About me
I am currently an Assistant Professor in the Department of Electrical,
Computer & Energy Engineering at the University of Colorado Boulder. Before this
appointment, I was postdoctoral researcher at the Davidson School of Chemical
Engineering at Purdue University under the advice of Prof. Can Li .
I used to be a Buckeye! I earned my Ph.D. in Electrical and Computer Engineering
from The Ohio State University in 2022, where I was advised by
Prof. Antonio Conejo.
My research focuses on the development of theory, algorithms, and models
for large-scale decision-making under uncertainty, at the intersection of
optimization and machine learning. While power and energy systems are a central
application area of my work, I am broadly interested in applying decision intelligence
theory and methods to complex engineered systems, including infrastructure networks
and operations problems. I am always happy to chat, so please feel free to reach out via email.
Education
PhD Electrical Engineering
The Ohio State University
MSc Electrical Engineering
The Ohio State University
BSc Electrical Engineering
Escuela Politécnica Nacional
Research interests
Optimization
Machine Learning
Power Systems
Experience
Postdoctoral Scholar
Purdue University
Responsibilities include:
- Devise scientific machine learning frameworks for end-to-end learning of optimization problems satisfying hard constraints and providing strong provable bounds.
- Develop algorithms for large-scale problems arising at the integration of planning and operation decisions of highly electrified chemical industries.
- Design frameworks based on large language models to (i) analyze solutions and repair infeasible optimization problems and (ii) detect, identify, and diagnose faults in industrial processes.
Graduate Research Assistant
The Ohio State University
Responsibilities include:
- Develop a unit commitment model with AC network constraints based on a second-order conic relaxation of the power flow equations and an algorithm to achieve an AC feasible solution.
- Design an algorithm based on Benders decomposition to address the AC network-constrained unit commitment problem of large-scale power systems.
- Propose a risk-aware network-constrained unit commitment model and an algorithm based on decomposition techniques to address the solution of large-scale power grids.
- Formulate a unit commitment model considering the optimal behavior of the natural-gas market and a solution method for large-scale systems based on an outer approximation algorithm.
- Devise a solution method for the corrective security-constrained unit commitment problem for large-scale power systems using a hybrid decomposition and a Kron-based network reduction technique.
Research Aide
Argonne National Laboratory
Responsibilities include:
- Develop a tool to visualize and analyze the behavior of distribution networks based on a component-based aggregate load model.
- Investigate the physical feasibility of engaging plug-in electric vehicles to support a power grid with increasing renewable energy.
Lecturer
Escuela Politécnica Nacional
Education
PhD Electrical Engineering
The Ohio State University
GPA: 3.96/4.0
Thesis on optimization models and techniques for the unit commitment problem of modern energy systems. Supervised by Prof Antonio J. Conejo. Presented papers at 4 conferences with 13 manuscripts being published in power systems and operations research journals including IEEE Transactions on Power Systems, Proceedings of the IEEE, European Journal of Operational Research, International Journal of Electrical Power & Energy Systems.
MSc Electrical Engineering
The Ohio State University
GPA: 3.95/4.0
Courses included:
- Optimization: Nonlinear and dynamic optimization, Complementarity models, Decomposition techniques, Stochastic optimization
- Power Systems: Analysis and operation, Electricity markets, Advanced topics in power systems, Advanced topics in sustainable energy
- Machine learning and Control theory: Linear systems theory, Nonlinear systems theory, Robust control, Stochastic Dynamical Systems, Reinforcement learning, Machine Learning
BSc Electrical Engineering
Escuela Politécnica Nacional
GPA: 3.1/4.0
Courses included:
- Power systems: Analysis, Stability, Operations, Reliability
Skills & Hobbies
Technical Skills
Programming: Python, Julia, Matlab
Optimization: JuMP, Pyomo, GAMS
Power systems: DIgSILENT PowerFactory
Awards
IEEE PES Outstanding Dissertation Award, Finalist
IEEE Power and Energy Society ∙
July 2024
This award recognizes the best emerging academic work that falls under the scope and enhances the mission of the IEEE Power and Energy Society.
Presidential Fellowship
The Ohio State University ∙
January 2022
The Presidential Fellowship is the most prestigious award given by the Graduate School to recognize the outstanding scholarly accomplishments and potential of graduate students entering the final phase of their dissertation research or terminal degree project.
Outstanding Reviewer
IEEE Transactions on Power Delivery ∙
December 2019
Outstanding reviewers are those recommended by editors for special recognition due to their exceptional review work.
Fulbright Scholarship
U.S. Department of State ∙
July 2016
The Fulbright Foreign Student Program awards merit-based grants for graduate students, young professionals and artists from abroad to study graduate programs in the United States.
Knowledge Generation Program Award
Vice Presidency of Ecuador ∙
May 2014
The Knowledge Generation Program in Ecuador is a government initiative aimed at promoting research, science, technology, and innovation in the country. It focuses on strengthening national research and development capacities by supporting projects in strategic areas. The program provides funding, scholarships, and technical assistance to the best undergraduate students in higher education institutions.