Data Scientist Resume

SUMMARY:

Data Scientist/AI Engineer with strong background in mathematics, machine learning, artificial intelligence, control, and engineering technologies. Developed deep learning algorithms for manufacturing applications. Published computer vision and AI conference papers. Interested in data problems in all domains.

PROFESSIONAL EXPERIENCE:

Data Scientist

Confidential

Developed a decentralized model development platform and open source package for deep learning applications.
Developed deep learning visual inspection models (accuracy>99%) for industrial products defect detection in manufacturing lines.
Wrote two papers on industrial computer vision, time series forecast, and federated model learning.
Building LSTM models for air pollution level prediction and stock price forecasts.

Research Assistant

Confidential

Data quality analytics and anomaly/edge detection of sensor signals in thermal science and energy research.
Developed laboratory software with pipeline integrating data processing, modelling, and analytics of gas physics.
Parameter study and statistical analysis of complex physical network models.
Initiated big data analytics proposal to study engine combustion chemistry and fluid dynamics.
Researched and resolved data discrepancies with 5 other top research groups from Stanford University and USC.
Refined computational fluid dynamics algorithms for complex flows.

TECHNICAL SKILLS:

Software/programming languages: Python (SciPy, NumPy, pandas, scikit - learn, TensorFlow, Pytorch, NLTK, matplotlib, Bokeh, Plotly, Keras, etc.), MATLAB, R, SQL (MySQL, PostgreSQL), C++, Fortran, Labview, Microsoft Azure, Apache Spark, IBM Watson, Linux, GPU computing.

Mathematics and machine learning skills Hypothesis testing, Monte Carlo, regularized linear regression, logistic regression, tree-based models, Naïve Bayes, PCA, deep learning (CNN, RNN), SVM, NLP, clustering, smoothing, graph theory, data visualization, finite element method, control theory, PDE solvers, etc:

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