Lucas Rosenblatt
PhD Candidate, Center for Responsible AI @NYU.
I am a third year PhD candidate at NYU where I am advised by Julia Stoyanovich and work closely with Christoper Musco. At NYU, I am affiliated with the NYU Center for Responsible AI. I also work closely with Bill Howe (of UW) and with the Volitional AI Lab (also at UW). 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, climate, AI with social impact, all with an eye towards 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
Mar 30, 2024 | Our paper Laboratory-Scale AI: Open-Weight Models are Competitive Even in Low-Resource Settings was accepted to FAccT 2024. This work was led by the indomitable Robert Wolfe; much credit to him, and happy to have been part of the team! |
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Feb 5, 2024 | Excited to be organizing the Spring iteration of NYC Privacy Day, to be held at NYU on April 19th, 2024. Privacy Day is a seasonal event that unites privacy folks from NYC institutions; hosting rotates between Columbia, NYU, Google and Cornell Tech. RSVP through the website if you can make it! |
Dec 11, 2023 | Two papers forthcoming at AAAI 2024: |
Dec 4, 2023 | I gave an invited talk at the first Columbia NYC Privacy Day. Thanks Rachel Cummings for inviting me (and for organizing)! |
Nov 6, 2023 | I gave a short talk at the NYU-Kaist Inclusive AI workshop. |
Oct 27, 2023 | Our paper Top-down Green-ups: Satellite Sensing and Deep Models to Predict Buffelgrass Phenology was accepted to the Tackling Climate Change with Machine Learning @ NeurIPS 2023 Workshop! Very fun collaboration with Bin Han and Bill Howe from the University of Washington, and Theresa Crimmins and Erin Posthumus from the USA-NPN. |
Sep 1, 2023 | Our paper Epistemic Parity: Reproducibility as an Evaluation Metric for Differential Privacy received the Best Experiment, Analysis, & Benchmark Paper (Runner-up) award at VLDB 2023! |
Jul 7, 2023 | Very happy to say that our 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 : ) |
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! |