AI Systems & Infrastructure
This course introduces students to streamlined interaction with AI models and systems, as well as implementation and deployment of scalable, production-ready AI systems on real-world infrastructures.
University-level courses I teach, covering lectures, literatures, exercises, and exam assessments.
This course introduces students to streamlined interaction with AI models and systems, as well as implementation and deployment of scalable, production-ready AI systems on real-world infrastructures.
Student projects I supervise, covering project proposals, problem definition, design choices, and final delivery.
A Master's semester project on learning trajectory representations that generalize across tasks, geographic regions, and transportation modes, modeling vehicle and vessel trajectories relative to road networks and sea depth contours and handling their widely varying sampling intervals.
A Master's semester project on bringing a data-centric perspective to trajectory machine learning, assessing the quality of training data and developing filtering and augmentation methods to improve model performance on downstream tasks.
A Bachelor's semester project on developing a computationally lightweight model deployable on embedded devices to remove humans from images or video feeds, serving as a prototype GDPR-compliant surveillance system.
Oral presentations, tutorials, and guest lectures delivered at international conferences and universities.
* Equal Contribution