Peyman Bateni

I am currently a Machine Learning Engineer at Meta. Previously, I led Beam AI, a Vancouver-based startup enabling mobile apps to monitor user heart rate, heart rate variability and stress through the selfie camera in real-time.

I completed my graduate studies in Machine Learning at the University of British Columbia under the supervision of Dr. Frank Wood where I divided my time as a researcher between UBC PLAI Group and Inverted AI. I completed my undergraduate studies in Computer Science at the University of British Columbia. During my time at UBC, I also had the pleasure of collaborating with Dr. Leonid Sigal and Dr. Guiseppe Carenini on a range of Computer Vision / NLP problems.

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Research / Publications

I'm broadly interested in developing methods that allow for intelligent reasoning and planning in real-life environments. My past research has primarily focused on few-shot, continual and active learning. As of recently, I have begun working on multi-modal translation models at Meta.

	Feed-Forward Panel Estimation for Discrete-time Survival Analysis of Recurrent Events with Frailty Borna Bateni, Peyman Bateni, Bishwadeep Bhattacharyya, Devin Reeh Preprint, 2024 ArXiv / Bibtex
	Real-Time Monitoring of User Stress, Heart Rate and Heart Rate Variability on Mobile Devices Peyman Bateni, Leonid Sigal IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Demo Track, 2023 ArXiv / Code / Bibtex / PapersWithCode / Video
	On Label-Eﬀicient Computer Vision: Building Fast and Effective Few-Shot Image Classifiers Peyman Bateni, Supervisor: Frank Wood, Second Reader: Leonid Sigal Master's Thesis UBC cIRcle Archives / Code / Bibtex / PapersWithCode / Video
	Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning Peyman Bateni, Jarred Barber, Raghav Goyal, Vaden Masrani, Jan-Willem van de Meent, Leonid Sigal, Frank Wood Social Science Research Network (SSRN) Electronic Journal, 2023 Paper / ArXiv / Code / Bibtex / PapersWithCode
	Enhancing Few-Shot Image Classification with Unlabelled Examples Peyman Bateni, Jarred Barber, Jan-Willem van de Meent, Frank Wood IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Algorithm Track, 2022 Paper / ArXiv / Code / Bibtex / PapersWithCode / Video
	Imagining The Road Ahead: Multi-Agent Trajectory Prediction via Differentiable Simulation Adam Scibior, Vasileios Lioutas, Daniele Reda, Peyman Bateni, Frank Wood IEEE International Conference on Intelligent Transportation (ITSC), 2021 (A short-form version of this paper was also presented at the Autonomous Driving: Perception, Prediction and Planning Workshop at CVPR 2021 where it was awarded Best Paper) Paper / ArXiv / Code / Bibtex / PapersWithCode / Video
	Neural RST-based Evaluation of Discourse Coherence Grigorii Guz, Peyman Bateni*, Darius Muglich, Giuseppe Carenini Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL) and the International Joint Conference on Natural Language Processing (IJCNLP)*, 2020 Paper / ArXiv / Code / Bibtex / PapersWithCode / Video
	Improved Few-Shot Visual Classification Peyman Bateni, Raghav Goyal, Vaden Masrani, Frank Wood, Leonid Sigal IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 (A short-form version of this paper was also presented at the Visual Learning with Limited Labels Workshop at CVPR 2020) Paper / ArXiv / Code / Bibtex / PapersWithCode / Video

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