Xiaohan Cheng

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About

Xiaohan Cheng is a pioneering researcher at the forefront of neuromorphic photonics and advanced materials for next-generation computing. Her work centers on developing novel perovskite-based platforms that integrate sensing and processing capabilities, a critical step toward energy-efficient, brain-inspired hardware. In her landmark 2025 study, "Sodium-enhanced perovskite reservoir for photonic in-sensor computing," Cheng introduced a groundbreaking approach that leverages sodium-doped perovskites to create a photonic reservoir computing system. This innovation enables direct in-sensor processing of optical data, dramatically reducing the energy and latency typically required for data transfer between sensors and processors. Already garnering 7 citations in its first year, this work signals a transformative impact on edge computing and artificial intelligence hardware. Cheng’s contributions are particularly notable for bridging materials science and photonic computing, offering a scalable path toward intelligent sensors that can learn and adapt in real time. Her research not only advances fundamental understanding of perovskite optoelectronics but also holds promise for applications in autonomous systems, medical imaging, and environmental monitoring. As a rising star in her field, Cheng continues to push the boundaries of what is possible with photonic in-memory computing.