I'm a fourth-year undergraduate student at the Jerome Fisher M&T Program at the University of Pennsylvania, specializing in AI safety and transparency research. My work focuses on evaluating and understanding large language models, particularly in the areas of:

• Model evaluations and benchmarking
• Steering model behaviors
• AI transparency and interpretability

• Co-authored the most comprehensive empirical meta-analysis of AI safety benchmarks to date
• Work presented at the UK AI Safety Institute
• Research cited by OpenAI's Superalignment Fast Grants page
• Techniques incorporated into major open-source projects (llama.cpp, vLLM)

• Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress? (NeurIPS 2024 D&B)
• Representation Engineering: A Top-Down Approach to AI Transparency (200+ citations)
• Localizing Lying in Llama (NeurIPS 2023 SoLaR Workshop)

• High-Efficiency Scattering Probe Design for S-Polarized Near-Field Microscopy (Applied Physics Express, 2021)
• Validity of Machine Learning in the Quantitative Analysis of Complex Scanning Near-Field Optical Microscopy Signals Using Simulated Data (Physical Review Applied, 2021)

• 🌐 Personal Website
• 📧 Email
• 📚 Google Scholar
• 🎓 Semantic Scholar
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I'm an experimentalist at heart with a quick, iterative, and empirically-driven approach. I like to focus on new potential research areas, rather than research that fits cleanly into pre-existing research areas.