Luca Zhou
About Me
I am a first-year PhD student in Computer Science at GLADIA, Sapienza University of Rome. Previously, I was a visiting graduate student researcher at UC San Diego.
My research focuses on Foundation model post-training, model merging, LLM evaluation, and agentic AI systems. I aim at building methods and tools that make large models more adaptable, composable, and usable.
Outside the lab, I stay active through sports 🥊🤸♂️ and explore my creativity through photography 📷 and music 🎹🎸. I’m always happy to collaborate, exchange ideas, or just have a chat. Feel free to reach out!
Research Interests
- Model Merging
- Post-training Adaptation
- LLM Evaluation
- Agentic AI
Publications
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Breaking the Monolith Workshop @ICIAP 2025
Selected Projects
News
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[04-2026] 🎉 CaTS-Bench, our benchmark for time series captioning and reasoning, has been accepted to ACL 2026 Findings!
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[01-2026] 📜 Wondering what determines model mergeability? Check out our newest preprint “Demystifying Mergeability: Interpretable Properties to Predict Model Merging Success”!
- [09-2025] 🎉 Excited to share that our paper “On Task Vectors and Gradients” will be presented at UniReps @NeurIPS 2025 in San Diego!
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[07-2025] 🎉 I’ve graduated with an MSc Degree from Sapienza University of Rome with honors! Check out my thesis here.
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[07-2025] 🎉 Our paper “ATM: Improving Model Merging by Alternating Tuning and Merging” has been accepted for presentation at the Breaking the Monolith: 1st ICIAP Workshop on Advances in Modular Deep Learning!
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[06-2025] 🚀 I’ve started a research internship at Panasonic North America on LLM code generation, collaborating with Stanford University and ItalAI.
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[03-2025] 🚀 I’m visiting UC San Diego as a visiting student researcher, working on a Multimodal Benchmark on Time Series Captioning & Reasoning alongside Rose STL Lab.