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<!doctype html><html lang="en"><head><meta charset="utf-8"><meta name="viewport" content="width=device-width,initial-scale=1"><title>CV | Yangdeyi Yang</title><meta name="description" content="Engineering CV for Yangdeyi Yang."><link rel="stylesheet" href="style.css"><link rel="icon" href="assets/favicon.svg" type="image/svg+xml"></head><body><a class="skip-link" href="#main">Skip to CV</a><header class="site-header"><div class="container header-inner"><a class="brand" href="index.html"><span class="brand-mark">dy.</span>Yangdeyi Yang</a><nav aria-label="CV navigation"><a href="index.html#work">Projects</a><a href="index.html#about">About</a><a href="cv.html" aria-current="page">CV</a><a href="mailto:124134230@umail.ucc.ie">Email</a><a class="language-switch" href="cv-zh.html" lang="zh-CN">中文</a></nav></div></header><main id="main" class="container cv"><p class="eyebrow">Curriculum vitae</p><h1>Yangdeyi Yang</h1><p class="cv-title">Electrical and Electronic Engineering · Signal Processing · Machine Learning</p><div class="cv-contact"><a href="mailto:124134230@umail.ucc.ie">124134230@umail.ucc.ie</a><span>Cork, Ireland</span><a href="https://github.com/Derekamethy">github.com/Derekamethy</a></div><p class="print-note no-print">Use your browser’s Print command to print this CV or save it as a PDF.</p><section><h2>Profile</h2><p>Electrical and Electronic Engineering MEngSc candidate with project experience in sensor machine learning, biomedical signal processing, multirate DSP and verification-oriented software. I pair clear experimental boundaries with implementation that others can inspect.</p></section><section><h2>Research experience</h2><h3>Machine Learning Research Intern · Tyndall National Institute</h3><p>2026, starting in May · CRFID sensing under reader-geometry shift.</p><ul><li>Built preprocessing, grouped partitions and source-only evaluation for chipless RFID measurements.</li><li>Compared models and diagnostics under an unseen reader distance-and-angle combination.</li><li>Reported near-chance transfer performance clearly, distinguishing measured evidence from untested explanations.</li></ul><p><a href="CRFID-research-website/">CRFID code and research evidence</a></p></section><section><h2>Selected engineering projects</h2><h3>Patient-specific EEG seizure detection · UCC EE6019</h3><ul><li>Implemented CHB-MIT ingestion, filtering, spectral and synchrony features, fold-local feature selection, Random Forest classification and event scoring.</li><li>Reported 53/55 detected seizure events and 0.3066 pooled false alarms/hour across a 10-subject retrospective study.</li></ul><p><a href="EEG-seizure-detection-website/">Detection pipeline and result tables</a></p><h3>EEG multirate DSP · UCC EE6041</h3><ul><li>Designed 500 Hz → 32 Hz conversion with an 8/125 ratio and a 4,145-tap Kaiser FIR.</li><li>Validated direct/polyphase equivalence and preservation of the 0.5–12.5 Hz analysis band.</li></ul><p><a href="eeg-multirate-dsp/">DSP implementation and benchmark</a></p><h3>Eight-channel EEG simulator and verification proof of concept</h3><ul><li>Built Python desktop and browser consoles with waveform playback, channel controls, fault injection and virtual 16-bit DAC mapping.</li><li>Defined the proposed physical path and retained the boundary between software verification and unmeasured hardware output.</li></ul></section><section><h2>Education</h2><h3>MEngSc, Electrical and Electronic Engineering · University College Cork</h3><p>2025–2026</p><h3>BE, Electrical and Electronic Engineering · University College Cork</h3><p>2020–2024</p></section><section><h2>Technical skills</h2><p>Python, NumPy, SciPy, pandas, scikit-learn, PyTorch; EEG filtering and feature extraction, multirate FIR processing, grouped experimental design, domain generalisation, error analysis; Git, automated tests and CI.</p></section></main><footer class="site-footer"><div class="container">© Yangdeyi Yang</div></footer>
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