Min Li

About

Min Li is a professor at the University of Washington College of Education, with research interests centered on the development of children and youth, measurement and statistics, and quantitative research methods. His work emphasizes assessments that go beyond measuring learning outcomes to empower students and improve learning processes. His research aims to study and model how student learning can be accurately, adequately, and fairly assessed in both large-scale testing and classroom settings, especially in tech-rich environments, to provide rich and actionable assessment results for learners and educators. His approach combines cognitive sciences and psychometric modeling approaches within STEM disciplines, focusing on issues of validity and validation, including examining cognitive demands of science items, using natural language processing to detect testing bias, modeling student reasoning and problem-solving strategies, automating grading of written responses, and addressing measurement issues in instructional tasks. His recent projects include developing equitable assessments in computer science, extracting actionable results from diagnostic assessments, and creating authentic and fair assessments in STEM fields. His scholarly contributions include numerous publications on topics such as science assessment, student reasoning, and test validity.

Research topics

• Computer Science
• Artificial Intelligence
• Machine Learning
• Optoelectronics
• Materials science
• Data science
• Telecommunications
• Human–computer interaction
• Physics
• Optics

Selected publications

• Programmable phase-change metasurfaces on waveguides for multimode photonic convolutional neural network

  Nature Communications · 337 citations

  Senior authorCorresponding

  Abstract Neuromorphic photonics has recently emerged as a promising hardware accelerator, with significant potential speed and energy advantages over digital electronics for machine learning algorithms, such as neural networks of various types. Integrated photonic networks are particularly powerful in performing analog computing of matrix-vector multiplication (MVM) as they afford unparalleled speed and bandwidth density for data transmission. Incorporating nonvolatile phase-change materials in…

  DOI

• On-the-fly closed-loop materials discovery via Bayesian active learning

  Nature Communications · 325 citations

  Abstract Active learning—the field of machine learning (ML) dedicated to optimal experiment design—has played a part in science as far back as the 18th century when Laplace used it to guide his discovery of celestial mechanics. In this work, we focus a closed-loop, active learning-driven autonomous system on another major challenge, the discovery of advanced materials against the exceedingly complex synthesis-processes-structure-property landscape. We demonstrate an autonomous materials discover…

  DOI

• Nonvolatile Electrically Reconfigurable Integrated Photonic Switch Enabled by a Silicon PIN Diode Heater

  Advanced Materials · 2020 · 252 citations

  Reconfigurability of photonic integrated circuits (PICs) has become increasingly important due to the growing demands for electronic-photonic systems on a chip driven by emerging applications, including neuromorphic computing, quantum information, and microwave photonics. Success in these fields usually requires highly scalable photonic switching units as essential building blocks. Current photonic switches, however, mainly rely on materials with weak, volatile thermo-optic or electro-optic modu…

  DOI

• Optical multi-beam steering and communication using integrated acousto-optics arrays

  Nature Communications · 2025-05-15 · 13 citations

  articleOpen accessSenior author

  Optical beam steering enables optical sensing, imaging, and long-range communication over free space. Despite the inherent speed of light, advanced applications increasingly require simultaneous steering of multiple, independently controlled beams, to enhance imaging throughput, boost communication bandwidth, and control qubit arrays for scalable quantum computing. However, precise multi-beam steering and control remain a significant challenge with current solid-state beam steering technologies,…

  PublisherOA PDFDOI

• Non-volatile tuning of cryogenic silicon photonic micro-ring modulators

  Nature Communications · 2025-10-21 · 3 citations

  articleOpen access

  Quantum computing, ultra-low-noise sensing, and high-energy physics experiments often rely on superconducting circuits or semiconductor qubits and devices operating at deep cryogenic temperatures (4K and below). Photonic integrated circuits and interconnects have been demonstrated for scalable communications and optical domain transduction in these systems. Due to energy and area constraints, many of these devices need enhanced light-matter interaction, provided by photonic resonators. A key cha…

  PublisherOA PDFDOI

Recent grants

• CAREER: Integration of 2D materials for broadband silicon photonics

  NSF · $400k · 2014–2019

• CAREER: Integration of 2D materials for broadband silicon photonics

  NSF · $90k · 2018–2020

• Collaborative Research: Nanofabricated multisite opto-electrical probes for optogenetic stimulation and neuronal recording applications

  NSF · $311k · 2013–2017

Frequent coauthors

• Ying Zhang

  Jining Medical University

  372 shared

• Jing Yang

  Southern Medical University

  72 shared

• Huan Zhang

  University of Chinese Academy of Sciences

  66 shared

• Tao Chen

  Xi'an Polytechnic University

  63 shared

• Yan Sun

  Peking University

  54 shared

• Huan Li

  52 shared

• Jian Zhang

  Zhejiang Academy of Forestry

  52 shared

• Jiayi Chen

  48 shared

Labs

• Measurement & StatisticsPI

Education

• Ph.D., Applied Physics

  California Institute of Technology

  2007

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