Summary
Thomas Ciarfuglia is an Assistant Professor and senior software engineer with over a decade of experience turning robotics and computer vision research into robust, real-world systems. He combines deep expertise in ROS, C++, and Python with advanced perception methods (3D vision, SLAM, deep learning), and his early work on deep-learning visual odometry was a finalist for ICRA’s Best Computer Vision Paper Award. He has led system integration for large EU projects, designed mission-critical state machines and multi-sensor perception pipelines, and even rescued and redesigned an HRI system using Whisper and an LLM-driven voice interface. His applied research spans precision agriculture, sports data science, and smart-city autonomy—securing external funding and working closely with domain experts to deploy self- and semi-supervised models in the field. A hands-on mentor and educator, he has taught graduate-level courses, supervised PhD students, and guided over 100 undergraduate theses, frequently converting top projects into collaborations and publications. Practical and ownership-oriented, he is equally comfortable soldering embedded boards as he is architecting cloud-to-edge AI systems for autonomous platforms.
11 years of coding experience
6 years of employment as a software developer
Computational Investing, Computational Investing at Coursera
Dottorato di Ricerca - PhD Mechatronics Robotics and Automation Engineering, Dottorato di Ricerca - PhD Mechatronics Robotics and Automation Engineering at Università degli Studi di Perugia
Mechanics of Materials, Mechanics of Materials at MitX
Introduction to Hadoop and MapReduce, Introduction to Hadoop and MapReduce at Udacity
English