Zehua Wei (Wedward)
Seattle, WA 206-***-**** *******.***@*****.*** https://www.linkedin.com/in/wedward
Data Scientist with 6 years chemical engineering background, 5 years of coding experience, 2 years of machine learning engineering experience in consultancy and fin-tech start-up. Currently focus on Medical Image Processing, Natural Language Processing, and Deep Learning.
Technical Proficiencies
Image Segmentation
Natural Language Processing
Sentimental Analysis
TensorFlow
SpaCy
Word2Vec
OpenCV
Scikit-learn
Python
Keras
cNN
Pandas
Professional Experience
BIOPROBER CORP, Bellevue, WA, 09/2017 – Present
Data Scientist
Applied state of art deep learning technology to Medical AI. BioProber Corp is Seattle R&D center of SonoScape Medical Corp, developing next generation ultrasound system.
Key Accomplishments:
Trained a light-weighed convolutional neural network to extract obstetrical information (like head circumference) using TensorFlow, achieved real-time image processing (400*400 60 Hz video without GPU acceleration).
Model outperformed the U-Net image segmentation neural network (both have a dice score of 0.97), by using 80% less computational resource, and no manual labelled training mask data.
Testing different deploy method like Nvidia TensorRT 3.0 inference engine, TensorFlow Serving, also tested model’s performance on Nvidia Jetson TX2 embedding system.
LUXOFT USA, Kirkland, WA, 03/2017 – 07/2017
Data Scientist
Data Science Consultant in the Big Data team, Global Center of Expertise(CoE) Luxoft (NYSE: LXFT). Our team served clients like SoftBank(Automotive), CenturyLink(Telecom), CIBC(Financial Services), etc.
Key Accomplishments:
Prototyped CenturyLink’s field engineer chatbot project in an agile team in three months, developed a “query knowledge base” chatbot based on MS Bot Framework, Azure QnA maker and pdf splitter.
KEESUN TRADING LLC, Cambridge, MA, 09/2016 – 12/2016
NLP Software Development Engineer Intern
Built a sentimental analysis product in Keesun Trading’s natural language processing (NLP) team with top researchers from CMU and UW on GitLab. Applied Machine Learning technologies to evaluate the news articles’ sentiment score.
Key Accomplishments:
Designed a software package using classifiers built in Scikit-learn, on top of hand-engineered linguistic features, such as sentiment polarity lexicon features extracted by spaCy, an industrial-strength NLP library.
Developed a DL module with Keras, using GloVe (Wikipedia-trained word vectors) as the embedding layer.
Our linguistic model got 88.2% accuracy on IMDB (marked as our benchmark performance), DL models reached the benchmark after 2 epochs of training, and the ensemble DL model achieved 90.6% after 4 epochs.
Reported that cNN architecture in our application was leading to fast convergence and quick overfitting; Bi-direction LSTM architecture cost 10x training time, and it tended to be underfitting the training data.
Education
Master of Science – Chemical Engineering, 2016 University of Washington, Seattle
Concentration: Computational Chemistry
Bachelor of Science – Applied Chemistry, 2013 Beihang University, Beijing, China
PRIOR CAREER Experience
E-SCIENCE INSTITUTE, UW SEATTLE
Data Science Trainee
Engineered 10 features based on known slave trade voyage records, classified 251 slave trips out of 1651 unknown individual trips from 240k ship logs between 1750-1850, quantified 10x slave trips comparing to previous Kaggle study.
CHEMICAL ENGINEERING DEPARTMENT, UW SEATTLE
Research Assistant in Computational Chemistry
Built molecular models with Material Studio, analyzed the models with Gromacs-OpenMPI (MD simulation package) on UW Hyak HPC, developed clustering methods to find steady peptide GrBP5 conformations.
BEIHANG-YUANZI MOUNTAINEERING EXPEDITION
Chief Mountain Photographer
Followed and photographed the climbing team’s 7-day expedition to Mt. Qizi (6206m) in Tibet, after 3-month training.