Suyue Chen
Assistant Actuary Level 4 at Transamerica
Coralville, Iowa, United States
Summary
🤩
Rockstar🎓
Top SchoolSuyue Chen is an actuary with six years of hands-on experience in life valuation, variable annuity hedging, and production ALM workflows at Transamerica, combining deep quantitative skills from dual degrees in Mathematics and Statistics and an M.S. in Actuarial Science. She has cleared multiple actuarial exams (including P, FM, MFE, C, MLC), completed all VEE and FAP requirements, and passed CFA Level I, demonstrating a strong commitment to technical credentialing. Her work spans stochastic and deterministic reserve modeling, hedge analytics (Delta/Rho/Gamma and macro strategies), and automation using Alteryx, SQL, Python, and VBA to modernize attribution and reporting processes. A contributor to the intel/neural-compressor project, she has applied backend refactoring and adaptor improvements for MXNet, reflecting an uncommon blend of actuarial domain knowledge and practical coding experience in model compression tooling. Known for learning quickly and communicating complex quantitative findings clearly, she is open to relocation to increase on-site collaboration and impact.
6 years of coding experience
Bachelor of Science (B.S.) Mathematics, Bachelor of Science (B.S.) Mathematics at University of MinnesotaMaster of Science (M.S.) Actuarial Science, Master of Science (M.S.) Actuarial Science at University of Iowa
English, Chinese, shanghai dialect, Korean, Japanese
Github Skills (6)
quantization10
mxnet10
adaptor10
python10
adapter10
deep-learning9
Programming languages (9)
Github contributions (5)
intel/neural-compressor
Jul 2020 - Jan 2023
SOTA low-bit LLM quantization (INT8/FP8/INT4/FP4/NF4) & sparsity; leading model compression techniques on TensorFlow, PyTorch, and ONNX Runtime
Role in this project:
Back-end Developer
Back-end DeveloperContributions:11 releases, 680 reviews, 524 commits in 2 years 6 months
Contributions summary:Suyue primarily focused on improving and adapting the MXNet adaptor layer within the neural-compressor repository. Their contributions involved refactoring code, including code style adjustments, and making changes to the MXNet adaptor to improve compatibility and functionality. The user's work touched on model quantization, calibration, and evaluation, specifically within the MXNet framework. Furthermore, the user performed general code formatting using autopep8.
knowledge-distillationauto-tuningcompressorsparsityintel
opea-project/GenAIExamples
Mar 2024 - Apr 2025
Generative AI Examples is a collection of GenAI examples such as ChatQnA, Copilot, which illustrate the pipeline capabilities of the Open Platform for Enterprise AI (OPEA) project.
Contributions:2 releases, 570 reviews, 580 PRs in 1 year
chatqnacodegencopilotgaudi2genai
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