Marvin Chancán

Marvin Chancán is a Postdoctoral Associate at Yale University's Intelligent Autonomy Lab, led by Ian Abraham. His research focuses on bio-inspired sensing and control for robotic systems, combining deep learning, computer vision, and neuroscience to develop high-performance neural architectures for autonomous navigation. He holds a Ph.D. in Electrical Engineering and Robotics from Queensland University of Technology (QUT, 2022), an M.S. in Applied Control from PUC-Rio (2012), and a B.S. in Mechatronics Engineering from Universidad Nacional de Ingeniería (UNI, 2009).

His work bridges biological neural circuits (e.g., insect and mammalian brains) with robotic systems, achieving state-of-the-art results in motion-and-vision-based localization and navigation. His publications appear in top venues like NeurIPS, ICRA, and RSS. Notable contributions include DeepSeqSLAM, CityLearn, and the MVP framework, emphasizing self-supervised and sample-efficient learning.

Chancán has received prestigious awards, including the 2020 QUT HDR High Achiever Award and several scholarships. He has served as a reviewer for journals like Science Robotics and conferences such as IROS. His industry experience spans automation and IT roles across The Americas, Europe, and Oceania.

His research aims to advance autonomous systems through biologically inspired algorithms, with a focus on real-world applications in robotics and autonomous vehicles.