About

I am a graduate researcher in computer science with a background in chemical engineering. My research has grown from a broad interest in computational problem solving into a more focused inquiry on how algorithms and mathematical models interact with the structure of optimization problems, spanning operations research and quantum computing, including integer and semidefinite programming, as well as large-scale problems in energy and process systems engineering.

This work has gradually drawn me toward a deeper question: what is the mathematical structure underlying these problems, and how can it be exploited? Exploring that question has shaped my current research interests:

  • Algebraic and graph-theoretic approaches to combinatorial optimization, including symmetry and group theory,
  • Reformulation and decomposition methods for mathematical programming models,
  • Quantum hybrid quantum-classical optimization algorithms.

Featured Research

View complete list here

A Hybrid Quantum-Classical Machine Learning Framework for Black Carbon Forecasting

Journal Article

I. Oliva-González, L. T. González, O. D. Lara-Montaño, A. I. Ramirez, A. Mendoza, I. M. Hernández-Romero

EPJ Quantum Technology (accepted)

Integrating Quantum Computing into Sustainable Carbon-Capture Materials Research: Opportunities and Perspectives

Book Chapter

I. M. Hernández-Romero, I. Oliva-González, O. D. Lara-Montaño, K. Hernández-Romero, G. G. Ezquivel-Patiño, O. Kharissova, A. I. Ramirez, L. T. González

Handbook of Carbon Negative Footprint Materials, Springer Nature (accepted)

Projects

View complete list on GitHub

Exploratory Study of Symmetry in Combinatorial Optimization

Explores symmetry reduction techniques including lexicographic constraints, variable fixing, and automorphism-based methods applied to classical ILP problems such as shortest path, graph coloring, max-cut, and traveling salesman, reducing redundant solutions and simplifying the solution space.

Symmetry-Aware CC Unit Commitment

Study of symmetry reduction applied to the Combined Cycle Min-Up/Min-Down Unit Commitment Problem (CC-MUCP), deriving demand-aware lexicographic constraints to eliminate the wreath product symmetry induced by identical packages and gas turbines.

Experience

Visiting Research Scholar

Tecnológico de Monterrey | Supervisor: Dr. Ilse María Hernández-Romero

Jan 2025 - Aug 2025
Monterrey, MEX
  • • Conducted collaborative research on hybrid quantum–classical neural architectures using variational quantum circuits to model black carbon dynamics
  • • Benchmarked performance against classical machine learning methods (PennyLane)
Aug 2023 - Aug 2025
Querétaro, MEX
  • • Developed and evaluated quantum and classical algorithms for discrete shortest-path problems using Julia
  • • Designed and implemented finite automata for encoding alphabetic sequences (Mathematica)

Process Technician

Ingredion México

Feb 2022 - Dec 2022
San Juan del Río, MEX
  • • Operated and monitored industrial starch processing systems
  • • Performed on-site troubleshooting and real-time adjustments to ensure process reliability

Undergraduate Intern

NOVARES México

Jan 2021 - Jun 2021
Silao, MEX
  • • Supported the implementation of health, safety, and environmental (HSE) programs in automotive manufacturing

Visiting Research Scholar

Instituto Tecnológico de Villahermosa | Supervisor: Dr. Francisco López-Villarreal

Summer 2019
Villahermosa, MEX
  • • Developed computational interface for vapor–liquid equilibrium calculations in isothermal flash distillation
  • • Applied numerical methods to thermodynamic optimization problems (MATLAB)

Education

MSc in Computer Science

Universidad Autónoma de Querétaro

Aug 2023 - Aug 2025
Querétaro, MEX

Dissertation on quantum annealing and simulated annealing for discrete-space route optimization.

BSc in Chemical Engineering

Universidad de Guanajuato

Jan 2017 - Dec 2021
Guanajuato, MEX

Dissertation on modeling and design of intensified distillation sequences for renewable fuel separation.

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