Lucas Rosenblatt
PhD Candidate, Center for Responsible AI @NYU.
I am a second year PhD candidate at NYU where I am advised by Julia Stoyanovich and work closely with Christoper Musco and Bill Howe (of UW). I am affiliated with the NYU Center for Responsible AI. I am grateful to be supported by a NSF Graduate Research Fellowship.
Broadly, my work aims to answer open questions on data privacy, algorithmic fairness and AI safety, with an eye towards improving society and doing social good.
I was formerly a member of the Microsoft AI rotational program, working out of the New England Research and Development lab (and remotely during COVID!). In 2019 I graduated from Brown University, where I wrote a thesis about AI and self-data collection.
I happen to own a school bus that I’ve spent a lot of time converting into a mobile home and finding a permanent home for it in rural Vermont. If you like, I’ll give you some great reasons to buy a bus, and arguably some better reasons not to. I also make movies and write as much as I can.
news
| Jul 7, 2023 | Very happy to say that paper Epistemic Parity: Reproducibility as an Evaluation Metric for Differential Privacy was accepted into the Proceedings of VLDB 2023! This was a huge team effort, so a big thanks to everyone on the paper for over a year of hard work : ) |
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| Apr 13, 2023 | I gave a talk at the excellent UCLA Synthetic Data Workshop. Thank you so much Guang Cheng for the invite and for organizing! Slides to be posted soon. |
| Mar 29, 2023 | Very excited to have been awarded a 2023 NSF Graduate Research Fellowship! |
| Mar 7, 2023 | Our paper The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice was accepted into the Proceedings of FAccT 2023! |
| Feb 16, 2023 | Our preprint The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice is available on arXiv. Please take a look, we believe there are exciting implications for the algorithmic fairness community. |
| Nov 19, 2022 | Our paper Counterfactual Fairness Is Basically Demographic Parity was accepted at AAAI 2023! |
| Oct 8, 2022 | Our paper Critical Perspectives: A Benchmark Revealing Pitfalls in PerspectiveAPI was accepted at NLP for Positive Impact 2022, part of EMNLP 2022. |
| Jun 13, 2022 | Our paper Spending Privacy Budget Wisely and Fairly was accepted at Theory and Practice of Differential Privacy 2022, part of ICML 2022. |
| Sep 25, 2021 | I began my PhD at NYU!  |
| Sep 1, 2021 | Our paper PerfGuard: deploying ML-for-systems without performance regressions, almost! was published in PVLDB 2021. |