
Cooper's pioneering work combines scientific discovery games (particularly in computational structural biochemistry), serious games, and crowdsourcing games. He has shown that video game players can outperform purely computational methods for certain types of structural biochemistry problems, effectively codify their strategies, and integrate with labs to help design real synthetic molecules. He has also developed techniques to adapt the difficulty of tasks to individual game players and to generate game levels.
Before joining Northeastern, Cooper was creative director of the Center for Game Science at the University of Washington. Cooper's industry journey comprises roles at Square Enix, Electronic Arts, and Pixar Animation Studios.
Recent publications
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Toward Space-Time WaveFunctionCollapse for Level and Solution Generation
Citation: Kaylah Facey, Seth Cooper. (2024). Toward Space-Time WaveFunctionCollapse for Level and Solution Generation AIIDE, 25-34. https://doi.org/10.1609/aiide.v20i1.31863 -
Procedurally Puzzling: On Algorithmic Difficulty and Player Experience in QD-Generated Logic Grid Puzzles
Citation: Fiona Shyne, Kaylah Facey, Seth Cooper. (2024). Procedurally Puzzling: On Algorithmic Difficulty and Player Experience in QD-Generated Logic Grid Puzzles AIIDE, 127-137. https://doi.org/10.1609/aiide.v20i1.31873 -
Sturgeon-MKIV: Constraint-Based Level and Playthrough Generation with Graph Label Rewrite Rules
Citation: Seth Cooper, Mahsa Bazzaz. (2024). Sturgeon-MKIV: Constraint-Based Level and Playthrough Generation with Graph Label Rewrite Rules AIIDE, 13-24. https://doi.org/10.1609/aiide.v20i1.31862 -
Asynchronous Collaboration with Quality-Diversity Search in Human Computation Games
Citation: Nicholas Osborn, Seth Cooper. (2024). Asynchronous Collaboration with Quality-Diversity Search in Human Computation Games FDG, 45. https://doi.org/10.1145/3649921.3656977 -
Authoring Games with Tile Rewrite Rule Behavior Trees
Citation: Jiayi Zhou, Chris Martens , Seth Cooper. (2024). Authoring Games with Tile Rewrite Rule Behavior Trees FDG, 47. https://doi.org/10.1145/3649921.3656979 -
A Design Framework for Reflective Play
Citation: Josh Aaron Miller, Kutub Gandhi, Matthew Alexander Whitby, Mehmet Kosa, Seth Cooper, Elisa D. Mekler, Ioanna Iacovides. (2024). A Design Framework for Reflective Play CHI, 519:1-519:21. https://doi.org/10.1145/3613904.3642455 -
Latent Combinational Game Design
Citation: Anurag Sarkar, Seth Cooper. (2024). Latent Combinational Game Design IEEE Trans. Games, 16, 659-669. https://doi.org/10.1109/TG.2023.3346331 -
Segment-wise Level Generation using Iterative Constrained Extension
Citation: Hao Mao, Seth Cooper. (2023). Segment-wise Level Generation using Iterative Constrained Extension CoG, 1-7. https://doi.org/10.1109/CoG57401.2023.10333222 -
Active Learning for Classifying 2D Grid-Based Level Completability
Citation: Mahsa Bazzaz, Seth Cooper. (2023). Active Learning for Classifying 2D Grid-Based Level Completability CoG, 1-4. https://doi.org/10.1109/CoG57401.2023.10333212 -
Game Level Blending using a Learned Level Representation
Citation: Venkata Sai Revanth Atmakuri, Seth Cooper, Matthew Guzdial. (2023). Game Level Blending using a Learned Level Representation CoG, 1-8. https://doi.org/10.1109/CoG57401.2023.10333227 -
path2level: Constraint-Based Level Generation from Paths
Citation: Seth Cooper, Matthew Guzdial. (2023). path2level: Constraint-Based Level Generation from Paths CoG, 1-4. https://doi.org/10.1109/CoG57401.2023.10333205 -
Mechanic Maker 2.0: Reinforcement Learning for Evaluating Generated Rules
Citation: Johor Jara Gonzalez, Seth Cooper, Matthew Guzdial. (2023). Mechanic Maker 2.0: Reinforcement Learning for Evaluating Generated Rules AIIDE, 266-275. https://doi.org/10.1609/aiide.v19i1.27522 -
Re-trainable Procedural Level Generation via Machine Learning (RT-PLGML) as Game Mechanic
Citation: Seth Cooper, Emily Halina, Jichen Zhu, Matthew Guzdial. (2023). Re-trainable Procedural Level Generation via Machine Learning (RT-PLGML) as Game Mechanic FDG, 69:1-69:3. https://doi.org/10.1145/3582437.3587210 -
Wrapped in Story: The Affordances of Narrative for Citizen Science Games
Citation: Josh Aaron Miller, Katherine Buse, Ranjodh Singh Dhaliwal, Justin B. Siegel, Seth Cooper, Colin Milburn. (2023). Wrapped in Story: The Affordances of Narrative for Citizen Science Games FDG, 33:1-33:11. https://doi.org/10.1145/3582437.3582443 -
Sturgeon-MKIII: Simultaneous Level and Example Playthrough Generation via Constraint Satisfaction with Tile Rewrite Rules
Citation: Seth Cooper. (2023). Sturgeon-MKIII: Simultaneous Level and Example Playthrough Generation via Constraint Satisfaction with Tile Rewrite Rules FDG, 64:1-64:9. https://doi.org/10.1145/3582437.3587205 -
Sturgeon-GRAPH: Constrained Graph Generation from Examples
Citation: Seth Cooper. (2023). Sturgeon-GRAPH: Constrained Graph Generation from Examples FDG, 23:1-23:9. https://doi.org/10.1145/3582437.3582465 -
On Variety, Complexity, and Engagement in Crowdsourced Disaster Response Tasks
Citation: Sofia Eleni Spatharioti and Seth Cooper. On Variety, Complexity, and Engagement in Crowdsourced Disaster Response Tasks. Proceedings of the 14th International Conference on Information Systems for Crisis Response and Management (2017).
Related news
Current PhD students
Previous PhD students
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Britton Horn
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Josh Aaron Miller
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Anurag Sarkar
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Sofia Eleni Spatharioti