Papers
31
Total Citations
626
H-Index
11
About
Hugo de Garis is a pioneering artificial intelligence researcher best known for his groundbreaking work in evolvable hardware, artificial brain development, and biologically inspired cognitive architectures. His career has been defined by an audacious ambition: to build genuinely artificial brains using evolutionary computation and massively parallel hardware systems. De Garis first garnered international attention with his 1993 work on genetic programming applied to "Darwin Machines," laying conceptual groundwork for hardware that could evolve its own neural circuitry. This vision culminated in the CAM-Brain Machine (CBM) project at ATR in Japan, where he pioneered the use of FPGA-based cellular automata to grow and evolve neural network modules at electronic speeds — a system capable of updating 75 million neurons in real time for robot control. These contributions earned him over 130 citations on the foundational CBM papers alone. Later in his career, de Garis turned toward surveying the broader landscape of artificial brain initiatives, co-authoring influential reviews of biologically inspired cognitive architectures that collectively attracted over 170 citations. His work sits at a fascinating intersection of neuroscience, evolutionary computation, and robotics, and his provocative long-term thinking about "artilect" intelligence continues to inspire — and challenge — researchers across disciplines.
Research Focus
Key Achievements
Top Papers
- 1
- 2EVOLVABLE HARDWARE Genetic Programming of a Darwin Machine134 citations · 1993
- 3
- 4
- 5Building an artificial brain using an FPGA based CAM-Brain Machine33 citations · 2000
- 6
- 7Untitled23 citations · 2001
- 8
- 9
- 10