Ernie's Leisure Code
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Ernie's Leisure Code

  • Ernie's Leisure Code
  • b01505025@g.ntu.edu.tw
  • ernie55ernie
  • b01505025

Ernie Chang is a quantitative researcher specializing in high-frequency trading, market microstructure modeling, and adversarial machine learning. His work spans alpha signal development, execution modeling, and large-scale data pipeline engineering. Ernie has designed and optimized a wide range of production-grade alphas—leveraging LOB dynamics, spectral and flow-toxicity features, and federated learning frameworks—and has contributed research such as FINISH for decentralized malware detection, published in leading IEEE journals. Ernie combines rigorous academic research with practical systems engineering, building fast, reliable, and scalable analytics for real-world trading environments.