معرفی
Ravid Shwartz-Ziv is an Assistant Professor and Faculty Fellow at NYU's Center for Data Science, with a dual role as Senior Research Scientist at Wand AI. His research bridges theoretical foundations and practical applications in artificial intelligence, focusing on Large Language Models (LLMs), information theory, and neural network interpretability.
- Ph.D. in Computational Neuroscience, Hebrew University of Jerusalem (2021)
- B.Sc. in Computer Science and Computational Biology, Hebrew University of Jerusalem (2014)
His research spans:
- Developing min-p sampling for LLM text generation
- Preventing representation collapse in Transformers
- Creating contamination-free LLM benchmarks like LiveBench
- Advancing information-theoretic frameworks for neural networks
- Exploring representation learning and model adaptation
Recent publications demonstrate expertise in LLM efficiency, self-supervised learning, and multi-agent systems. Notable awards include the Google PhD Fellowship, Moore-Sloan Fellowship, and multiple best paper recognitions. He has led research initiatives at Intel and Google AI, focusing on neural network compression, XGBoost comparisons for tabular data, and innovative benchmarking frameworks.
