ON.Energy — Financial Intern
Quantitative analysis of energy markets. Multicriteria decision models for investment planning. Financial modeling.
Member Profile
Engineering Physicist · Data Analyst
I focus on data-driven modeling, Koopman operator theory, and real-world applications in energy and climate systems. I aim to bridge theory and practice through smart, scalable tools.
A quick snapshot of tools and methods I use most.
Reverse-chronological highlights.
Quantitative analysis of energy markets. Multicriteria decision models for investment planning. Financial modeling.
Physics-informed neural networks based on variational principles to improve dataless training efficiency and accuracy.
Data extraction and analysis for model training/validation. Forecasting and downscaling using ML methods.
Application of mHAVOK as a spectral tool for the analysis of Lindbladian quantum systems.
Measure theory and Markov processes to describe probability distributions for battery power and energy.
Developed an algorithm based on generalized embeddings for linearization of chaotic dynamical systems.
Led a seminar series on Koopman analysis.
Built Python automations to increase efficiency and improve reporting.
Analyzed Mexican energy market and transmission network, including LMP visualization.
Designed and implemented the industry partner website using front-end tools.
Designed a wavelet-based algorithm for damage detection in composite beams.
Designed Parquet + SQL workflows for faster storage and querying.
Event planning, sponsorships, and balance reports.
Applied Wolfram Mathematica to analytical descriptions of optical systems.
Participated in talks, events, and seminaries.
Selected university / industry-collab coursework projects.
Built a custom vacuum chamber for electrical characterization; participated in synthesis and SEM/TEM/AFM/Raman.
Analytical specific-heat model using phononic interactions; simulated vibrational dynamics with Ising models.
Genetic algorithms for cost optimization under terrain constraints identified via unsupervised learning.
Study of Mexico’s energy market after significant political reforms.
Studied integration of renewable energy sources into the Mexican energy market.
Optimized a charge/discharge scheme based on Mexican energy and power tariff structures.