Isabel Domínguez Jiménez

Physics, Programmer, Developer, and Data Scientist

• Location: México
• Email: isadoji@gmail.com
• LinkedIn: isadoji404
• GitHub: isadoji

Profile

I am a data scientist and educator with 12+ years of experience in higher education and scientific research.

Skilled in advanced programming, data analysis, and machine learning, I bring an analytical approach to solving complex problems.

Technical Skills

• Python (NumPy, Pandas, Matplotlib, Scikit-learn, Seaborn, Keras)
• C++ (ROOT-CERN), Fortran
• SQL, Tableau, Jupyter Notebooks, GitHub
• Google Suite, Slack, Trello, Moodle
• Languages: Spanish (Native), English (B2)

Professional Experience

Full-Time Professor and Researcher - Autonomous University of Sinaloa (2013–2024)

• Taught 50+ courses, including Computational Physics and Optimization.
• Supervised 11 theses (BSc, MSc, PhD) and conducted workshops on data analysis.
• Developed specialized software for scientific simulations.

Visiting Professor - University of Colima (2022–2023)

• Developed machine learning models (Logistic Regression, Decision Trees, Neural Networks) using Python.
• Enhanced data analysis workflows in high-energy particle physics experiments.

Postdoctoral Researcher - Nuclear Sciences Institute, UNAM (2011–2012)

• Optimized Monte Carlo simulations in C++ for high-energy physics research.

Education

• Bootcamp in Data Science - TripleTen (2024)
• PhD in Physics - National Autonomous University of Mexico (2011)
• Master’s in Physics - CINVESTAV, Mérida (2003)
• Bachelor’s in Physics - Autonomous University of the State of Morelos (2001)

Awards

• National Research System - CONAHCyT Level II (2023–2027)
• Desirable Profile for Full-Time Professors (2023–2026)
• Academic Group, Consolidated Level “Decision Support Systems” (2022–2027)

Projects

You can find more details about my projects on my GitHub Projects Page.

Project 1: Vehicle Price

• Description Determine the factors that influence the price of a vehicle and creation and management of a virtual Python environment, development of a web application and its deployment in a Render cloud service that will make it accessible to the public.
• Technologies Used: Python, Scikit-learn, Pandas, Ploty, Streamlit
• Link: Vehicle Price

Project 2: Oil Extraction Analysis

• DescriptionMachine Learning model to predict the amount of oil extracted.
• Technologies Used: Python, Scikit-learn, Pandas, Matplotlib, Scipy,Numpy, GridSearchCV
• Link: Oil Extraction Analysis

Project 3: Movie Reviews

• Description Classify movie reviews with ML models.
• Technologies Used: Python, Scikit-learn, Pandas, TQMD, NLTK, TF-IDF, BERT, Spacy, Torch, Transformers
• Link: Movie Reviewse

Project 4: Age determination

• Description Image age determination with ML modelos.
• Technologies Used: Python, Scikit-learn, Pandas, Tensorflow
• Link: Age determination

Project 5: Photons

• DescriptionNumerical calculations from prompt-photon production by magnetic fields in heavy-ion collisions.
• Technologies Used: Mathematica,ROOT(C++)
• Link: Photons