Ph.D. in Engineering · University of Regina January 2021 – May 2026 Research in machine learning for signal-based indoor localization.
Research problem: estimate indoor position from high-dimensional WiFi fingerprints while controlling matching cost and sensitivity to signal variation.
Methods: similarity-based candidate selection, signal representation learning, structured attention, and knowledge distillation. The papers and repositories below document the methods and experiments.
Group Matching Method
Reduce the search space for RSS fingerprint matching.
Machine Learning Engineer Intern · Ericsson March 2021 – April 2023
This Montreal-based role overlapped with my doctoral studies at the University of Regina.
Engineering focus: preprocessing, feature engineering, and similarity-based matching for high-dimensional WiFi data, followed by model training and benchmarking.
Python, NumPy, and Pandas workflows for large-scale WiFi datasets.
ML and deep learning models using PyTorch, TensorFlow, and scikit-learn.
Evaluation and visualization tools for model analysis and technical reporting.
Machine Learning Engineer (Contract) · Mercor November 2025 – May 2026
Shown with recent work; the Bay Area chapter indicates my current location, not the location of this contract.
Engineering focus: Python pipelines for LLM-driven task execution and reproducibility, evaluation frameworks for agent systems, benchmarking, and analysis of workflow failures.
Questions behind the work
Does the output follow the instructions?
Can we reproduce the result?
Where does the workflow fail, and how do we measure it?
I’m Huang, a Machine Learning Engineer & Researcher currently based in the Bay Area.
I’m interested in Software Engineer, Data Scientist, Research Scientist, and Machine Learning Engineer roles that connect software and data workflows with modeling, experimentation, or evaluation.
Prepared high-dimensional WiFi datasets with Python, NumPy, and Pandas. Built preprocessing and feature engineering workflows for model training and benchmarking.
University of Regina · PhD research · January 2021 – May 2026
Efficient Algorithms
Group-based matching reduces the candidate search space for RSS fingerprint localization. The research examines localization accuracy alongside computational efficiency.
Fingerprint transformation, similarity filtering, and adaptive reference selection address the structure of high-dimensional signal data. Structured attention is another research direction documented in the project overview.
Ericsson & University of Regina · Overlapping industry and doctoral work
Model Benchmarking
Developed and compared ML and deep learning models, with evaluation and visualization tools for performance analysis. Investigated signal noise and missing data to understand model robustness.
Built an application tracker with page metadata extraction, platform detection, notes, and a tracking dashboard. This project demonstrates browser tooling and workflow organization.