Dr. Awni Hannun
Staff Machine Learning Researcher
Staff Machine Learning Researcher at Apple Machine Learning Research and creator of Apple MLX, an open-source array framework designed specifically for Apple Silicon. Former researcher at Baidu AI Research who co-authored Deep Speech and pioneered CTC sequence modeling.
Areas of focus
Professional niches
Proof of Work
Deep Speech: Scaling up End-to-End Speech Recognition
First author of the landmark Baidu Deep Speech paper, proving that replacing complex phonetic acoustic pipelines with a single recurrent neural network trained end-to-end with CTC achieves state-of-the-art accuracy in noisy real-world speech.
End-to-end recurrent models without attention mechanisms struggle to maintain alignment over multi-minute audio streams.
Context: Bidirectional RNNs, CTC loss, custom GPU parallel prefix beam search decoders.
View missionMLX: An Efficient Machine Learning Framework for Apple Silicon
Conceived, engineered, and open-sourced MLX, a NumPy-like array framework with composable function transformations (grad, vmap) that exploits Apple Silicon's unified memory architecture for zero-copy CPU/GPU execution.
Exclusively optimized for Apple Silicon hardware; non-macOS platforms are not natively accelerated.
Context: Apple Silicon Metal, unified memory up to 192GB, C++ core with Python bindings.
View mission