Technologies & Tools
Expertise across the full data science and engineering stack
Data Scientist · Data Engineer · ML Engineer
Turning complex data into actionable insights through machine learning, statistical modeling, and scalable data engineering — backed by a research background in computational physics
Expertise across the full data science and engineering stack
Data science, machine learning, and data engineering projects, alongside computational physics research
Computational image-analysis framework to quantify morphological and spatial changes in tumor tissue under MCT1/4 inhibition using IF microscopy data.
Computational framework to implement, compare, and benchmark classical numerical methods for solving ODEs against Wolfram's built-in NDSolve, using canonical nonlinear systems.
Advanced computational biophysics model to study cancer metastasis as a non-equilibrium phase transition, further used as a foundation for a Renormalization Group (RG)-inspired analysis.
End-to-end analytics pipeline consolidating NetSuite ERP data across 7 offices in 4 regions into three automated, row-level-secured Power BI reports — replacing a 4-day manual monthly process with daily refreshes.
Deep learning approach to classify and reconstruct Laguerre-Gaussian light modes distorted by propagation through a dispersive medium — reaching 97.28% accuracy with no image pre-processing.
Desktop fiscal risk tracker for BRP Querétaro's Global Trade and Compliance teams, tracing customs declaration (pedimento) rectifications and import/export data across multiple plants — cutting the customs data bulk-import step from 2 days to 15 minutes.
Unrestricted Hartree-Fock (UHF/STO-2G) electronic structure calculations in GAMESS, mapping the potential, kinetic, and total energy of NO₂ and H₂O as a function of bond length.
Linear stability analysis of the Chen chaotic attractor — deriving its three equilibrium points analytically and locating a Hopf bifurcation (μ between 3.3 and 3.4) via Jacobian eigenvalue sweeps and 3D trajectory simulation.
Kermack–McKendrick SIR model (RK4) forecasting COVID-19 spread in Querétaro, Mexico from public health data — validated against real case reports with a 7-day peak-timing offset and a 30.45% magnitude error.
2-level 2D environmental platformer built in Unity/C# for a game development course, featuring a variable jump-strength mechanic and a rescue-based win condition — playtested as a standalone build with real users.
Professional journey and academic achievements
The CRG and IFAE positions below are two strands of a single Master's thesis project (MMRES, Universitat Pompeu Fabra): IFAE hosted the computational/theoretical modeling, while a 14-week stay at CRG provided the experimental wet-lab data used to calibrate it.
Centre for Genomic Regulation (CRG)
April 2026 - July 2026
Research on the changes in morphologic structure of tumors under novel treatments applying segmentation algorithms in Python.
Institut de Física d'Altes Energies (IFAE)
September 2025 - August 2026
Research on the application of Renormalization-Group frameworks to cancer metastasis based on computational models made with Python.
Alesso Cummins
February 2025 - October 2025
Use of Python, SQL and Microsoft Fabric to implement ETL pipelines and real-time monitoring systems of massive commercial and fiscal data.
Bombardier Recreational Products (BRP)
July 2023 - August 2024
Use of Python and SQL for database maintenance, development of automated reporting systems and data visualization dashboards of massive global trade data.
Universidad Nacional Autónoma de México (UNAM)
October 2022 - June 2024
Use of Matlab to construct convolutional neural networks for pattern recognition and classification for optical quantum communication with LG beams.
Universidad Autónoma de Querétaro (UAQ)
January 2020 - December 2021
Use of software Gamess to perform energy calculations and geometry optimization of the $NO_2$ molecule using Hartree-Fock method.
Universitat Pompeu Fabra (UPF) and Barcelona Institute of Science and Technology (BIST)
September 2025 - August 2026
Focus in the intersection of theoretical physics and biological sciences. Application of computational and statistical models to the study of macroscopic observables for experimental sciences.
Google · Coursera
March 2025
Foundational certificate in applying generative AI tools to workplace tasks, covering prompt engineering, evaluating AI tools, and using AI responsibly. View credential.
Google · Coursera
February 2025
8-course specialization covering security risk management, network security, Linux and SQL, threat/vulnerability detection, incident response with SIEM tools, and automating cybersecurity tasks with Python. View credential.
Santander & BEDU
November 2023 - March 2024
Advanced certification in data science methodologies, machine learning algorithms, statistical analysis techniques and use of tools such as SQL, MongoDB, Python and R. View credential.
Universidad Autónoma de Querétaro (UAQ)
July 2019 - December 2023
Specialized in computational physics for mathematical and physical modeling. Graduate with honors and recognition for best GPA. Group leader and treasurer of the alumni society.
ICFO-UNAM
September 2023
International Schools on the Frontiers of Light. Best Poster Award.
US Particle Accelerator School
June 2022
Fundamentals of particle accelerator physics and technology with simulations and measurements lab.
Centro de Investigación y de Estudios Avanzados (CINVESTAV)
August 2022
Advanced Summer School of 2022 by the physics department of CINVESTAV Zacatenco, in Mexico City.
Various Platforms
Ongoing
Continuous professional development in cloud technologies, advanced analytics, and emerging data science methodologies.