Eric Cheng

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About

Eric Cheng is a leading researcher in functional programming and domain-specific languages, with a focus on the theory and optimization of arrows—a powerful abstraction for computation that is more general than monads. His major contributions center on the development and formalization of *causal commutative arrows* (CCAs), a restricted class of arrows that enable efficient, provably correct optimization for signal processing and dataflow computations. Cheng’s work is foundational to the Yampa domain-specific language, which leverages arrows for reactive and real-time systems. His most-cited paper, “Causal commutative arrows and their optimization” (2009, 47 citations), introduces key techniques for optimizing arrow-based programs, while his subsequent 2011 paper (20 citations) deepens the theoretical framework. Together, these works have shaped how researchers and practitioners design high-performance, composable abstractions for streaming and interactive applications, earning Cheng recognition as a key contributor to the practical advancement of functional reactive programming.