Connected Human Intelligence, Networks & Evolution
At Self-Stacked-Systems Co-Lab, we believe that intelligence follows an underlying pattern in all its forms — whether biological or artificial. Our mission is to advance knowledge at the intersection of cognitive neuroscience, human development, species evolution, complex systems, and robotics, forging a framework of connected intelligence and a more ethical adoption of AI as a human-driven tool.
Our inspiration, Professor Michael Commons, Assistant Professor at Harvard Medical School, Dept. of Psychiatry, has spent his career studying learning, development, and evolution. First animals, then people, and now machines. A holder of several patents, his methods promise to continue the AI revolution for the benefit of human-machine interaction.
Our Vision & Goals
We envision a future where the principles of cognition, evolution, and technology converge to illuminate the mechanisms of adaptive intelligence. By bridging disciplines, we aim to decode the emergent properties of intelligence and apply these insights to create more resilient, adaptive, and ethical systems — both human and artificial.
Our Core Principles
- Interdisciplinarity – Knowledge thrives where fields intersect. We embrace a fusion of neuroscience, computational cognition, robotics, and complexity science.
- Collaboration – Discovery is a collective endeavor. We cultivate a research environment where diverse perspectives and expertise merge to tackle fundamental questions.
- Evolutionary Perspective – Understanding intelligence requires a deep exploration of how cognitive and neural architectures have emerged through evolution.
- Complexity & Networks – Intelligence cannot be reduced to isolated components. We study cognition through the lens of network science, self-organization, and hierarchical processing.
- Biologically Inspired Approach – AI is the result of reverse engineering the brilliance of natural processes.
- Ethical Considerations – Our approach delves on the biologically plausibility of AI, reducing costs and optimizing efficiency in an exponential manner, mimicking the processes underlying the cost-economy of the brain.
What We Do
- Investigate the neural and computational principles of intelligence and cognition.
- Explore the evolution of cognitive architectures and their application in AI and robotics.
- Develop new frameworks for understanding complex adaptive systems.
- Bridge gaps between human and machine intelligence through innovative modeling and experimentation.
We are scientists, engineers, and thinkers, united by a commitment to unlocking the mysteries of intelligence and fostering meaningful innovation. Join us in shaping the future of connected intelligence, one discovery at a time.
