CV
My academic CV.
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.
Experience
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2023 - Senior Software Systems Engineer
PDF Solutions
1D Registration Location Discovery – Geometry-based Pattern Search (Mar 2026 – Present)
- 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.
- Designed and integrated an end-to-end pipeline from layout parsing to candidate search and result generation, deployed on HPC (SGE clusters) for scalable large-scale layout processing.
Image-based Registration & Template Matching Pipeline (Oct 2025 – Mar 2026)
- Designed an end-to-end image-based pipeline for registration location selection, 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.
- Built scalable and production-ready workflows, deployed across HPC (SGE) and AWS with debugging and validation pipelines for large-scale semiconductor inspection.
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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
Awards
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2018 Hamilton Fellowship
Vanderbilt University
Fellowship awarded to support doctoral studies.
Languages
Chinese : Native speaker
English : Fluent