Jessica Kreinsen
Data Analyst | Data Scientist | Data Engineer
I apply data science and machine learning to industrial applications.
Projects
Physics-Informed Neural Networks (PINNs)
A physics-informed neural network (PINN) that embeds Paris-law crack-growth physics and a computational pipeline that links process parameters to fatigue-life distributions.
This project uses: Python, PyTorch, scikit-learn, pandas, NumPy, Matplotlib, SciPy, Torch, physics-informed neural networks (PINNs), Paris-law fracture mechanics, Monte Carlo simulation, extreme-value statistics (GEV), Weibull reliability analysis, feature engineering, Git/GitHub
Predictive Modeling of California’s Energy Systems
A predictive analysis of the last 20 years of California’s energy reports.
This project uses: Python, Google Colab, data cleaning, data visualization, regression modeling, prediction models, evaluation metrics, Tableau
Photovoltaics: The Science, History, and Future
A research report on the science, materials, history, politics, and economics of photovoltaics and solar energy.
This project uses: research, reporting, physics, circuit diagrams, and presentations
NLP & LSTM Language Model
Part One is a word and sentiment analysis of Taylor Swift’s discography. Part Two is an LSTM language model that predicts the next words in a Swift-esque song.
This project uses: Python, GitHub, Visual Studio Code, Genius API, pandas, NLTK, matplotlib, plotly, sentiment analysis, data collection, data cleaning, data visualization, machine learning, LSTM, RNN, neural network, prediction model, Tableau, dashboards
Student Rental: Use Case Study Report
The conceptual models for an original business idea are implemented in a DBMS and validated in MySQL, NoSQL, and Python.
This project uses: MySQL, MongoDB, Python, EER, UML, relational modeling, DBMS, UI models
Startup Data Dashboard
An interactive dashboard exploring data on unicorn companies.
This project uses: Tableau, dashboards, data cleaning, data visualization