Energy and computing are two inseparable challenges for modern society: the energy demands of artificial intelligence (AI) and data-centric applications are growing exponentially, outpacing the advances in computing hardware. Future computing must deliver more useful work with more limited energy and thermal budgets. AI hardware must process information at low power, move vast amounts of data at high bandwidth, and dissipate heat efficiently at the same time.
Regardless of whether silicon remains dominant or it is partly replaced by emerging materials, the fundamentals underpinning the enormous energy consumption remain the same and cannot be treated separately: electron and phonon transport, atomic disorder and interfaces. My research develops foundational theory for heat and charge transport, to identify energy efficiency limits of computing hardware and guides the design of energy-efficient materials and systems.
Frontier technologies based on solid-state devices will soon meet the boundary of our usual understanding of energy transport. Our pursuit of faster computing, higher energy efficiency and better sustainability requires major advancements in the study of quantum energy transport. Our research on electron/phonon dynamics in charge and heat transport then has both technological and scientific importance that could lead to discovery of novel transport phenomena and disruptive technology strategies.
My PhD research is motivated by the following challenges in our community:
My Postdoc research is motivated by the growing energy demand of computing, and the fact that the energy efficiency of existing computing hardware is still orders of magnitude higher than the thermodynamic Landauer limit (theoretical minimum amount of energy required to erase one bit of information). I focus on examining the atomic details and fundamental energy limits across the computing stack, and provide practical guidelines to device designs.
A common theme of my research is to address how close we can get to fundamental energy limits and how atomistic understanding can enable more efficient hardware. Computing provides an immediate application for my research, but the broader goal is to establish transferable principles for energy transport in materials, devices and systems.
My research aims to tackle the challenges above along these directions:
Fundamental Limits of Energy-Efficient Computing: From Anderson Localization to Transistor Switching
Nonequilibrium Energy Carrier Transport
High Temperature Thermal Transport
Temperature-Dependent Optical Responses
[Community Software: FourPhonon](https://zrhan.notion.site/Community-Software-FourPhonon-4d813e9773774925bc83d7ac4cd56214)