Mirco Ravanelli, PhD, P.Eng
- Associate Professor, Computer Science and Software Engineering
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Sign in to editResearch areas: Conversational AI, Multimodal AI, Deep Learning, Foundation Models, Large Language Models (LLMs), Audio Tokens, Representation Learning, Self-Supervised Learning, Interpretable AI, Efficient AI, Speech and Audio Processing, Sequence Modeling, Open-Source AI.
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Biography
Short Bio
I am an AI researcher, educator, and open-source leader working on the next generation of intelligent machines.I am an Associate Professor at Concordia University, Adjunct Professor at Université de Montréal, and Associate Member of Mila – Quebec AI Institute. My research focuses on deep learning for Conversational AI, multimodal foundation models, interpretable AI, and efficient machine learning.My work has resulted in over 100 scientific publications and has been recognized through international awards, including the Amazon Research Award. I had the privilege of completing my postdoctoral training at Mila under the supervision of Yoshua Bengio.I am the founder and leader of SpeechBrain, one of the world's most widely adopted open-source toolkits for speech and conversational AI, used by researchers and engineers across academia and industry. SpeechBrain has become a global community effort, helping democratize access to cutting-edge AI technologies.Beyond research, I am passionate about education and mentorship. I believe that advancing AI requires not only scientific breakthroughs but also training the next generation of researchers and engineers to develop AI responsibly and for the benefit of society.Research interests: Conversational AI • Multimodal LLMs • Audio Tokens • Representation Learning • Interpretable AI • Efficient Deep Learning • Open-Source AI
Teaching activities
Teaching
I teach undergraduate and graduate courses in Machine Learning and Conversational AI. My teaching has been recognized through several awards, including the President's Excellence in Teaching Award (2026) and the Gina Cody School Award for Excellence in Teaching by a Junior Faculty (2025).
Research activities
Research Interests
My research focuses on Conversational AI, multimodal foundation models, and deep learning. I develop methods that enable machines to learn efficient, interpretable, and robust representations from speech, audio, language, and other modalities. My current interests include multimodal LLMs, audio tokenization, self-supervised learning, efficient AI, and interpretable deep learning, with a strong commitment to open-source research through the SpeechBrain project.
Publications
Publication list
The list of my publications is available here:
https://sites.google.com/site/mircoravanelli/papers