Loren Lugosch
Machine Learning Researcher at Apple
United States
Summary
🤩
Rockstar🎓
Top SchoolLoren Lugosch is a Machine Learning Researcher with 11 years of experience bridging academic rigor and production ML, currently working at Apple after a PhD in Electrical Engineering at McGill/Mila. His background spans research roles and internships across industry leaders (including Facebook AI Research, Nuance, and Fluent.ai) where he focused on speech and audio technologies. Loren has practical impact on open-source speech tooling—contributing knowledge-distillation techniques to the widely used SpeechBrain toolkit to improve ASR performance. He combines deep learning research with hands-on engineering for experiment setup, loss design, and model compression, and his training in computer engineering with a linguistics minor informs a pragmatic, language-aware approach to speech models.
11 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Electrical Engineering, Doctor of Philosophy (Ph.D.) Electrical Engineering at McGill University / Mila Quebec AI InstituteMaster of Engineering (M.Eng.) Electrical Engineering, Master of Engineering (M.Eng.) Electrical Engineering at McGill University
French, Chinese, German, English
Github Skills (8)
pytorch10
distill10
speech-recognition10
deep-learning10
dis10
asr10
audio-processing9
language-model8
Programming languages (4)
Github contributions (5)
speechbrain/speechbrain
Sep 2020 - Jun 2021
A PyTorch-based Speech Toolkit
Role in this project:
ML Engineer
ML EngineerContributions:2 reviews, 106 commits, 5 PRs in 9 months
Contributions summary:Loren contributed to the `speechbrain/speechbrain` repository by implementing knowledge distillation techniques within a speech recognition recipe. They modified the code for experiment setups, including loading teacher model inference results and calculating distillation losses. The changes also include alterations to loss calculations and the strategy for averaging or weighting teacher losses. This demonstrates a focus on improving model performance through knowledge transfer.
voice-recognitionasrspeech-recognitionspeech-separationspeaker-verification
lorenlugosch/end-to-end-SLU
Mar 2019 - Mar 2021
PyTorch code for end-to-end spoken language understanding (SLU) with ASR-based transfer learning
Contributions:172 commits, 1 PR, 48 pushes in 2 years
pytorchunderstandingend-to-endasrtransfer-learning
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