Jeremy Castagno | Springfield College

Jeremy Castagno

Jeremy Castagno

Assistant Professor of Computer Science
Jeremy Castagno, Springfield College
  • Doctor of Philosophy in Robotics, University of Michigan, Ann Arbor, Mich., 2021
  • Master of Science in Robotics, University of Michigan, Ann Arbor, Mich., 2018
  • Bachelor of Science in Chemical Engineering, Brigham Young University, Provo, Utah, 2013

Jeremy Castagno is an engineer, computer scientist, and roboticist. His area of expertise is in machine learning, simulation/modeling, and developing robust decision-making strategies. His research focuses on new techniques for robot mapping and collaboration. Castagno has won numerous awards in machine learning and artificial intelligence competitions hosted by the Air Force Research Laboratory, the National Security Innovation Network, and the British Royal Navy. Before pursuing academia and becoming a teacher, he worked as control systems engineer at Valero Energy. Castagno loves the outdoors and enjoys hiking, kayaking, and sledding.

Research Interests
  • Localization and Mapping
  • Computer Vision
  • Machine Learning
  • Computational Geometry
Certifications and Memberships
  • Member of Institute of Electrical and Electronics Engineers (IEEE)
  • Member of American Institute of Aeronautics and Astronautics (AIAA)
  • Reviewer for: IEEE Transactions on Intelligent Transportation Systems, AIAA Journal of Aerospace Information Systems, MDPI Sensors, MDPI Remote Sensing

Selected Works

Conferences and Presentations

  • Atkins, E.; Castagno, J. “Rooftop Landings for Safe Urban Drone Operations.” Amazon Re:MARS (2019). Invited Speaker.


  • Castagno, J.; Atkins, E., “Map-Based Planning for Small Unmanned Aircraft Rooftop Landing.” In Handbook on Reinforcement Learning and Control, Vamvoudakis, Y. Wan, F. L. Lewis, D. Cansever (Eds.), Springer, 2021.
  • Castagno, J.; Atkins, E. “Polylidar3D - Fast Polygon Extraction from 3D Data”. Sensors 2020, 20, 4819.
  • Castagno, J.; Atkins, E., “Polylidar – Polygons from Triangular Meshes.” IEEE Robotics and Automation Letters, vol. 5, no. 3, pp. 4634-4641, July 2020.