Eduardo Izquierdo Torres is an Associate Professor in the Department of Electrical and Computer Engineering at Rose-Hulman Institute of Technology. His academic work bridges multiple disciplines including Artificial Intelligence, Cognitive Science, Neuroscience, Robotics, and Electrical and Computer Engineering, contributing to the excellence of education at Rose-Hulman through his highly interdisciplinary approach. Dr. Izquierdo received his academic degrees from prestigious institutions: Ph.D. in Computer Science and AI (2008) from the Centre for Computational Neuroscience and Robotics at the University of Sussex, Brighton, UK Master of Science in Intelligent Systems (2004) from the University of Sussex, Brighton, UK Bachelor of Science in Computer Engineering (2002) from Universidad Simon Bolivar, Venezuela Dr. Izquierdo's research focuses on understanding intelligence in living organisms and developing artificial systems with similar robustness, flexibility, and adaptivity. His work spans Evolutionary and Adaptive Systems, including Evolutionary Robotics, Cognitive Science, Artificial Life, Evolutionary Computation, Morphological Computation, Embodied Intelligence, Evolutionary Hardware, Neuromorphic Engineering, BioRobotics, NeuroRobotics, and Biologically-Inspired Artificial Intelligence. He takes an integrated approach, studying how behavior arises from the interaction between brains, bodies, and environments through computational models of complete brain-body-environment systems. His recent publications demonstrate a strong trend toward understanding social interaction, neural plasticity, and multifunctional neural circuits, particularly using C. elegans as a model organism. His work combines computational neuroscience with artificial life principles to explore how complex behaviors emerge from neural circuits, with applications in robotics and artificial intelligence. Many of his recent papers focus on perceptual crossing, central pattern generation, and the role of homeostatic plasticity in neural networks. Dr. Izquierdo has received significant recognition for his research: NSF CAREER award: "From connectome to behavior: computational models of multifunctional neural circuits in C. elegans" (2019-2025), $882,772.00 as PI NSF Workshop grant: "Functional logic of neural circuits: diamonds in the rough" (Part 2, 2022-2023), $50,000.00 as Co-PI NSF Workshop grant: "Functional logic of neural circuits: diamonds in the rough" (Part 1, 2021-2022), $50,000.00 as Co-PI NSF Supplemental grant: "Reinforcement learning in dynamical recurrent neural networks" (2021), $50,683.00 as PI Winner of the 2021 ISAL (International Society of Artificial Life) Outstanding Student Paper Award Dr. Izquierdo has advised numerous graduate students, including PhD candidates Lindsay Stolting, Zachary Laborde, Andrew Claros, Josh Nunley, and Haily Merritt, as well as postdoctoral researchers Dr. Madhavun Candadai and Dr. Jason Yoder. His research has been consistently supported by multiple NSF grants totaling over $1.5 million, demonstrating the significance and impact of his work in computational neuroscience and bio-inspired AI. His grants have focused on understanding neural circuits in C. elegans, reinforcement learning in neural networks, and computational models of behavior. Dr. Izquierdo leads a research group focused on computational neuroethology and bio-inspired AI, with collaborative projects involving researchers from multiple institutions. His lab develops computational models of brain-body-environment systems, with particular expertise in neuromechanical models of C. elegans. He has created numerous open-source software tools for analysis and simulation, including packages for information theoretic analysis, connectome exploration, and neuromechanical modeling. His collaborative work with researchers like Dr. Erick Olivares, Prof. Randall Beer, and others has produced significant advances in understanding how neural circuits generate behavior.
