• September 2024: We just posted on arXiv a new exciting work on evaluating PM2.5 forecasts from the perspective of individual decision making.

• August 2024: Our new work on reconstructing particle trajectories with Schrödinger Bridges was just posted on arXiv – check it out!

• July 2024: I am organizing a NeurIPS workshop on Bayesian Decision Making and Uncertainty – please consider submitting your research to it :)

• February 2024: I won the Outstanding Student Presentation Award at the AGU 2023 Annual Meeting

• June 2023: I have been selected as a Student Poster Award winner at the 36th New Englang Statistics Symposium.

• May 2023: I am excited to share I will be in Seattle for the summer interning at Apple, doing research in the Health AI team!

• February 2023: I won the Best Presentation Award for the talk on ‘‘Gaussian Processes at the Helm(holtz)’’ at 28th Annual LIDS Student Conference, Optimization and Algorithms Session :)

• July 2022: I have been selected as a Poster Award winner in the category BayesComp/j-ISBA at ISBA 2022.

• June 2022: I won the Microsoft Award for the best talk at BAYSM 2022!

Publications

• Berlinghieri, R.; Trippe, B. L.; Burt, D. R.; Giordano, R.; Srinivasan, K.; Özgökmen, T.; Junfei, X.; & Broderick, T. Gaussian processes at the Helm (holtz): A more fluid model for ocean currents. In International Conference on Machine Learning (ICML 2023).

• Berlinghieri, R.; Krajbich, I.; Maccheroni, F.; Marinacci, M.; Pirazzini, M. Measuring utility with diffusion models. Science Advances 9 (34), 2023.

• Jing, B.*, Corso, G.*, Berlinghieri, R., & Jaakkola, T. (2022). Subspace diffusion generative models. In European Conference on Computer Vision (ECCV 2022).

Preprints

• Berlinghieri, R.*; Burt, D. R.*, Giani, P.; Fiore, A.; Broderick, T. A Framework for Evaluating PM2.5 Forecasts from the Perspective of Individual Decision Making (2024)

• Shen, Y.*; Berlinghieri, R.*; Broderick, T. Multi-marginal Schrödinger Bridges with Iterative Reference Refinement (2024)

Talks

• Gaussian processes at the Helm(holtz):
  • AGU Annual Meeting 2023 - physics-informed machine learning oral session. San Francisco, December, 2023. [Invited Talk]
  • Approximation Methods in Bayesian Analysis workshop. CIRM Marseille, June 2023.
  • New England Statistics Symposium 2023. Boston, June 2023.
  • MIT Machine Learning Advances Symposium. Cambridge, May 2023. [Spotlight Talk]
  • 28th Annual LIDS Student Conference. Cambridge, February 2023.
  • 2022 NeurIPS Workshop on Gaussian Processes, Spatiotemporal Modeling, and Decision-making Systems. New Orleans LA, December 2022.
  • 13th International Conference on Bayesian Nonparametrics (BNP13). Puerto Varas, Chile, October 2022.
  • Bayesian Young Statisticians Meeting (BAYSM 2022). Montreal, Canada, June 2022.
  • Machine Learning for Submesoscale Characterization, Ocean Prediction, and Exploration (ML-SCOPE) meeting. Online, May 2022.

Posters

• Gaussian processes at the Helm(holtz):
  • Bayesian Nonparametrics Networking Workshop. Melbourne, December 2023.
  • EnviBayes workshop on complex environmental data. Fort Collins, September 2023.
  • 40th International Conference on Machine Learning. Honolulu, July 2023.
  • Approximation Methods in Bayesian Analysis workshop. CIRM Marseille, June 2023.
  • New England Statistics Symposium 2023. Boston, June 2023.
  • MIT Machine Learning Advances Symposium. Cambridge, May 2023.
  • World Meeting of the International Society for Bayesian Analysis (ISBA 2022). Montreal, July 2022.
  • MIT Statistics and Data Science conference (SDSCon). Cambridge, April 2022.