The research is in two areas: general purpose parallel computing, and models of neural computation. The first area will investigate the possibility of finding a standardizing bridging model for parallel computing, at a level intermediate between the architecture and language levels. Such a standard would insulate the development of software and hardware and thereby speed the success of the parallel computing industry. The bulk-synchronous parallel (BSP) model will be considered as the prime candidate. The second area of research will further develop a discrete model of neural computation that is both weak enough that its constituents are plausibly simulated by human cortex, yet strong enough that some basic tasks of learning and memory can be implemented on it.
