NSF announces new investment areas for the Emerging Frontiers in Research and Innovation program

The U.S. National Science Foundation Directorate for Engineering plans one new topic area for the NSF Emerging Frontiers in Research and Innovation (EFRI) program in Fiscal Year 2024: Engineering Organoid Intelligence (EOI). Additionally, the EFRI program plans to employ an Ideas Lab approach to stimulate interdisciplinary research into emerging technologies for personalized learning for engineering education. These topics were developed with input from the research community.

Engineering Organoid Intelligence
For many years, engineers have aspired to emulate the complexity of the human brain in computation through the design of artificial intelligence systems. However, compared to the human brain, current AI systems lack energy efficiency, computational flexibility and robustness. While AI is increasingly being incorporated into our daily lives, it is reaching its limits due to such inefficiencies and consequent unsustainable energy requirements.

The EOI EFRI topic will support fundamental research on the development of engineered biocomputers using brain organoids (3D brain cell cultures) to utilize the computational capacity of the brain. Organoid cultures will be interfaced with electronics to deliver input and export output to external digital systems.

EOI will build on recent advances in 3D neural cell culture methods and neuronal "wetware" to harness the computing power of the brain and overcome the challenges of current AI systems. Neurons can process information in real time with low levels of energy consumption. Using 3D neuronal cell culture allows for a thousandfold increase in cell density as compared to 2D culture, exponentially increasing the number of synapses and neuronal connections available for the development of wetware systems with learning capacity.

Transformative research outcomes arising from this program could include the development of biological computing systems that transcend the energy limitations of current AI systems; increased understanding of human cognition, learning and memory; and insights into neurological disease.

Integrating ethical, legal and social considerations of the proposed research will be essential to this topic.

Personalized learning for engineering education 
Dynamic personalized assessment of learning is the next frontier in engineering education. Understanding how individuals are learning in real time and tailoring instruction accordingly will afford great opportunities for designing effective and inclusive engineering education.

Personalized teaching and learning in engineering, driven by learners, will integrate sensors and data to understand cognitive practices and provide real-time feedback on learner progress. Integration of physiological, physical and cognitive cues with knowledge management and retrieval processes will inform researchers' understanding of an individual learner's process.

Successfully developing technologies to monitor student learning and proactively adjust for optimal learning will require convergent advances in neuroscience, sensing, AI and human cognition.

Researchers will use the Ideas Lab framework to catalyze interactions between researchers from each of these communities, incorporating innovative approaches while forming interdisciplinary teams to develop personalized learning for engineering education.