Research

You can also find my articles on my google scholar profile.

Published or Forthcoming Journal Articles

• Contextual Inverse Optimization: Offline and Online Learning. O. Besbes, Y. Fonseca, and I. Lobel. Operations Research (2025).
  • An earlier version that includes some of these results appeared at the Conference on Learning Theory (COLT), 2021, with the title “Online Learning from Optimal Actions.”
• ArCo: An R package to Estimate Artificial Counterfactuals. Y. Fonseca, R. Masini, M. Medeiros, and G. Vasconcelos.R. Journal (2018)
  • Package available in R: link

Working Papers

• Procurement Design with Network Effects: A Case Study in Infrastructure. Y. Fonseca, V. Manshadi, and D. Saban. (submitted).
  • An earlier version that includes some of these results appeared at EC’26, Proceedings of the 2026 ACM Conference on Economics and Computation.
• When One Shines, All Glow: The Influence of Platform Badges. O. Besbes, Y. Fonseca, Z. Lai, R. Mastronmonaco, and F. Zheng. (major revision Management Science)
  • Selected for presentation at 2026 MSOM Service Management SIG.

• Constrained Learning for Causal Inference. T. Cai, Y. Fonseca, K. Hou, and H. Namkoong. (submitted).

• Signaling Competition in Two-Sided Markets. O. Besbes, Y. Fonseca, I. Lobel, and F. Zheng. (major revision Management Science)
  • An earlier version that includes some of these results appeared at EC’23, Proceedings of the 2023 ACM Conference on Economics and Computation.
  • Second Place, MSOM Student Paper Competition, 2024
  • Second Place, RMP Jeff McGill Student Paper Award, 2023
• BooST: Boosting Smooth Trees for Partial Effect Estimation in Nonlinear Regressions. Y. Fonseca, M. Medeiros, G. Vasconcelos, and A. Veiga.

Refereed Conferences

• Procurement Design with Network Effects: A Case Study in Infrastructure. Y. Fonseca, V. Manshadi, and D. Saban. EC’26, Proceedings of the 2026 ACM Conference on Economics and Computation.

• Nonparametric Instrumental Variable Regression Through Stochastic Approximate Gradients. Y. Fonseca, C. Peixoto, and Y. Saporito. Proceedings of the 38th Conference on Neural Information Processing Systems (NeurIPS 2024)

• Signaling Competition in Two-Sided Markets. O. Besbes, Y. Fonseca, I. Lobel, and F. Zheng. EC’23, Proceedings of the 2023 ACM Conference on Economics and Computation.

• Statistical Learning and Inverse Problems: A Functional Gradient Descent Approach. Y. Fonseca and Y. Saporito. Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS 2022)

• Online Learning from Optimal Actions. O. Besbes, Y. Fonseca, and I. Lobel. COLT’ 21, 34th Annual Conference on Learning Theory.

Work in Progress

• Recovering Tacit Knowledge from Unstructured Expert Logs: A Contextual Inverse Optimization Framework. M. Bickel, Y. Fonseca, and T. Netland.

• Nonlinear Contextual Inverse Optimization. Y. Fonseca, L. F. Marques, C. Peixoto, and Y. Saporito.

Prior Life

• Relação entre os parâmetros de rugosidade 3D e a molhabilidade do titânio com grãos micrométricos e sub-micrométricos G. Leite, Y. Fonseca, A. Gomes, and C. Elias. Matéria (Rio de Janeiro), 25, 2020.

• Modeling of the influence of chemical composition, sintering temperature, density, and thickness in the light transmittance of four zirconia dental prostheses Y. Fonseca, C. Elias, S. Monteiro, H. Dos Santos, and C. Dos Santos. Materials, 12(16), 2529, 2019.

• Extensiometric analysis of strain in craniofacial bones during implant-supported palatal expansion Elias, Carlos Nelson; Jogaib, Daniel; Zanivan, Daniel; Fonseca, Yuri. Journal of the Mechanical Behavior of Biomedical Materials, 2017.