About

Daphne Wui Yarn Chan is an assistant professor in the Department of Chemical Engineering at Carnegie Mellon University, with a courtesy appointment in Materials Science and Engineering. Her research interests focus on designing polymers to address global sustainability challenges, including energy production, decarbonization, and materials science. She earned her BS in chemical and biomolecular engineering from Johns Hopkins University in 2013 and her Ph.D. in chemical engineering from the Massachusetts Institute of Technology (MIT) in 2019. Under the supervision of Bradley Olsen at MIT, she developed strategies for designing engineering plastics from renewable protein feedstock and approaches for recycling waste tire rubber. Following her doctoral studies, she served as a postdoctoral researcher at the University of Minnesota from 2019 to 2022, working with Marc Hillmyer on self-assembled block polymers and their applications in ultrafiltration membranes. Chan has received several awards recognizing her research contributions, including the University of Minnesota's President's Postdoctoral Fellowship and the MIT Tata Center for Technology and Design Fellowship.

Research topics

• Computer Science
• Artificial Intelligence
• Optics
• Computer vision
• Physics
• Geometry
• Mathematics
• Computer graphics (images)
• Telecommunications
• Acoustics
• Algorithm

Selected publications

• LiTo: Surface Light Field Tokenization

  arXiv (Cornell University) · 2026-03-11

  articleOpen access

  We propose a 3D latent representation that jointly models object geometry and view-dependent appearance. Most prior works focus on either reconstructing 3D geometry or predicting view-independent diffuse appearance, and thus struggle to capture realistic view-dependent effects. Our approach leverages that RGB-depth images provide samples of a surface light field. By encoding random subsamples of this surface light field into a compact set of latent vectors, our model learns to represent both geometry and appearance within a unified 3D latent space. This representation reproduces view-dependent effects such as specular highlights and Fresnel reflections under complex lighting. We further train a latent flow matching model on this representation to learn its distribution conditioned on a single input image, enabling the generation of 3D objects with appearances consistent with the lighting and materials in the input. Experiments show that our approach achieves higher visual quality and better input fidelity than existing methods.

  PublisherOA PDF

• LiTo: Surface Light Field Tokenization

  arXiv (Cornell University) · 2026-03-11

  preprintOpen access

  We propose a 3D latent representation that jointly models object geometry and view-dependent appearance. Most prior works focus on either reconstructing 3D geometry or predicting view-independent diffuse appearance, and thus struggle to capture realistic view-dependent effects. Our approach leverages that RGB-depth images provide samples of a surface light field. By encoding random subsamples of this surface light field into a compact set of latent vectors, our model learns to represent both geometry and appearance within a unified 3D latent space. This representation reproduces view-dependent effects such as specular highlights and Fresnel reflections under complex lighting. We further train a latent flow matching model on this representation to learn its distribution conditioned on a single input image, enabling the generation of 3D objects with appearances consistent with the lighting and materials in the input. Experiments show that our approach achieves higher visual quality and better input fidelity than existing methods.

  PublisherDOI

• Holospeed: High-Speed Holographic Displays for Dynamic Content

  2025-07-21

  article1st authorCorresponding

  Holographic displays are plagued by speckle - noise-like artifacts caused by the coherent interference of laser light. To mitigate this challenge, state-of-the-art systems use time multiplexing on fast spatial light modulators (SLMs) to effectively temporally smooth out these effects. In our work, we observe that such an approach struggles in practice in the context of dynamic content, manifesting motion blur and stroboscopic artifacts thanks to a fundamental mismatch between expected and displayed motion. To tackle this challenge, we propose a paradigm of holographic high-speed display, where we use the underlying fast SLM to reproduce target content that changes at the same framerate. Approaches built using this paradigm mitigate motion blur and strobing, and simultaneously minimize speckle and maximize contrast with the right loss functions. We demonstrate such a methodology in both simulation and a real system.

  PublisherDOI

• Holodepth: Programmable Depth-Varying Projection via Computer-Generated Holography

  Lecture notes in computer science · 2024-11-24

  book-chapter1st authorCorresponding
  PublisherDOI

• Dual-Shutter Optical Vibration Sensing

  IEEE Transactions on Pattern Analysis and Machine Intelligence · 2023-12-20 · 2 citations

  article

  Visual vibrometry is a highly useful tool for remote capture of audio, as well as the physical properties of materials, human heart rate, and more. While visually-observable vibrations can be captured directly with a high-speed camera, minute imperceptible object vibrations can be optically amplified by imaging the displacement of a speckle pattern created by shining a laser beam on the vibrating surface. In this paper, we propose a novel method for sensing vibrations at high speeds (up to 63 kHz), for multiple scene sources at once, using sensors rated for only 130 Hz operation. Our method relies on simultaneously capturing the scene with two cameras equipped with rolling and global shutter sensors, respectively. The rolling shutter camera captures distorted speckle images that encode the high-speed object vibrations. The global shutter camera captures undistorted reference images of the speckle pattern, helping to decode the source vibrations. We demonstrate our method by capturing vibration caused by audio sources (e.g., speakers, human voice, and musical instruments) and analyzing the vibration modes of a tuning fork.

  PublisherDOI

• Light-Efficient Holographic Illumination for Continuous-Wave Time-of-Flight Imaging

  2023-12-10 · 2 citations

  articleOpen access1st authorCorresponding

  Time-of-flight (TOF) cameras have seen widespread adoption in recent years across the entire spectrum of commodity devices. However, these devices are fundamentally limited by their dynamic range, struggling with saturation from nearby, brighter objects and noisy depth from farther, darker objects. In this work, we explore overcoming these limitations in the context of continuous-wave time-of-flight (CWTOF) devices, by using a holographic light source capable of redistributing light according to arbitrary patterns. In particular, we propose using such a system to move light from overexposed to underexposed regions of a scene, such that the entire scene is well exposed. Such a methodology can be easily integrated with existing illumination schemes for TOF. Our proof-of-concept prototype is constructed from off-the-shelf optical components, and demonstrated on a number of lab scenes.

  PublisherOA PDFDOI

• SpinCam: High-Speed Imaging via a Rotating Point-Spread Function

  2023-10-01 · 3 citations

  article1st authorCorresponding

  High-speed cameras are an indispensable tool used for the slow-motion analysis of scenes. However, the fixed bandwidth of any imaging system quickly becomes a bottleneck, resulting in a fundamental trade-off between the camera’s spatial and temporal resolutions. In recent years, compressive high-speed imaging systems have been proposed to circumvent these issues by optically encoding the signal and using a reconstruction procedure to recover a video. Our work proposes a novel approach for compressive high-speed imaging based on temporally coding the camera’s point-spread function (PSF). By mechanically spinning a diffraction grating in front of a camera, the sensor integrates an image blurred by a PSF that continuously rotates over time. We also propose a deconvolution-based reconstruction algorithm to reconstruct videos from these measurements. Our method achieves superior light efficiency and handles a wider scene class than prior methods. Also, our mechanical design yields flexible temporal resolution that can be easily increased, potentially allowing capture at 192 kHz—far higher than prior works. We demonstrate a prototype for various applications, including motion capture and particle image velocimetry (PIV).

  PublisherDOI

• Analyzing Physical Impacts Using Transient Surface Wave Imaging

  2023-06-01 · 3 citations

  article

  The subtle vibrations on an object's surface contain information about the object's physical properties and its interaction with the environment. Prior works imaged surface vibration to recover the object's material properties via modal analysis, which discards the transient vibrations propagating immediately after the object is disturbed. Conversely, prior works that captured transient vibrations focused on recovering localized signals (e.g., recording nearby sound sources), neglecting the spatiotemporal relationship between vibrations at different object points. In this paper, we extract information from the transient surface vibrations simultaneously measured at a sparse set of object points using the dual-shutter camera described by Sheinin et al. [37]. We model the geometry of an elastic wave generated at the moment an object's surface is disturbed (e.g., a knock or a footstep) and use the model to localize the disturbance source for various materials (e.g., wood, plastic, tile). We also show that transient object vibrations contain additional cues about the impact force and the impacting object's material properties. We demonstrate our approach in applications like localizing the strikes of a ping-pong ball on a table mid-play and recovering the footsteps' locations by imaging the floor vibrations they create.

  PublisherDOI

• Holocurtains: Programming Light Curtains via Binary Holography

  2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · 2022 · 13 citations

  1st authorCorresponding
  • Computer Science
  • Artificial Intelligence
  • Computer Science

  Light curtain systems are designed for detecting the presence of objects within a user-defined 3D region of space, which has many applications across vision and robotics. However, the shape of light curtains have so far been limited to ruled surfaces, i.e., surfaces composed of straight lines. In this work, we propose Holocurtains: a light-efficient approach to producing light curtains of arbitrary shape. The key idea is to synchronize a rolling-shutter camera with a 2D holographic projector, which steers (rather than block) light to generate bright structured light patterns. Our prototype projector uses a binary digital micromirror device (DMD) to generate the holographic interference patterns at high speeds. Our system produces 3D light curtains that cannot be achieved with traditional light curtain setups and thus enables all-new applications, including the ability to simultaneously capture multiple light curtains in a single frame, detect subtle changes in scene geometry, and transform any 3D surface into an optical touch interface.

  PublisherDOI

• Dual-Shutter Optical Vibration Sensing

  2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · 2022 · 21 citations

  • Computer Science
  • Artificial Intelligence
  • Computer Science

  Visual vibrometry is a highly useful tool for remote capture of audio, as well as the physical properties of materials, human heart rate, and more. While visually-observable vibrations can be captured directly with a high-speed camera, minute imperceptible object vibrations can be optically amplified by imaging the displacement of a speckle pattern, created by shining a laser beam on the vibrating surface. In this paper, we propose a novel method for sensing vibrations at high speeds (up to 63kHz), for multiple scene sources at once, using sensors rated for only 130Hz operation. Our method relies on simultaneously capturing the scene with two cameras equipped with rolling and global shutter sensors, respectively. The rolling shutter camera captures distorted speckle images that encode the high-speed object vibrations. The global shutter camera captures undistorted reference images of the speckle pattern, helping to decode the source vibrations. We demonstrate our method by capturing vibration caused by audio sources (e.g. speakers, human voice, and musical instruments) and analyzing the vibration modes of a tuning fork.

  PublisherDOI

Frequent coauthors

• Matthew O’Toole

  Carnegie Mellon University

  9 shared

• Mark Sheinin

  Carnegie Mellon University

  4 shared

• Srinivasa G. Narasimhan

  Carnegie Mellon University

  4 shared

• James F. O’Brien

  International Computer Science Institute

  2 shared

• Mariko Isogawa

  Keio University

  2 shared

• Kris Kitani

  Carnegie Mellon University

  2 shared

• Ye Yuan

  2 shared

• Rachel Albert

  University of the West Indies

  2 shared

Labs

• Materials Science and EngineeringPI

Education

• B.S., Chemical and Biomolecular Engineering

  Johns Hopkins University

  2013

• Ph.D., Chemical Engineering

  Massachusetts Institute of Technology

  2019

Awards & honors

• University of Minnesota's President's Postdoctoral Fellowshi…
• MIT Tata Center for Technology and Design Fellowship
• ACS Graduate Student and Postdoctoral Scholars Recognition P…
• Top 10 Posters at ACS CERM 2024