Huang Daoji

Huang Daoji

Quant Research & Data Scientist at BNP Paribas

Huang Daoji’s personal Website

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I am Daoji Huang, a Quant Research & Data Scientist at BNP Paribas (Data AI Lab & Flow Rate QR), working on ML-driven alpha research and market making across linear rates, inflation, and FX — spanning trading signals and agentic-AI infrastructure.

I did a masters at ETH Zurich after a bachelor from Peking U, please refer to my resume(in pdf) or a html version for more details.

I will post my brief notes on some interesting papers from time to time, see Blog Posts. Also you can find some of my lecture notes on Github at Peking U, HKUST, and ETH Zürich.

Professional Experience

  • Quant Research & Data Scientist, BNP Paribas Data AI Lab & Flow Rate QR
    • Aug. 2023 - Present
    • ML-driven alpha research and market making across linear rates, inflation, and FX
    • Yield curve building: multi-layered yield-curve models for market-making and relative-value trading
    • Cross-asset RV: signals across rates/FX/xccy/inflation/commodities
    • FX Basket: neural-network (PyTorch) trading strategy for APAC NDFs, plus MENA FX basket-weight modeling
    • Agentic AI platform: MCP-based multi-agent LLM system coordinating quant, IT, and trading
  • Research Intern, ETH Zürich
    • Sep. 2022 - Dec. 2022
    • Machine Learning - 3D Vision and Reconstruction
    • ROMEO@ECCVW24’: annotation-free 3D human-object interaction reconstruction from images
  • Machine Learning Intern, ByteDance/Tiktok AILab
    • Aug. 2020 - Jul. 2021
    • Machine Learning - Neural Rendering
    • Improved end-to-end Neural Radiance Field (NeRF) model with a unified backbone and optimized training

Education

  • ETH Zürich
    • Sep. 2021 - Jul. 2023
    • MSc in Computer Science
    • Publications: PaLM@CVPRW23’, ECCV24’
  • Yuanpei College, Peking University
    • Sep. 2016 - Jun. 2020
    • BSc in Computer Science and Technology (Outstanding Graduate, National Scholarship)
  • Department of Computer Science, Hong Kong University of Science and Technology
    • Feb. 2019 - Jun. 2019
    • Visit student (Dean’s List)

Academic Projects

  • PaLM: Predicting Actions through LLM, ETH Zürich (01/2023 - 07/2023)
    • Vision-language model + large language model for Long-Term Action Anticipation
    • Winning entry of Ego4D LTA challenge@CVPRW23’, poster@ECCV24’

Skills

  • Programming Languages: Python, C++, SQL
  • ML & Frameworks: PyTorch, LightGBM, Transformers/LLM, TensorFlow, JAX
  • Tools: Git, Linux