Dakota Ling
Milwaukee,USA
Summary
Machine Learning Engineer with practical experience in computer vision and a strong foundation in biomedical engineering. Proven ability to develop and deploy AI solutions that enhance medical imaging diagnostics. Adept at translating complex challenges into actionable insights, demonstrating adaptability, creativity, and a commitment to advancing healthcare technologies.
Overview
5
5
years of professional experience
Work History
Software Engineer – Rotation 3
GE Healthcare - Edison Engineering Development Program
11.2024 - Current
- Refactored C++ modules and CUDA-accelerated tools for real-time CT image reconstruction, including adaptive compute integration across both CUDA and OpenCL backend.
- Refactored legacy image-processing pipelines using OOP and CI/CD practices and implemented signal processing kernels via a stepwise approach to optimize convolution, interpolation, and spatial transformations.
- Built modular unit and regression test suits to validate reconstruction performance and accuracy under hybrid GPU workloads.
MR Recon Software Engineer – DL Fat/Water Swap
Rotation 2
03.2024 - 11.2024
- Built CNN-based deep learning models (VGG-16, ResNet-18) for automated detection of global fat/water classification errors in DICOM MRI volumes.
- Designed a CV preprocessing pipeline for 30+ MRI scans (normalization, augmentation, intermediate DICOM extraction) that reduced runtime by 60%.
- Validated on 50+ clinical volumes with 95% average confidence; transferred scalable pipeline to global engineering teams.
- Deployed model to MR systems for real-time fat/water error detection during scans under FDA regulations.
AI Engineer – Imaging Platform & Solutions
Rotation 1
07.2023 - 03.2024
- Developed a hierarchical CV (PyTorch) NLP pipeline using embeddings and LLMs to classify free-text service suite failure logs into structured categories (e.g., software vs. hardware), enabling downstream analytics.
- Integrated Retrieval-Augmented Generation (RAG) for internal document querying and built a Dockerized chatbot to surface technical specs from Confluence and diagnostic repositories.
- Led performance benchmarking of LLM configurations using statistical evaluation metrics (precision, recall, F1), guiding the selection of optimal embedding-model pairs for production.
EEG Image Reconstruction, Undergraduate Research
University at Buffalo
09.2022 - 05.2023
- Applied foundational computer vision principles in developing a multimodal variational autoencoder for EEG-based visual image reconstruction.
- Processed EEG voltage data using statistical analysis and trained neural network classifiers on cloud infrastructure.
Telemedicine Biomedical Camera
Undergraduate Research Assistant
02.2022 - 04.2022
- Developed a thermal imaging camera system using computer vision to extract heart rate, respiration rate, and temperature in real time with ±2 accuracy.
- Applied signal processing and parallelized filtering pipelines to stabilize biometric measurements, integrating facial detection and thermal ROI tracking.
- Designed a stepwise architecture to process thermal wavefronts and calibrated various lighting and camera conditions for robust, deployable performance.
Education
Master of Engineering - Electrical & Computer Engineering
Marquette University
Milwaukee, WI12.2026
Bachelor of Science - Biomedical Engineering
University At Buffalo
Buffalo05-2023
Skills
- Languages & Frameworks: Python, C, CUDA, MATLAB, SQL, GitLab
- ML/AI Tools: TensorFlow, PyTorch, Scikit-Learn, LangChain, RAG, Embeddings, LLMs, ONNX, Lightning
- MLOps/Workflow: Docker, GitLab CI/CD, Google Test, Linux, Jupyter, GitHub, Agile Scrum
- Cloud & Systems: High-Performance Computing, Parallel Processing, Distributed Systems
LEADERSHIP
GE Healthcare – Edison Inclusion and Diversity Committee Outreach Waukesha, WI July 2023 – August 2023
- Coordinated a 4-week STEM workshop for high school students in the Upward Bound college preparatory program, introducing engineering principles and career pathways.
- Organized an on-site tour of GE Healthcare to provide students with firsthand exposure to engineering roles and workplace culture.
GE Healthcare – AAF Attract: Early Talent Co-Lead 2023 – Present
- Planned and executed networking and educational events to connect incoming interns with GE Healthcare teams and learning opportunities.
- Managed event logistics, budgeting, and funding to ensure impactful, well-organized intern engagement programs.
Timeline
Software Engineer – Rotation 3
GE Healthcare - Edison Engineering Development Program
11.2024 - Current
MR Recon Software Engineer – DL Fat/Water Swap
Rotation 2
03.2024 - 11.2024
AI Engineer – Imaging Platform & Solutions
Rotation 1
07.2023 - 03.2024
EEG Image Reconstruction, Undergraduate Research
University at Buffalo
09.2022 - 05.2023
Telemedicine Biomedical Camera
Undergraduate Research Assistant
02.2022 - 04.2022
Master of Engineering - Electrical & Computer Engineering
Marquette University
Bachelor of Science - Biomedical Engineering
University At Buffalo
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