Grace Ciambrone

I’m an AI & Data Science Researcher with experience building and validating NLP-focused models and research outputs. I work comfortably from data preparation through modeling, visualization, and writing—always aiming to turn results into publishable, real-world value.

At Università della Svizzera italiana (USI), Lugano, I served as a Technical lead on a taxonomy project for autonomous vehicles, collaborating with a PhD researcher under advisor Paulo Tonella. Using AWS and Git, I supported an academic workflow with the goal of publishing an academic manuscript in 2026.

Earlier, as an Undergraduate AI & Data Science Researcher at the Human Language Technologies Laboratory, I translated needs of U.S. policy experts into data science objectives and communicated progress through weekly presentations. I also created a corpus of phishing emails, performed analysis, built NLP models, and visualized outcomes, then wrote, published, and presented a technical manuscript at a global ACM conference.

I’m strongly motivated by research rigor and applied impact, supported by competitive funding and recognition, including a NASA Space Grant, NSF REU Grant, and NSF Seed Grant. I bring practical tooling across Python, TensorFlow, PyTorch, and scikit-learn, plus confidence with ambiguity, feedback, and initiative—so I can contribute quickly while continuing to learn.