About

Ping Guo is an Associate Professor of Mechanical Engineering at Northwestern University. His research aims to bring innovations to precision engineering by pushing the limits of precision manufacturing and expanding the boundary of intelligent metrology with deep learning-enabled computer vision technologies. His group works to enhance fundamental understandings of new process mechanics and principles, achieve technological advances in machine tool design and control, and explore novel applications in advanced manufacturing. Guo has received numerous recognitions, including the F.W. Taylor Medal from the International Academy for Production Engineering CIRP in 2023, the ASME Kornel F. Ehman Manufacturing Medal in 2021, and the SME Outstanding Young Manufacturing Engineer Award in 2020. His professional service includes serving as an associate editor for the Journal of Manufacturing Processes since 2017.

Research topics

• Computer Science
• Artificial Intelligence
• Materials science
• Optics
• Physics
• Engineering
• Nanotechnology
• Structural engineering
• Mechanical engineering
• Control engineering
• Chromatography
• Chemistry
• Pathology
• Biophysics
• Medicine

Selected publications

• Near-field acoustic gripping for contactless semiconductor die handling

  CIRP Annals · 2026-05-01

  articleSenior authorCorresponding
  PublisherDOI

• Investigation of jet initiation in in-gel near-field electrospinning

  Physics of Fluids · 2026-01-01

  articleSenior author

  In-Gel Near-Field Electrospinning (IG-NFES) integrates near-field electrospinning with embedded three-dimensional printing to achieve high-resolution fiber fabrication within a support gel matrix. We present a multiphysics simulation framework to study jet initiation in IG-NFES. Our framework explicitly incorporates gel drag effects and provides systematic parametric analysis quantifying how material property ratios govern jet stability, enabling predictive material selection and process optimization beyond trial-and-error approaches. We systematically investigated the influence of viscosity, density, and dielectric permittivity ratio on the jet initiation behaviors. Our results reveal that viscosity ratio (M) and dielectric permittivity ratio (Q) are the most critical parameters affecting jet formation and stability. A viscosity ratio of 2.5 promotes stable jet elongation, while significantly lower or higher values lead to premature breakup or jet suppression. As Q increases from 3 to 15, jet behavior transitions from no initiation, to droplet breakup, and finally to stable jet formation due to enhanced electric field focusing on the ink. We also analyzed the roles of two key dimensionless numbers: the electric capillary number (CaE) and the Weber number (We). The transition from droplet formation to continuous jetting is governed by CaE, with stable fiber formation observed within the range of 6–12. Similarly, stable jetting occurs when We lies between 10−5 and 10−3. The model predictions were validated with experiments, confirming the identified regime transitions. These findings offer quantitative insights for optimizing material selection and process parameters in IG-NFES, paving the way for advanced applications in robotics, soft electronics, and biomedical devices.

  PublisherDOI

• Leadless pacemakers: A review of communication methods, energy management, and clinical applications

  Progress in Medical Devices · 2025-09-25

  articleOpen access

  Leadless pacemakers have emerged as a mainstream clinical solution, and their communication capabilities, crucial for reliable pacing and device monitoring, continue to evolve. This review systematically examines the fundamental principles of leadless pacemaker communication systems, current design requirements, existing challenges, and future development trends. We outline the bidirectional communication mechanism between leadless pacemakers and external programmers through wireless technologies, focusing on radio-frequency field communication coupled with load modulation techniques to optimize energy efficiency and transmission reliability. Additionally, we analyze the role of artificial intelligence in adaptive communication protocols and explore the clini cal potential of remote monitoring and control systems. This comprehensive analysis aims to serve as a reference for the development of communication architectures for leadless pacemakers.

  PublisherOA PDFDOI

• Multiscale Analysis of High Impact Toughness in a Novel Low-Cost Titanium Alloy

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• Multiscale analysis of high impact toughness in a novel low-cost titanium alloy

  Journal of Materials Research and Technology · 2025-08-26 · 5 citations

  articleOpen accessCorresponding

  This study systematically investigates the deformation behavior of novel low-cost Ti-6Al-4V-0.4Fe-0.6Mo alloy with varying microstructures under dynamic impact loading. The microstructures with equiaxed and bimodal were fabricated by controlling the temperatures (880°C, 900°C and 920°C) and cooling rates (air cooling, AC and furnace cooling, FC). Charpy impact testing results show that the 920FC sample, featuring large equiaxed α phases (average size: 8.2 μm), α lamellae (thickness: 1.5 μm), and retained β-phases, exhibits the highest impact toughness of ∼62.5 J/cm 2 . Compared with 880FC (∼45.3 J/cm 2 ), 900FC (∼42.1 J/cm 2 ) and Ti-6Al-4V alloys with equiaxed microstructures (∼50 J/cm 2 ), the impact toughness is improved by 38%, 48% and 25%, respectively. Moreover, the impact toughness of the 920AC sample (∼47.6 J/cm 2 ) is 20% higher than that of 880AC (∼39.5 J/cm 2 ) and 900AC samples (∼39.5 J/cm 2 ). Microstructural analyses results show that both 920AC and 920FC samples exhibit low α phase aspect ratios, high α phase spheroidization proportion, and large α grain sizes. The 920FC sample has a percentage of twin boundaries as high as 58.7%, which is the core mechanism for its superior impact toughness over the 920AC sample. Interestingly, we found that twinning nucleation in both α and secondary α phases (α s ) is induced by stacking faults and the abundant stacking faults form martensite 9R phase. The coarsening and growth of twins are affected by dislocation slip. In addition, the calculated results based on the Yu Rui-huang electron theory show that Fe and Mo weaken the inhibitory effect of V on dislocation slip and provide a low-energy path for twin boundary migration.

  PublisherDOI

• Layer-Wise Anomaly Detection in Directed Energy Deposition using High-Fidelity Fringe Projection Profilometry

  ArXiv.org · 2025-08-31

  preprintOpen accessSenior author

  Directed energy deposition (DED), a metal additive manufacturing process, is highly susceptible to process-induced defects such as geometric deviations, lack of fusion, and poor surface finish. This work presents a build-height-synchronized fringe projection system for in-situ, layer-wise surface reconstruction of laser-DED components, achieving a reconstruction accuracy of ${\pm}$46 $μ$m. From the reconstructed 3D morphology, two complementary geometry-based point cloud metrics are introduced: local point density, which highlights poor surface finish, and normal-change rate, which identifies lack-of-fusion features. These methods enable automated, annotation-free identification of common deposition anomalies directly from reconstructed surfaces, without the need for manual labeling. By directly linking geometric deviation to defect formation, the approach enables precise anomaly localization and advances the feasibility of closed-loop process control. This work establishes fringe projection as a practical tool for micrometer-scale monitoring in DED, bridging the gap between process signatures and part geometry for certifiable additive manufacturing.

  PublisherOA PDFDOI

• Graph Neural Networks for patterned welds detection on point clouds

  Journal of Manufacturing Processes · 2025-04-30 · 4 citations

  articleSenior authorCorresponding
  PublisherDOI

• Single-Energy Structure Decomposition Using X-Ray Grating Interferometry

  2025-11-01

  article

  We introduce a novel single-energy structure decomposition (SESD) method using X-ray grating interferometry for quantifying the microstructure of unknown materials. The approach exploits the nonlinear correlation between linear attenuation and diffusion coefficients, specifically demonstrating that the linear diffusion coefficient (LDC) inversely correlates with the diameter of microspheres when their size significantly exceeds the system's autocorrelation length (ACL). We derive an approximation where the LDC of large microspheres is a function of the microsphere diameter and the ACL. By using this relationship, we present a method to express the LDC of unknown microspheres as a linear combination of two reference microspheres. The SESD method integrates dark-field and absorption signals, and provides accurate microsphere size identification. Experimental results validate the effectiveness of SESD, with potential applications in pulmonary disease diagnostics, particularly for imaging pulmonary microstructures.

  PublisherDOI

• DPMNet: Frequency-Aware Dual-Path Modulation for Robust Scene Text Detection*

  2025-09-26

  article1st authorCorresponding

  Scene text detection is crucial for applications like document analysis, autonomous driving, and instant translation. Despite progress in deep learning, existing methods struggle with geometric diversity and multi-scale text due to ineffective feature fusion and context modeling. Traditional approaches often naively combine high-level and low-level features, losing fine details in small text and overemphasizing high-level semantics, reducing detection accuracy. To mitigate these constraints, DPMNet is presented, a novel network with two key modules: The Frequency-Aware Dual-Path Modulation (FADPM) module, which adaptively refines features by enhancing high-frequency details while optimizing low-frequency semantics. The Multibranch Adaptive Fusion (MAF) module leverages multi-scale dilated convolutions and spatial weight allocation to improve context integration. We evaluated the proposed methods TotalText, CTW1500 and ICDAR19 ArT. Extensive experiments have demonstrated the state-of-the-art performance and our method’s exceptional robustness.

  PublisherDOI

• In situ investigation of slip behavior and failure mechanisms in Ti-6Al-4V-0.4Fe-0.6Mo alloy with bimodal microstructure

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

Recent grants

• FMSG: Cyber: Distributed Surface Patterning Through a Cohort of Robots

  NSF · $496k · 2022–2025

Frequent coauthors

• Jianjian Wang

  North China Electric Power University

  33 shared

• Yang Yang

  20 shared

• Kornel F. Ehmann

  Northwestern University

  17 shared

• Yaoke Wang

  Northwestern University

  15 shared

• Pingfa Feng

  13 shared

• Shiming Gao

  Chinese University of Hong Kong

  13 shared

• Wei‐Hsin Liao

  University of Hong Kong

  11 shared

• Yongqing Zhao

  9 shared

Education

• Ph.D., Mechanical Engineering

  Northwestern University

  2014

• Bachelor, Automotive Engineering

  Tsinghua University

  2009

Awards & honors

• F.W. Taylor Medal, International Academy for Production Engi…
• ASME Kornel F. Ehman Manufacturing Medal (2021)
• ASME Best Organizer of Symposium & Sessions Award (BOSS Awar…
• SME Outstanding Young Manufacturing Engineer Award (2020)
• SME Outstanding Associate Editor for Journal of Manufacturin…