About

ECE Associate Professor Charles DiMarzio was selected by the International Society for Optics and Photonics (SPIE) as a 2021 Senior Member. SPIE Senior Members are Members of distinction honored for their professional experience, their active involvement with the optics community and SPIE, and/or significant performance that sets them apart from their peers.

Research topics

• Chemistry
• Biology
• Biophysics
• Biochemistry
• Computer Science
• Biomedical engineering
• Physics
• Medicine
• Composite material
• Optics
• Nanotechnology
• Materials science
• Pathology

Selected publications

• Cellular fluorescence microscopy aberration correction with focus-diverse machine learning

  2026-03-04

  articleSenior author

  A microscope objective is a significant cost of an optical system, but a low-cost objective may introduce optical aberrations into the final image, making specimen interpretation difficult. Our research investigates using focus-diverse image stacks and machine learning to correct aberrations computationally and restore perceptual similarity to the aberrated image. Our previous research showed promising results for entirely synthetic cell datasets, but lacked a way to viably extend the method to experimental data because of the training data required. This research focuses specifically on a method to artificially aberrate experimental data and generate a semi-synthetic dataset to support focus-diverse machine learning efforts. Performance is evaluated with quantitative and qualitative metrics including peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) index. Qualitative and quantitative results show that artificial aberration is a viable method for generating semi-synthetic datasets, and that focus-diverse machine learning trained on semisynthetic datasets can be used for aberration correction. This is an important step to able generate the quantity of focus-diverse aberrated training data required by machine learning models.

  PublisherDOI

• On-glass interference confocal reflectance microscopy for collagen fibril diameter measurement

  2026-03-04

  articleSenior author

  Previously, our group demonstrated using interference confocal reflectance microscopy (I-CRM) to measure collagen fibril diameters when suspended. An equally popular but optically unique challenge is presented when imaging collagen on glass, which is used for studying early stage fibril development. In this short manuscript, we present interference confocal reflectance microscopy as an alternative to atomic force microscopy for quantifying collagen fibrils below 50nm.

  PublisherDOI

• SCANS: A Soft Gripper With Curvature and Spectroscopy Sensors for In-Hand Material Differentiation

  IEEE Robotics and Automation Letters · 2025-10-13 · 1 citations

  article

  We introduce the soft curvature and spectroscopy (SCANS) system: a versatile, electronics-free, fluidically actuated soft manipulator capable of assessing the spectral properties of objects either in hand or through pre-touch caging. This platform offers a wider spectral sensing capability than previous soft robotic counterparts. We perform a material analysis to explore optimal soft substrates for spectral sensing, and evaluate both pre-touch and in-hand performance. Experiments demonstrate explainable, statistical separation across diverse object classes and sizes (metal, wood, plastic, organic, paper, foam), with large spectral angle differences between items. Through linear discriminant analysis, we show that sensitivity in the near-infrared wavelengths is critical to distinguishing visually similar objects. These capabilities advance the potential of optics as a multi-functional sensory modality for soft robots. The complete parts list, assembly guidelines, and processing code for the SCANS gripper are accessible at: <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://parses-lab.github.io/scans/</uri>.

  PublisherDOI

• Combining machine learning and Fourier optics for fluorescence microscopy aberration correction

  2025-03-19

  articleSenior author

  There is commercial interest in producing high quality microscopy images for low cost. Our research combines Fourier optics and machine learning to attempt to correct aberrations in low-quality fluorescence microscopy images. We use Fourier optics to generate a synthetic dataset and validate the approach and then discuss how the technique might be applied to real world fluorescence images.

  PublisherDOI

• SCANS: A Soft Gripper with Curvature and Spectroscopy Sensors for In-Hand Material Differentiation

  ArXiv.org · 2025-10-02

  preprintOpen access

  We introduce the soft curvature and spectroscopy (SCANS) system: a versatile, electronics-free, fluidically actuated soft manipulator capable of assessing the spectral properties of objects either in hand or through pre-touch caging. This platform offers a wider spectral sensing capability than previous soft robotic counterparts. We perform a material analysis to explore optimal soft substrates for spectral sensing, and evaluate both pre-touch and in-hand performance. Experiments demonstrate explainable, statistical separation across diverse object classes and sizes (metal, wood, plastic, organic, paper, foam), with large spectral angle differences between items. Through linear discriminant analysis, we show that sensitivity in the near-infrared wavelengths is critical to distinguishing visually similar objects. These capabilities advance the potential of optics as a multi-functional sensory modality for soft robots. The complete parts list, assembly guidelines, and processing code for the SCANS gripper are accessible at: https://parses-lab.github.io/scans/.

  PublisherOA PDFDOI

• Interference confocal reflectance microscopy for collagen fibril diameter measurement

  2025-03-19

  articleOpen accessSenior author

  Collagen fibrils provide an interesting challenge for traditional optical microscopy due to being large enough to visualize (>20nm) but usually below the Abbe diffraction limit point spread function. Confocal reflectance microscopy has been used previously to visualize collagen fibrils without fluorescent tags or other lethal methods (e.g, electron microscopy), but still cannot break the fundamental diffraction limit. We explore a sub-category of confocal reflectance known most commonly as interference reflectance microscopy, and more specifically confocal interference reflectance microscopy. The previous literature and the working principle for both mono and multi-wavelength systems are examined, finite difference time domain (FDTD) simulation results are presented, and initial imaging results of Type I collagen fibrils are shown. We believe this method has untapped potential for imaging collagen fibrils and could provide another non-lethal, no stain live imaging method to qualitatively measure collagen fibril diameters.

  PublisherOA PDFDOI

• PROSPECT: Precision Robot Spectroscopy Exploration and Characterization Tool

  arXiv (Cornell University) · 2024-03-25

  preprintOpen access

  Near Infrared (NIR) spectroscopy is widely used in industrial quality control and automation to test the purity and grade of items. In this research, we propose a novel sensorized end effector and acquisition strategy to capture spectral signatures from objects and register them with a 3D point cloud. Our methodology first takes a 3D scan of an object generated by a time-of-flight depth camera and decomposes the object into a series of planned viewpoints covering the surface. We generate motion plans for a robot manipulator and end-effector to visit these viewpoints while maintaining a fixed distance and surface normal. This process is enabled by the spherical motion of the end-effector and ensures maximal spectral signal quality. By continuously acquiring surface reflectance values as the end-effector scans the target object, the autonomous system develops a four-dimensional model of the target object: position in an $R^3$ coordinate frame, and a reflectance vector denoting the associated spectral signature. We demonstrate this system in building spectral-spatial object profiles of increasingly complex geometries. We show the proposed system and spectral acquisition planning produce more consistent spectral signals than naive point scanning strategies. Our work represents a significant step towards high-resolution spectral-spatial sensor fusion for automated quality assessment.

  PublisherOA PDFDOI

• Diffraction

  2024-01-18

  book-chapter1st authorCorresponding
  PublisherDOI

• Interference

  2024-01-18

  book-chapter1st authorCorresponding
  PublisherDOI

• Stops, Pupils, and Windows

  2024-01-18

  book-chapter1st authorCorresponding
  PublisherDOI

Recent grants

• UNS:Collaborative Research: Coded-illumination Fourier Ptychography for High-content Multimodal Imaging

  NSF · $300k · 2015–2020

Frequent coauthors

• Milind Rajadhyaksha

  28 shared

• Dana H. Brooks

  Northeastern University

  25 shared

• Joseph L. Hollmann

  Draper Laboratory

  21 shared

• William C. Warger

  Massachusetts General Hospital

  20 shared

• Heidy Sierra

  University of Puerto Rico-Mayaguez

  16 shared

• Ronald A. Roy

  University of Oxford

  15 shared

• Carey M. Rappaport

  Northeastern University

  14 shared

• Carol M. Warner

  Northeastern University

  14 shared

Labs

• Optical Science LaboratoryPI

Education

• PhD, ECE

  Northeastern University

  1996

• MS, Physics

  Worcester Polytechnic Institute

  1973

• BS, Engineering Physics

  University of Maine

  1969

Awards & honors

• 2022 SPIE Fellow
• 2021 Senior Member of SPIE the International Society of Opti…
• 2021 Senior Member of Optica (formerly OSA)
• 2021 Patent for Methods, systems, and devices for optical se…
• 2016 Patent for Deep tissue focal fluorescence imaging with…