The Scope

In his 1988 book, Hans Moravec observed: “It is comparatively easy to make computers exhibit adult-level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility,” This puzzling insight – now known as Moravec’s paradox – reminds researchers that the prevailing paradigms of sensing and computational architecture may be fundamentally unsuited for performing physical tasks efficiently. 

To explore a radically different approach to perception, computation, control, and communication architectures for next-generation autonomy, we organize a workshop on “Emerging Architectures for Sensing, Computing, and Control.” Purdue University would host this 2.5-day event in May 2026, and possibly annually thereafter, bringing together approximately 20 invited speakers from within and outside the university. The speakers will represent a broad range of expertise, including neuroscience, neuromorphic computation, semiconductors, optics, information theory, and control engineering. 

The primary goal of the workshop is to create a shared forum for these diverse research communities that rarely interact within the current conference landscape. Through this community-building effort, the workshop will be a catalyst for launching large-scale, cross-disciplinary collaborative research in the coming decade. This will also be a great venue to attract researchers and stakeholders from different agencies and socialize the community's ideas. 

To provide an initial working structure, this year’s workshop will be organized into four themes, each spanning half a day of updates and discussions: 

1. Fundamental limits and underlying science 

2. Architectures and their properties 

3. Applications and inspirations 

4. Other perspectives 

Example interpretations of the theme areas: 

1. Fundamental limits and underlying science: Autonomy comprises physical components for sensing, computation, actuation, and communication, each of which is subject to fundamental laws of physics—such as the Rayleigh limit for optical sensing, the Landauer limit for computation, Bode’s integral law for control, and Shannon’s laws for communication, among others yet to be discovered. This track explores the fundamental limits of autonomy and the gaps between these limits and the performance attainable by today’s technologies. 

2. Architectures and their properties: A wide range of computing architectures has been developed to support the growth of AI and autonomous systems. These include artificial neural networks, analog architectures such as very-large-scale integrated (VLSI) circuits, spiking neural networks, optical neural networks, and other bio-inspired mechanisms. This track examines these architectures and their properties, with a focus on identifying core structural characteristics and their implications for usability, scalability, training dynamics, and alignment with physical embodiment. 

3. Applications and inspirations: Inspiration for optimal embodiment may be drawn from specific application domains as well as from the decision-making architectures of biological systems. This track focuses on identifying key features of such embodiments and on exploring the computing and autonomy architectures that are best aligned with the requirements of each application.

4. Other perspectives: This theme provides a venue for participants to present relevant material that does not fit naturally within the three themes above, including alternative viewpoints or contradictory perspectives that may challenge prevailing assumptions.