Yunyi Zhu

VLDB 2026 Research / reviewers in the wild / expert

dblp:95/6090 · DBLP profile ↗

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13ranked-venue papers

4as first author

10since 2021 · last 2026

—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 8 · 2 first-author · 6 since 2021Artificial intelligence and machine learning · 5 · 2 first-author · 4 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

Year	Publication	Venue	Position
2026	ChromoLCD: LCD-based Compact Reprogrammer for On-the-fly High-Resolution Images on Photochromic Surfaces abstract Color-changing materials, such as photochromic pigments, allow objects to have reprogrammable multicolor surface images. Existing systems that reprogram these images are based on projectors and LEDs, each with advantages and limitations in device portability and image resolution. In this paper, we present ChromoLCD, a surface reprogrammer that uses a liquid crystal display (LCD) to achieve a compact handheld device without sacrificing image resolution. ChromoLCD consists of an LCD panel with a custom backlight containing R,G,B and UV LEDs, forming high-resolution light patterns with the required wavelengths. The compact form factor of ChromoLCD enables on-the-fly reprogramming of everyday surfaces. Our technical evaluation shows that ChromoLCD achieves a resolution of 25 ppi, which is 8 times better than the prior work. We demonstrate ChromoLCD with three applications, including the stamping of reprogrammable AR markers on a kitchen counter, on-the-fly designs on personal accessories, and reference pictures on a whiteboard. Yunyi Zhu, Katherine Arianna Yan, Emily Guan, Alexandru Luchianov, Eden Hen, Stefanie Mueller 0001	TEI	1
2025	TactStyle: Generating Tactile Textures with Generative AI for Digital Fabrication abstract CHI ’25, April 26–May 01, 2025, Yokohama, Japan Faraz Faruqi, Maxine Perroni-Scharf, Jaskaran Singh Walia, Yunyi Zhu, Shuyue Feng, Donald Degraen, Stefanie Mueller 0001	CHI	4
2025	FiberCircuits: A Miniaturization Framework To Manufacture Fibers That Embed Integrated Circuits Cédric Honnet, Wedyan Babatain, Yiyue Luo, Ozgun Kilic Afsar, Chloe Bensahel, Sarah Nicita, Yunyi Zhu, Andreea Danielescu 0001, Neil Gershenfeld, Joseph A. Paradiso	UIST	7
2025	Ego4D: Around the World in 3,600 Hours of Egocentric Video abstract We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite. It offers 3,670 hours of daily-life activity video spanning hundreds of scenarios (household, outdoor, workplace, leisure, etc.) captured by 931 unique camera wearers from 74 worldwide locations and 9 different countries. The approach to collection is designed to uphold rigorous privacy and ethics standards, with consenting participants and robust de-identification procedures where relevant. Ego4D dramatically expands the volume of diverse egocentric video footage publicly available to the research community. Portions of the video are accompanied by audio, 3D meshes of the environment, eye gaze, stereo, and/or synchronized videos from multiple egocentric cameras at the same event. Furthermore, we present a host of new benchmark challenges centered around understanding the first-person visual experience in the past (querying an episodic memory), present (analyzing hand-object manipulation, audio-visual conversation, and social interactions), and future (forecasting activities). By publicly sharing this massive annotated dataset and benchmark suite, we aim to push the frontier of first-person perception. Kristen Grauman, Andrew Westbury, Eugene Byrne, Vincent Cartillier, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang 0007, Devansh Kukreja, Miao Liu 0007, Xingyu Liu 0001, Tushar Nagarajan, Ilija Radosavovic, Santhosh K. Ramakrishnan, Fiona Ryan, Jayant Sharma 0002, Michael Wray, Mengmeng Xu 0006, Eric Zhongcong Xu, Chen Zhao 0002, Siddhant Bansal, Dhruv Batra, Sean Crane, Tien Do, Morrie Doulaty, Akshay Erapalli, Christoph Feichtenhofer, Adriano Fragomeni, Qichen Fu, Abrham Gebreselasie, Cristina González, James Hillis, Xuhua Huang, Yifei Huang 0002, Wenqi Jia 0001, Weslie Khoo, Jáchym Kolár, Satwik Kottur, Anurag Kumar 0003, Federico Landini, Yanghao Li, Zhenqiang Li 0002, Karttikeya Mangalam, Raghava Modhugu, Jonathan Munro, Tullie Murrell, Takumi Nishiyasu, Will Price, Paola Ruiz Puentes, Merey Ramazanova, Leda Sari, Kiran K. Somasundaram, Audrey Southerland, Yusuke Sugano, Ruijie Tao, Minh Vo, Xindi Wu, Takuma Yagi, Ziwei Zhao 0003, Yunyi Zhu, Pablo Andrés Arbeláez, David Crandall, Dima Damen, Giovanni Maria Farinella, Christian Fügen, Bernard Ghanem, Vamsi K. Ithapu, C. V. Jawahar, Hanbyul Joo, Kris Makoto Kitani, Haizhou Li 0001, Richard A. Newcombe, Aude Oliva, Hyun Soo Park, James M. Rehg, Yoichi Sato 0001, Jianbo Shi, Zheng Shou 0001, Antonio Torralba 0001, Lorenzo Torresani, Mingfei Yan, Jitendra Malik	IEEE Trans. Pattern Anal. Mach. Intell.	64
2024	PortaChrome: A Portable Contact Light Source for Integrated Re-Programmable Multi-Color Textures abstract In this paper, we present PortaChrome, a portable light source that can be attached to everyday objects to reprogram the color and texture of surfaces that come in contact with them. When PortaChrome makes contact with objects previously coated with photochromic dye, the UV and RGB LEDs inside PortaChrome create multi-color textures on the objects. In contrast to prior work, which used projectors for the color-change, PortaChrome has a thin and flexible form factor, which allows the color-change process to be integrated into everyday user interaction. Because of the close distance between the light source and the photochromic object, PortaChrome creates color textures in less than 4 minutes on average, which is 8 times faster than prior work. We demonstrate PortaChrome with four application examples, including data visualizations on textiles and dynamic designs on wearables. Yunyi Zhu, Cédric Honnet, Yixiao Kang, Junyi Zhu 0001, Angelina J. Zheng, Kyle Heinz, Grace Tang, Luca Musk, Michael Wessely, Stefanie Mueller 0001	UIST	1
2024	Fault diagnosis of wind turbine gearbox under limited labeled data through temporal predictive and similarity contrast learning embedded with self-attention mechanism Yunyi Zhu, Zheng Qian	Expert Syst. Appl.	1
2023	A partial domain adaptation scheme based on weighted adversarial nets with improved CBAM for fault diagnosis of wind turbine gearbox Yunyi Zhu, Zheng Qian	Eng. Appl. Artif. Intell.	1
2022	InfraredTags: Embedding Invisible AR Markers and Barcodes Using Low-Cost, Infrared-Based 3D Printing and Imaging Tools abstract Existing approaches for embedding unobtrusive tags inside 3D objects require either complex fabrication or high-cost imaging equipment. We present InfraredTags, which are 2D markers and barcodes imperceptible to the naked eye that can be 3D printed as part of objects, and detected rapidly by low-cost near-infrared cameras. We achieve this by printing objects from an infrared-transmitting filament, which infrared cameras can see through, and by having air gaps inside for the tag’s bits, which appear at a different intensity in the infrared image. Mustafa Doga Dogan, Ahmad Taka, Michael Lu, Yunyi Zhu, Akshat Kumar, Aakar Gupta, Stefanie Mueller 0001	CHI	4
2022	Ego4D: Around the World in 3, 000 Hours of Egocentric Video abstract We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite. It offers 3,670 hours of dailylife activity video spanning hundreds of scenarios (household, outdoor, workplace, leisure, etc.) captured by 931 unique camera wearers from 74 worldwide locations and 9 different countries. The approach to collection is designed to uphold rigorous privacy and ethics standards, with consenting participants and robust de-identification procedures where relevant. Ego4D dramatically expands the volume of diverse egocentric video footage publicly available to the research community. Portions of the video are accompanied by audio, 3D meshes of the environment, eye gaze, stereo, and/or synchronized videos from multiple egocentric cameras at the same event. Furthermore, we present a host of new benchmark challenges centered around understanding the first-person visual experience in the past (querying an episodic memory), present (analyzing hand-object manipulation, audio-visual conversation, and social interactions), and future (forecasting activities). By publicly sharing this massive annotated dataset and benchmark suite, we aim to push the frontier of first-person perception. Project page: https://ego4d-data.org/ Kristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang 0007, Miao Liu 0007, Xingyu Liu 0001, Tushar Nagarajan, Ilija Radosavovic, Santhosh K. Ramakrishnan, Fiona Ryan, Jayant Sharma 0002, Michael Wray, Mengmeng Xu 0006, Eric Zhongcong Xu, Chen Zhao 0002, Siddhant Bansal, Dhruv Batra, Vincent Cartillier, Sean Crane, Tien Do, Morrie Doulaty, Akshay Erapalli, Christoph Feichtenhofer, Adriano Fragomeni, Qichen Fu, Abrham Gebreselasie, Cristina González, James Hillis, Xuhua Huang, Yifei Huang 0002, Wenqi Jia 0001, Weslie Khoo, Jáchym Kolár, Satwik Kottur, Anurag Kumar 0003, Federico Landini, Yanghao Li, Zhenqiang Li 0002, Karttikeya Mangalam, Raghava Modhugu, Jonathan Munro, Tullie Murrell, Takumi Nishiyasu, Will Price, Paola Ruiz Puentes, Merey Ramazanova, Leda Sari, Kiran K. Somasundaram, Audrey Southerland, Yusuke Sugano, Ruijie Tao, Minh Vo, Xindi Wu, Takuma Yagi, Ziwei Zhao 0003, Yunyi Zhu, Pablo Andrés Arbeláez, David Crandall, Dima Damen, Giovanni Maria Farinella, Christian Fügen, Bernard Ghanem, Vamsi K. Ithapu, C. V. Jawahar, Hanbyul Joo, Kris Makoto Kitani, Haizhou Li 0001, Richard A. Newcombe, Aude Oliva, Hyun Soo Park, James M. Rehg, Yoichi Sato 0001, Jianbo Shi, Zheng Shou 0001, Antonio Torralba 0001, Lorenzo Torresani, Mingfei Yan, Jitendra Malik	CVPR	63
2021	Lenticular Objects: 3D Printed Objects with Lenticular Lens Surfaces That Can Change their Appearance Depending on the Viewpoint abstract In this paper, we present a method that makes 3D objects appear differently under different viewpoints. We accomplish this by 3D printing lenticular lenses across the curved surface of objects. By calculating the lens distribution and the corresponding surface color patterns, we can determine which appearance is shown to the user at each viewpoint. Jiani Zeng, Honghao Deng, Yunyi Zhu, Michael Wessely, Axel Kilian, Stefanie Mueller 0001	UIST	3
2020	CurveBoards: Integrating Breadboards into Physical Objects to Prototype Function in the Context of Form abstract CurveBoards are breadboards integrated into physical objects. In contrast to traditional breadboards, CurveBoards better preserve the object's look and feel while maintaining high circuit fluidity, which enables designers to exchange and reposition components during design iteration. Since CurveBoards are fully functional, i.e., the screens are displaying content and the buttons take user input, designers can test interactive scenarios and log interaction data on the physical prototype while still being able to make changes to the component layout and circuit design as needed. We present an interactive editor that enables users to convert 3D models into CurveBoards and discuss our fabrication technique for making CurveBoard prototypes. We also provide a technical evaluation of CurveBoard's conductivity and durability and summarize informal user feedback. Junyi Zhu 0001, Lotta-Gili Blumberg, Yunyi Zhu, Martin Nisser, Ethan Levi Carlson, Xin Wen 0025, Kevin Shum, Jessica Ayeley Quaye, Stefanie Mueller 0001	CHI	3
2020	MorphSensor: A 3D Electronic Design Tool for Reforming Sensor Modules abstract MorphSensor is a 3D electronic design tool that enables designers to morph existing sensor modules of pre-defined two-dimensional shape into free-form electronic component arrangements that better integrate with the three-dimensional shape of a physical prototype. MorphSensor builds onto existing sensor module schematics that already define the electronic components and the wiring required to build the sensor. Since MorphSensor maintains the wire connections throughout the editing process, the sensor remains fully functional even when designers change the electronic component layout on the prototype geometry. We detail the MorphSensor editor that supports designers in re-arranging the electronic components, and discuss a fabrication pipeline based on customized PCB footprints for making the resulting freeform sensor. We then demonstrate the capabilities of our system by morphing a range of sensor modules of different complexity and provide a technical evaluation of the quality of the resulting free-form sensors. Junyi Zhu 0001, Yunyi Zhu, Jiaming Cui, Leon Cheng, Jackson C. Snowden, Mark Chounlakone, Michael Wessely, Stefanie Mueller 0001	UIST	2
2007	A Flexible Annealing Chaotic Neural Network to Maximum Clique Problem abstract Based on the analysis and comparison of several annealing strategies, we present a flexible annealing chaotic neural network which has flexible controlling ability and quick convergence rate to optimization problem. The proposed network has rich and adjustable chaotic dynamics at the beginning, and then can converge quickly to stable states. We test the network on the maximum clique problem by some graphs of the DIMACS clique instances, p-random and k random graphs. The simulations show that the flexible annealing chaotic neural network can get satisfactory solutions at very little time and few steps. The comparison between our proposed network and other chaotic neural networks denotes that the proposed network has superior executive efficiency and better ability to get optimal or near-optimal solution. Gang Yang 0001, Yunyi Zhu	Int. J. Neural Syst.	4