(she/her/hers)
Stanford University
quantum computing, integrated photonics, photonic neural networks, thermal sustainability, optical mechanics
Lingling Fan is a Ph.D. candidate in electrical engineering at Stanford University. Prior to her appointment at Stanford, she received her Bachelor of Science degree in physics, while she worked in the Department of Applied Physics at Yale University. Her research interests are in computational, experimental, and theoretical studies of photonic structures and devices, especially for neural networks, information processing, and radiative cooling applications. She has published more than 21 papers in this field, has given five invited talks at major international conferences, and currently holds two U.S. patents. In addition to her academic research, she completed internships at SWS research Shanghai in 2018 summer and X the Moonshot Factory of Google LLC in 2022 summer. Lingling is a recipient of the National Scholarship from the Ministry of education of China from 2015 to 2018, a Hong Kong Shan-Yuan (C. W. Chu) scholarship in 2016, a Kathy Xu scholarship in 2018, an Engineering Fellowship from Stanford University in 2018, a CLEO presenter award in 2020, a DARE fellowship finalist in 2021 and an EECS rising star travel grant in 2022.
Energy-saving with photonics: photonic synthetic dimension enabled compact and parallel computing and all-year round energy-sustainable thermal management
Photonics towards energy-saving lie at the intersection of electromagnetics, quantum computing, and machine learning. To advance efficient information processing and sustainable energy utilization, we approach this goal by engineering photonic energy, momentum, and qubits and will bring a significant influence on multiple fields such as artificial intelligence and carbon neutralization. However, it faces fundamental limitations such as spatial footprints, control energy consumption, and unpredictable environment to build photonic systems that can process data intelligently and sustainably. To this end, in this talk, I will introduce my research focused on optical frequency comb-based computational hardware that is compact and consumes minimum control energy. I also bridged disciplines to solve challenges in thermal management and light sails.
The first part of this talk focuses on photonic computation. Multi-dimensional convolution lies at the cornerstone of artificial intelligence and represents the most computationally intensive step in convolutional neural networks. However, the hardware performance using digital electronics for such convolution operations is constrained by the low-speed operation, high-power consumption, and poor scalability to large data. We propose a new approach that performs multi-dimensional convolutions in frequency synthetic dimensions. Our scheme can achieve arbitrary multi-dimensional convolution kernels for frequency-encoded information with a simple and low-loss setup. Our work points to using compact and reconfigurable integrated photonic circuits to improve machine learning hardware for state-of-the-art artificial intelligence performances.
The second part of this talk focuses on thermal sustainability. Energy-efficient buildings play an essential role in sustainability, and it is imperative to develop innovations to achieve improved energy efficiency of building HVAC with a reduced carbon footprint. Nevertheless, traditional building materials can hardly achieve both cooling and heating energy savings throughout the year due to excessive heat transfer arising from high emissivity. We demonstrate a new approach of colored low-emissivity films for building wall thermal envelopes to provide year-round energy-saving solutions. Our work can help reduce heat gain and loss by up to 257.6 MJ per installation wall area annually, which would be beneficial for global neutrality and sustainability. The rapid growth of world population also poses a major threat to the global energy supply, which motivates us to explore an optimal nighttime power generation system of power density Watts/m2 for potential applicability without any electricity input. In addition, from a fundamental perspective, we identify the unique signature of nonreciprocity in heat transfer between planar bodies. We demonstrated that nonreciprocal heat transfer could provide new capabilities for manipulating photon heat flow.
Last but not least, I will talk about optical mechanics. Optical forces play a crucial role in light sails for space travel and precise manipulation of the nanoscale. We provide a general understanding of optical forces, in terms of a few parameters that have direct physical meanings. Our work serves as a design tool for complex optical structures in optical tweezers, light sails, and biomedical size-sorting.