Christopher Curtis

PhD Researcher, Khoury College of Computer Sciences, Northeastern University.

I’m a computer science PhD researcher at Northeastern University and a member of the Civic AI Lab, advised by Saiph Savage. My work spans model evaluation, Transformer architectures, and human–computer interaction.

My research connects technical questions about AI capabilities with practical questions about system design. Published and publicly released work includes CIPHERGRID, a benchmark testing whether models can infer an unfamiliar symbolic world from examples and act on its rules; a NeurIPS tutorial on positional encoding in Transformers; and studies of AI tools that support crowdworkers and gig workers.

I am an NSF NRT PEAR Fellow. My background also includes software engineering at Hewlett Packard Enterprise, independent development of simulation and AI tools, and service in the New York Army National Guard.

Khoury College of Computer Sciences

Northeastern University

Boston, MA

news

2026	Our paper CIPHERGRID was accepted to the NeurIPS 2026 Evaluations & Datasets Track.
2026	Nominated for the Outstanding PhD Award.
2025	Co-presented the official NeurIPS tutorial Positional Encoding: Past, Present, and Future with Saiph Savage in Mexico City, with teaching code and slides released publicly.
2024	Selected as an NSF NRT PEAR Fellow at Northeastern (2024–25).
2024	Selected for the NSF IRES Germany program, building full-stack platforms for explainable-AI (XAI) research.
2024	Co-authored research appearing in ACM PACMHCI / CSCW and the ACM Collective Intelligence Conference.

selected publications

NeurIPS

CIPHERGRID Benchmark: From Multimodal Rule Inference to Sequential Action

Christopher Curtis, Victor Fragoso, and Saiph Savage

Advances in Neural Information Processing Systems (NeurIPS), Evaluations & Datasets Track, 2026 · Accepted, forthcoming

Dataset Code

@inproceedings{curtis2026ciphergrid,
  title     = {{CIPHERGRID} Benchmark: From Multimodal Rule Inference to Sequential Action},
  author    = {Curtis, Christopher and Fragoso, Victor and Savage, Saiph},
  booktitle = {Advances in Neural Information Processing Systems},
  year      = {2026},
  note      = {Accepted, Evaluations and Datasets Track}
}

CSCW

A Culturally-Aware AI Tool for Crowdworkers: Leveraging Chronemics to Support Diverse Work Styles

Carlos Toxtli, Christopher Curtis, and Saiph Savage

Proceedings of the ACM on Human-Computer Interaction (CSCW), 2024

DOI

@article{toxtli2024culturally,
  title   = {A Culturally-Aware AI Tool for Crowdworkers: Leveraging Chronemics to Support Diverse Work Styles},
  author  = {Toxtli, Carlos and Curtis, Christopher and Savage, Saiph},
  journal = {Proceedings of the ACM on Human-Computer Interaction},
  year    = {2024},
  doi     = {10.1145/3686899}
}

ACM CI

Office-Mind AI: A Generative AI Tool for Gig Workers

Christopher Curtis, Seth Cooper, and Saiph Savage

ACM Collective Intelligence Conference, Extended abstract, 2024

PDF Program

@inproceedings{curtis2024officemind,
  title     = {Office-Mind AI: A Generative AI Tool for Gig Workers},
  author    = {Curtis, Christopher and Cooper, Seth and Savage, Saiph},
  booktitle = {Book of Extended Abstracts of the ACM Collective Intelligence Conference},
  year      = {2024}
}