Brandon Wang Email & Phone Number

Los Angeles, Ca, Us

Seattle, Washington, Us

Seattle, Washington, Us

Supply chain data science- ETL pipeline and data engineering for large-scale data- Productionized two machine learning model APIs for customer promise and transit time prediction (low latency and high traffic)- Developed MLOps pipeline including drift monitoring, model retrain, model deployments, automation, testing, and CICD- Designed and conducted various experimentations for product launch, metrics tracking, and causal inferenceTech stack- Teradata SQL- Python- Pyspark- Presto SQL- REST API- AWS- Docker- Kubernetes- Airflow- NewRelic (+NRQL)- Splunk

Seattle, Washington, Us

Bentonville, Arkansas, Us

Omni-channel supply chain data science and analytics- Wrote a discrete event simulation tool for a multi-echelon inventory network - Developed net promoter score prediction model and causal analysis framework- Developed anomaly detection model for inventory data pipeline- Data analytics and modeling in e-commerce supply chain network including inventory flow, inbound, outbound, and operation/transportation.Tech stack- Teradata SQL- Python (Numpy, Pandas, Simpy, Scikit-learn)- Pyspark- Azure Databricks- Tableau

Bentonville, Arkansas, Us

Champaign, Il, Us

Data Analytics/Predictive Modeling­- Data mining of raw data from several public and private sources ­- Developed ETL pipeline including data validation, data imputation, string pre-processing, and feature extractions­- Implemented risk modeling framework to predict accident occurrence and hotspots using GIS and mixed logit model­- Identified and classified accident causes using DBSCAN, EM clustering, logistic regression, random forest, naïve Bayes, SVM, and CNN­- Designed framework to model accident consequences using elastic net, random forest, xgboost, and SVR- Led a team of researchers in statistics analytics research, including data engineering and statistical modeling, and communicated results to industry sponsors- Machine Learning Platform: SciPy/NumPy/Scikit-learn/Pandas, Tensorflow, Keras- Machine Learning Algorithms: Regression, Clustering, Random Forests, SVM, Recommender, Sentiment Analysis, RBM, Autoencoder, CNN, RNN, and LSTM

Champaign, Il, Us

Railroad Transportation Engineering

New York, Us

Big data analysis / Predictive modeling- Developed ETL code for large scale distributed system server performance big data (trillions of rows), including unstructured and semi-structured data; including tokenization, stemming, lemmatization, parsing, and feature engineering. - Conducted anomaly detection using kernel density estimation, K-Means, SVM- Conducted time series analysis and machine learning algorithms to predict server performance and provided solution for alleviating server performance issues- Built a multifunctional front-end platform using xml to access model predictions and recommendations

Berkeley, Ca, Us

Artificial Intelligence for Autonomous Vehicle- Designed and implemented simulation experiments for autonomous vehicle technology and ramp metering - Combined traffic flow theory and AI technology with simulation toolkit and Python API- Predicted traffic condition using simulation data and optimized metering with mathematical model

Reclaimed Asphalt Pavement - Advisor: Gerardo FlintschProject - Lab testing various percentages of RAP.

Blacksburg, Va, Us

CEE 3604 - Introduction to Transportation Engineering.

Blacksburg, Va, Us

Transit Planning - Advisor: Antonio TraniProject - Study of the Dulles Corridor Metro-rail in Washington, D.C. The project analyzed ridership and optimum pricing for the metro-rail system and compared those factors to current highway system.

Blacksburg, Va, Us

Traffic Engineering - Advisor: Hesham Rakha and Jianhe DuProject - Study of closely spaced adaptive signal controls in Blacksburg, VA.

Blacksburg, Va, Us

Traffic Engineering - Advisor: Hesham RakhaThe efficiency, energy, and environmental impacts of roundabouts in Blacksburg, VA. Roundabouts were modeled and compared to different traffic control methods and sensitivity analysis.

Doctor Of Philosophy (Ph.D.), Transportation Engineering, Statistics Minor

Master Of Science (M.S.), Transportation Engineering

Bachelor Of Science (B.S.), Magna Cum Laude, Civil And Environmental Engineering