I’m a Member of Technical Staff at Microsoft AI. My work focuses on reinforcement learning and post-training for language models.
Previously, I was an engineering manager at Apple, working on World Knowledge Answers. I helped build and scale question answering across Siri, Spotlight, and Safari, with a focus on modeling, evaluation, and generative summarization.
Prior to Apple, I was an individual contributor at Turi (a startup formerly known as Dato and GraphLab). I helped build the NLP and recommender system toolkits for Turi Create.
During graduate school, I focused on probabilistic models for relational events, e.g., communication or interaction within a social network. I obtained a Ph.D. from the Department of Statistics at University of California, Irvine, working with Padhraic Smyth and the DataLab. I also had the opportunity to do research internships at Google Research NY (with Daryl Pregibon) and Microsoft Research (with Chris Meek).
Research
Recent
MAI-Thinking-1: Building a Hill-Climbing Machine
The Microsoft AI Team
Microsoft AI Technical Report, 2026 [paper]
Entity-Based Knowledge Conflicts in Question Answering
Shayne Longpre, Kartik Perisetla, Anthony Chen, Nikhil Ramesh, Chris DuBois, Sameer Singh
EMNLP 2021 [paper]
Active Learning Over Multiple Domains in Natural Language Tasks
Shayne Longpre, Julia Reisler, Edward Huang, Yi Lu, Andrew Frank, Nikhil Ramesh, Chris DuBois
arxiv [paper]
Combining Compressions for Multiplicative Size Scaling on Natural Language Tasks
Rajiv Movva, Jinhao Lei, Shayne Longpre, Ajay Gupta, and Chris DuBois
arxiv [paper]
An Exploration of Data Augmentation and Sampling Techniques for Domain-Agnostic Question Answering
Shayne Longpre, Yi Lu, Zhucheng Tu, Chris DuBois
2nd Workshop on Machine Reading for Question Answering (co-located with EMNLP) [paper]
Pivot Through English: Reliably Answering Multilingual Questions without Document Retrieval
Ivan Montero, Shayne Longpre, Ni Lao, Andrew J. Frank, Christopher DuBois
arXiv [paper]
How Effective is Task-Agnostic Data Augmentation for Pretrained Transformers?
Shayne Longpre, Yu Wang, Chris DuBois
Findings of EMNLP 2020 [paper]
On the Transferability of Minimal Prediction Preserving Inputs in Question Answering
Shayne Longpre, Yi Lu, Chris DuBois
NAACL 2021 [paper]
Tempura: Query Analysis with Structural Templates
Tongshuang Wu, Kanit Wonguphasawat, Donghao Ren, Kayur Patel, Chris DuBois
CHI 2020 [paper]
Collaborative denoising auto-encoders for top-n recommender systems
Yao Wu, Christopher DuBois, Alice X Zheng, Martin Ester
Proceedings of the Ninth ACM International Conference on Web Search and Data Mining [paper]
Previous
Approximate Slice Sampling for Bayesian Posterior Inference
Christopher DuBois, Anoop Korattikara, Max Welling, Padhraic Smyth
AI STATS 2014 [paper]
Waiting for a retweet: modeling waiting times in information propagation
Emma Spiro, Christopher DuBois, Carter Butts
NIPS 2012 Workshop on Social Media and Social Networks [paper]
Stochastic Collapsed Variational Bayesian Inference for Latent Dirichlet Allocation
James Foulds, Levi Boyles, Christopher DuBois, Max Welling, Padhraic Smyth
KDD 2013 [paper]
Stochastic blockmodeling of relational event dynamics
Christopher DuBois, Carter Butts, Padhraic Smyth
AI STATS 2013 [paper]
Windows into Relational Events: Data Structures for Contiguous Subsequences of Edges
Michael J. Bannister, Christopher DuBois, David Eppstein, Padhraic Smyth
SODA 2013 [paper]
Statistical Models for Exploring Individual Email Communication Behavior
Nicholas Navaroli, Christopher DuBois, Padhraic Smyth
ACML 2012 (JMLR workshop) [paper]
Hierarchical Models for Relational Event Sequences
Christopher DuBois, Carter T. Butts, Daniel McFarland, Padhraic Smyth
Journal of Mathematical Psychology [paper]
Latent Set Models for Two-Mode Network Data
Christopher DuBois, James Foulds, Padhraic Smythh
Fifth International AAAI Conference on Weblogs and Social Media (2011) [paper]
A multiple time-scale computational model of a tumor and its micro environment
Christopher DuBois, Farnham J, Aaron E, Radunskaya A.
Mathematical Biosciences and Engineering, Vol.10 [paper]