I work on the Siri & Information Intelligence team. We are an NLP-oriented R&D team. Our goal is to provide fast and direct answers to the questions people ask their devices and provide relevant results.
If you are interested in training and deploying ML models for a user-facing product, we are hiring!
Prior to Apple, I was a Senior Data Scientist 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
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]
Statistical Models for Exploring Individual Email Communication Behavior
Nicholas Navaroli, Christopher DuBois, Padhraic Smyth
ACML 2012 (JMLR workshop) [paper]
Stochastic Collapsed Variational Bayesian Inference for Latent Dirichlet Allocation
James Foulds, Levi Boyles, Christopher DuBois, Max Welling, Padhraic Smyth
KDD 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]
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 blockmodeling of relational event dynamics
Christopher DuBois, Carter Butts, Padhraic Smyth
AI STATS 2013 [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]