Peng Zhao
Optical Systems · Imaging · Edge AI

Peng Zhao

Hardware and AI, from concept to production

I'm an engineer fascinated by how devices perceive and interact with the physical world. Following my Ph.D. in Optics and Photonics from CREOL, my journey has centered on leading sensing engineering initiatives across ASML, Apple, and Meta, taking complex optical architectures from concept all the way to mass production. Lately, I'm focused on pushing the frontier where smart hardware products interface with AI 🚀.

In my free time, I love getting outside for sports (🎾, 🏊‍♂️, 🏄‍♂️, 🥾) and exploring photography 📸. I'm also big on traveling, teaching, and connecting with new people.

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Toolbox

Open code, one repo at a time

Open tools from my own work — optical simulation, imaging pipelines, and AI from training to deployment, each published with the write-up that explains how it works.

  • Four panels of the same ColorChecker scene through camsim: a RAW CFA mosaic, the demosaiced colour image, the colour-corrected image, and the final tone-mapped output.
    camsim — Camera Sensor & ISP SimulationWrite-upFull physical simulation of the camera sensor and ISP — from sensor-plane spectral irradiance → RAW through QE, CFA, IR-cut, shot/read/dark-current/fixed-pattern noise and dual conversion gain (LCG/HCG) → a linear-light ISP → MTF, SNR, ΔE2000 and acutance. Published on PyPI, it is the bridge from photon-level optical simulation to image-quality metrics and downstream machine-vision and ML studies.PythonNumPySciPycolour-scienceSourcePyPI
  • A framework diagram for cnn-classifier: typed YAML flows through data adapters, a model registry, trainer and callbacks, evaluation and diagnostics, to a report, with every stage writing a self-describing run directory; below, CIFAR-10 train/validation accuracy curves and a row-normalized 10-class confusion matrix.
    cnn-classifier — Config-Driven CNN TrainingWrite-upA config-driven PyTorch toolkit that takes any image/label dataset from typed YAML to a trained, evaluated, and reported classifier — dataset adapters with leakage checks, a model registry, a headless trainer with callbacks/AMP/EMA/checkpointing, calibration and bootstrap evaluation, training diagnostics, and self-contained reports. Exercised end-to-end on CIFAR-10 with a residual CNN and ResNet-18 transfer, and published on PyPI as cnn-classifier-toolkit, it is reusable infrastructure for the next classification project.PythonPyTorchtorchvisionPydanticSourcePyPI
  • A detection frame from the pipeline: green boxes labelled “person: 0.84” and “person: 0.82” drawn over two people on a stadium touchline.
    Webcam Smart DetectionWrite-upReal-time webcam detection: YOLO objects and OpenCV faces in the same frame, both publishing an identical result so the render loop never learns which detector drew a box.PythonYOLOv8OpenCVSource
  • A synthetic slanted-edge test chart: nine tilted squares on grey, each with green ROI boxes labelled 0_T through 8_B for the thirty-six edges the pipeline measures.
    Slanted-Edge SFRWrite-upSynthetic slanted-edge charts with a known answer — noise, vignetting, distortion, gamma — measured back by an ISO 12233 pipeline: 36 edges per chart, MTF50 and Nyquist metrics, and a validation module that says where recovery fails.PythonNumPySciPyOpenCVSource
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Publications

Papers and patents

Publications

13 Journals, 8 Refereed Proceedings, and 28 Conference Presentations.

Patents

  • PatentOpticsHardwareSystem DesignFiled

    Optical Sensing of Translational and Rotational Shaft Movements

    US Patent Application No. US63541246 · 2024

  • PatentOpticsHardwareEdge AIFiled

    Single Photon Avalanche Diodes for Rotational and Translational Input Detection

    Application No. US18892374 · 2024

  • PatentOpticsHardwareIssued · Date of Publication: 03/23/2023

    Cylindrical Retroreflector Array for Rotation Tracking

    US Patent Publication No. US20230086536A1 · 2023

All publications

Writing

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Notes on optical design, hardware that has to ship, and where AI genuinely helps.

Let's build something that ships.

I'm interested in optical and sensing systems where the hard part is making the physics survive production.

Get in touch
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