Yung Daniel Cho
Machine Learning Scientist Iii Data and Ai @Expedia Group
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WORK HISTORY
Machine Learning Scientist Iii Data and Ai @Expedia Group
Toronto, ON, CA
AI Discovery and Recommendation
EDUCATION
University of Toronto
Master's degree, Chemical Engineering with a focus on machine learning
University of Waterloo
Bachelor of Applied Science (B.A.Sc.), Chemical Engineering with Statistics option
Georgia Institute of Technology
Masters of Science, Computer Science, ML Specialization
The G. Raymond Chang School of Continuing Education at Toronto Metropolitan University
Graduate Certificate of Data Analytics, Big Data, and Predictive Analytics, Data Science
SKILLS
ABOUT YUNG DANIEL CHO
Machine Learning engineer with 6 years of experience developing and scaling computer vision, time series analysis, and deep learning to solve real-world problems. Applied expertise in statistics and first principles to model material science and manufacturing processes to optimize product quality, asset life, and reduce waste. Apply distributed computing to scale workflows using HPC and Kubernetes to millions of users or design scenarios. Optimized churn prevention in e-commerce to lift profit. Certified AWS Machine learning Specialist.GitHub profile: https://github.com/yungchidanielchoMethods and toolsLanguages: Python, Matlab, Simulink, SQL, Spark, PyTorchStatistics: experimental design (AB testing), hypothesis testing, ANOVA, time series analysis, spectral analysis, relational calculusDeep learning: TensorFlow, PyTorch, PyTorch lightening, Machine Learning: PCA, PLS, neural network, random forest, xgboost, Unsupervised Machine Learning: KNN, clustering Image: computer vision, classification, segmentation Text: Information retrieval, transformer, LangChain RAG, milvusDatabases: MySQL, MongoDB, Databricks, ArcGISProcess Control: PID tuning, process identification with Matlab, Six sigma, statistical process improvement, MPC, state space Models, LSTMDevOps: Docker, Kubernetes, git, github action, ArgoCD, spinnaker, Jankin, HashiCorp terraform, Vault, Rancher, Omegaconf/Hydra, dynaconf MLOps: MLflow, Feast store, KubeflowVisualization: Altair, Matplotlib, Seaborn, Plotly, StreamlitDistributed and high-performance computing: Ray, SLURM, Altair PBS, Dagster, Spark, FlyteStorage: S3, Hive, IcebergProcess Engineering: reactive flow using computational Fluid dynamics (ANSYS Fluent, Autodesk Moldflow) Process modeling: ASPEN Plus for fuel cell, glass processing and injection molding Reliability Engineering: root cause analysis, risk modelling, hazard analysis
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