deep learning for bioacoustics &
AI for social good
mark [dot] thomas @ dal [dot] ca
I am third-year PhD candidate in computer science @ Dalhousie University under the supervision of Stan Matwin. My main interests are in applying deep learning to the area of bioacoustics. Specifically, I work on algorithms for detecting endangered baleen whale vocalizations in acoustic recordings.
In late November I will be giving an invited talk at the MERIDIAN & Ocean Networks Canada Workshop in Victoria, BC.
In early December I will be presenting two abstracts at the 178th Meeting of the Acoustical Society of America in San Diego, California.
Immediately after the ASA Meeting, I will be attending NeurIPS 2019 in Vancouver, BC and presenting a poster at the AI for Social Good Workshop.
Thomas, M., Martin, B., and Matwin., S. (2019) Detecting Endangered Baleen Whales within Acoustic Recordings using Region-based Convolutional Neural Networks. Joint Workshop on AI for Social Good at the 33rd Conference on Neural Information Processing Systems (NeurIPS 2019). [arXiv coming soon]
Thomas, M., Martin, B., Kowarski, K., Gaudet, B., and Matwin., S. (2019) Marine Mammal Species Classification using Convolutional Neural Networks and a Novel Acoustic Representation Joint European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2019). [arXiv]
Thomas, M. (2019) Towards a Novel Data Representation for Classifying Acoustic Signals 32nd Canadian Conference on Artificial Intelligence (Canadian AI 2019). [paper]
PhD: Computer Science, Dalhousie University (2017 - exp. 2021)
MSc: Mathematics & Statistics, Acadia University (2013 - 2015)
BSc: Mathematics & Statistics and Economics, Acadia University (2009 - 2013)
Intern Machine Learning Scientist @ JASCO Applied Sciences (Jan 2018 - Present)
Data Scientist @ Fix.com (May 2015 - Aug 2017)