CV

My academic and professional background.

Portrait of Xiaosi Zhang

Contact Information

Name
Xiaosi Zhang
Professional Title
Senior Software Systems Engineer
Location
San Jose, California

Professional Summary

Senior Software Systems Engineer with a Ph.D. from Vanderbilt University, working at the intersection of semiconductor systems, computer vision, and machine learning. Designs scalable end-to-end solutions for registration, defect detection, and robust matching in structured environments.

Computer Vision Machine Learning System Design Semiconductor Image Processing Data Pipeline

Experience

2023 - Present

Senior Software Systems Engineer

PDF Solutions

Scalable Synthetic Workload Generation FrameworkAug 2026 - Present

  • Designed a configurable synthetic workload generation framework for large-scale semiconductor inspection systems, supporting diverse geometric patterns, spatial distributions, tile configurations, and workload scales without relying on proprietary customer data.
  • Built a multi-format data pipeline integrating layout generation, structured recipe data, spatial metadata, and registration locations, ensuring consistent geometry, coordinate systems, and data relationships across outputs.
  • Implemented parallel workload generation using swath-based partitioning and configurable CPU multiprocessing, enabling efficient processing of large-scale structured datasets.

High-Throughput SEM Inspection & Anomaly Analysis SystemAug 2026 - Sep 2026

  • Architected a high-throughput semiconductor inspection pipeline that analyzes thousands of SEM images within minutes, replacing hours of manual review through automated registration, anomaly detection, and failure characterization.
  • Developed a robust SEM-to-design registration algorithm using normalized cross-correlation, structural edge matching, and subpixel refinement, generalizing across multiple semiconductor products and varying SEM conditions.
  • Built a parallel image analytics pipeline using multi-threaded processing and robust statistics (Median/MAD Z-score) to automatically detect Bright, Gray, Dark, Background, and Low-Correlation mismatch signatures across large datasets.

GAN-based SEM ↔ Layout Translation SystemJan 2026 - Present

  • Built a GAN-based machine learning image-to-image translation system (U-Net + PatchGAN) for SEM ↔ layout simulation domain translation in semiconductor inspection.
  • Designed multi-objective loss functions (adversarial + L1 + cycle consistency) to preserve geometric fidelity while improving visual realism.
  • Deployed the model as a RESTful API (FastAPI) for scalable inference and integration into inspection and analysis workflows.

1D Registration Location Discovery – Geometry-based Pattern SearchSep 2025 – Jan 2026

  • Designed a geometry-aware search system to identify robust registration locations from semiconductor layouts using edge-based spatial analysis.
  • Built efficient candidate generation and filtering mechanisms with spatial indexing and rule-based isolation constraints for structured layout patterns.
  • Developed scoring strategies to evaluate pattern quality and robustness under highly noisy conditions.

Image-based Registration & Template Matching PipelineApr 2025 – Sep 2025

  • Designed an end-to-end image-based pipeline for registration location selection in huge chip design layout(~mm^2), including layout rasterization, candidate sampling, template matching, and quality scoring.
  • Applied computer vision techniques (template matching and correlation analysis) to identify robust patterns under noise, ambiguity, and repetitive structures.
  • Developed data-driven quality metrics (e.g., peak ratio, feature coverage) for pattern ranking and selection.

Automated 1D Registration Ranking & Selection SystemMay 2024 - Oct 2024

  • Designed an automated pipeline for registration candidate ranking and selection in semiconductor inspection workflows.
  • Modeled the problem as a candidate scoring task using edge-based features (Sobel gradient, signal contrast) to evaluate registration quality.
  • Implemented a multi-stage pipeline (generate → score → rank → select) to replace failed or low-quality locations with optimal alternatives.

Data-Driven 2D Registration Tuning SystemJune 2023 - Dec 2023

  • Built a data-driven system for registration tuning and candidate filtering in semiconductor inspection workflows,resulting in 99% system registration pass rate for CPU and GPU chip defect detection
  • Modeled the problem as a scoring and ranking task using 2D spatial features and 1D signal statistics to identify high-quality alignment locations under noise.
  • Designed adaptive thresholding and failure-type classification (e.g., false pass, multi-peak ambiguity) to improve robustness and generalization.

Customer Collaboration & Technical Leadership

  • Acted as a customer-facing engineer, delivering live demos of e-beam inspection systems to customers.
  • Provided on-site and remote technical support, diagnosing complex registration and inspection issues in real production environments.
  • Partnered with product managers and application engineers to translate customer requirements into scalable and testable technical solutions.
2018 - 2023

Graduate Research Assistant

Vanderbilt University

Ph.D. research in optoelectronic characterization, signal processing, and data-driven analysis

  • Performed optoelectronic characterization using scanning photocurrent microscopy (SPCM), generating spatially-resolved signal maps for device behavior and defect patterns.
  • Analyzed photocurrent and electrical signals to characterize carrier transport, device variability, and pattern-level anomalies across spatial regions.
  • Developed signal and image processing pipelines (MATLAB/Python) for noise reduction, feature extraction, and spatial pattern recognition.
  • Explored data-driven approaches for pattern analysis and feature extraction from high-dimensional measurement data.

Education

Publications

1

Graphene-based microfluidic perforated microelectrode arrays for retinal electrophysiological studies

A. Esteban-Linares*, X. Zhang*, H. H. Lee, M. L. Risner, S. M. Weiss, and Y. Q. Xu

Lab on a Chip (2023) · * Equal contribution

2

Probing light-stimulated activities in the retina via transparent graphene electrodes

X. Zhang, H. Lee, Y. Zhang, T. S. Walmsley, D. Li, E. Levine, and Y. Q. Xu

ACS Applied Bio Materials (2022)

3

In situ monitoring of electrical and optoelectronic properties of suspended graphene ribbons during laser-induced morphological changes

X. Zhang, T. S. Walmsley, and Y. Q. Xu

Nanoscale Advances (2020)

4

Vapor plume oscillation mechanisms in transient keyhole during tandem dual beam fiber laser welding

X. Chen*, X. Zhang*, S. Pang, R. Hu, and J. Xiao

Optics and Lasers in Engineering (2018) · * Equal contribution

5

Sub-microsecond vapor plume dynamics under different keyhole penetration regimes in deep penetration laser welding

X. Chen, S. Pang, X. Shao, C. Wang, X. Zhang, P. Jiang, and J. Xiao

Journal of Physics D: Applied Physics (2017)

Highlights

Hamilton Fellowship

Vanderbilt University · Fellowship awarded to support doctoral studies.

Languages

Chinese (Native speaker) · English (Fluent)