David Arbour

Senior Research Scientist

San Jose

I am currently a researcher at Adobe research where my work focuses on the intersection between experimentation, causal inference, and machine learning and AI with a particular focus on dependent data. Previously I was a research scientist in the Core Data Science group at Facebook. My work at Facebook focused on developing methods for adaptive experimentation, specifically Bayesian optimization and contextual bandits. Previous to that, I earned a PhD from UMass Amherst in computer science.

I am currently looking for motivated students for research internships in the Summer of 2025. Interested students should reach out to me directly.

Publications

Leveraging semantic similarity for experimentation with AI-generated treatments

Shi, Lei., Arbour, David., Addanki, Raghavendra., Sinha, Ritwik., Feller, Avi. (Dec. 3, 2025)

Neural Information Processing Systems (NeurIPS 2025)

Image Difference Captioning via Adversarial Preference Optimization

Huang, Zihan., Wu, Junda., Surana, Rohan., Yu, Tong., Arbour, David., Sinha, Ritwik., McAuley, Julian. (Nov. 4, 2025)

Conference on Empirical Methods in Natural Language Processing (EMNLP 2025)

Editing Partially Observable Networks via Graph Diffusion Models

Trivedi, Puja., Rossi, Ryan., Arbour, David., Yu, Tong., Dernoncourt, Franck., Kim, Sungchul., Lipka, Nedim., Park, Namyong., Ahmed, Nesreen., Koutra, Danai. (Jul. 27, 2024)

ICML 2024

Continuous Treatment Effects with Surrogate Outcomes

Zeng, Zhenghao., Arbour, David., Feller, Avi., Addanki, Raghavendra., Rossi, Ryan., Sinha, Ritwik., Kennedy, Edward. (Jul. 1, 2024)

International Conference on Machine Learning (ICML)

News