CV

Education

B.S. in GitHub, GitHub University, 2012
M.S. in Jekyll, GitHub University, 2014
Ph.D in Version Control Theory, GitHub University, 2018 (expected)

Work experience

Summer 2015: Research Assistant
- Github University
- Duties included: Tagging issues
- Supervisor: Professor Git
Fall 2015: Research Assistant
- Github University
- Duties included: Merging pull requests
- Supervisor: Professor Hub

Skills

Skill 1
Skill 2
- Sub-skill 2.1
- Sub-skill 2.2
- Sub-skill 2.3
Skill 3

Publications

Heterogeneous Catalytic Ozonation of Phenol over Iron-based Catalysts in a Trickle Bed Reactor

Briceño, L., Durán, J. E. (2020). "Heterogeneous Catalytic Ozonation of Phenol over Iron-based Catalysts in a Trickle Bed Reactor." Ingenieria. 20(July-December 2020).

Machine learning for guiding high-temperature PEM fuel cells with greater power density

Luis A. Briceno-Mena, Gokul Venugopalan, José A. Romagnoli, Christopher G. Arges. (2021). "Machine learning for guiding high-temperature PEM fuel cells with greater power density, " Patterns. Volume 2, Issue 2, 2021, 100187, ISSN 2666-3899, https://doi.org/10.1016/j.patter.2020.100187.

Electrochemical Pumping for Challenging Hydrogen Separations

Gokul Venugopalan, Deepra Bhattacharya, Evan Andrews, Luis Briceno-Mena, José Romagnoli, John Flake, and Christopher G. Arges ACS Energy Lett. 2022, 7, XXX, 1322–1329 DOI: 10.1021/acsenergylett.1c02853.

PemNet: A Transfer Learning-Based Modeling Approach of High-Temperature Polymer Electrolyte Membrane Electrochemical Systems

Luis A. Briceno-Mena, José A. Romagnoli, and Christopher G. Arges Industrial & Engineering Chemistry Research 2022 61 (9), 3350-3357 DOI: 10.1021/acs.iecr.1c04237.

Electrochemical Pumping for Challenging Hydrogen Separations

TGokul Venugopalan, Deepra Bhattacharya, Evan Andrews, Luis Briceno-Mena, José Romagnoli, John Flake, and Christopher G. Arges, ACS Energy Letters 2022 7 (4), 1322-1329.

Data mining and knowledge discovery in chemical processes: Effect of alternative processing techniques

Briceno-Mena, L., Nnadili, M., Benton, M., & Romagnoli, J. (2022). Data mining and knowledge discovery in chemical processes: Effect of alternative processing techniques. Data-Centric Engineering, 3, E18. doi:10.1017/dce.2022.21

Optimization of multi-mode classification for process monitoring

Zachary Webb, Miriam Nnadili, Estelle Seghers, Luis Briceno-Mena, José Romagnoli (2022). Optimization of Multi-Modal Classification for Process Monitoring. Frontiers in Chemical Engineering, 4, 2673-2718

Deconvoluting charge-transfer, mass transfer, and ohmic resistances in phosphonic acid–sulfonic acid ionomer binders used in electrochemical hydrogen pumps

Arunagiri, Karthik, Wong, Andrew Jark-Wah, Briceno-Mena, Luis, Elsayed, Hania Gaber Hassan, Romagnoli, José A., Janik, Michael J., & Arges, Christopher G. (2023). Deconvoluting charge-transfer, mass transfer, and ohmic resistances in phosphonic acid–sulfonic acid ionomer binders used in electrochemical hydrogen pumps. Energy & Environmental Science, 16(12). https://doi.org/10.1039/d3ee01776a

Synergizing data-driven and knowledge-based hybrid models for ionic separations

Teslim Olayiwola, Luis A. Briceno-Mena, Christopher G. Arges, and Jose A. Romagnoli ACS ES&T Engineering 2024 4 (12), 3032-3044.

Machine Learning for Accelerating Materials Development for Electrochemical Systems: Fuel Cells and Electrochemical Separations

September 27, 2021

Workshop talk at Telluride Science Research Center Workshop on Machine Learning and Informatics for Chemistry and Materials, Telluride, Colorado, United States

Luis Briceno-Mena

CV

Education

Work experience

Skills

Publications

Heterogeneous Catalytic Ozonation of Phenol over Iron-based Catalysts in a Trickle Bed Reactor

Machine learning for guiding high-temperature PEM fuel cells with greater power density

Electrochemical Pumping for Challenging Hydrogen Separations

PemNet: A Transfer Learning-Based Modeling Approach of High-Temperature Polymer Electrolyte Membrane Electrochemical Systems

Electrochemical Pumping for Challenging Hydrogen Separations

Data mining and knowledge discovery in chemical processes: Effect of alternative processing techniques

Optimization of multi-mode classification for process monitoring

Deconvoluting charge-transfer, mass transfer, and ohmic resistances in phosphonic acid–sulfonic acid ionomer binders used in electrochemical hydrogen pumps

Synergizing data-driven and knowledge-based hybrid models for ionic separations

Talks

Use of a trickle bed reactor for heterogeneous catalytic ozonation of phenol

Iron- and Manganese-modified Diatomite as Catalyst for Ozonation of Wastewater

Modelado, optimización y control en Ingeniería Química vía aprendizaje automático

Modelado, Optimización y Control en Ingeniería Química vía Aprendizaje Automático

A Machine Learning Approach for Device Design from Materials and Operation Data

Inteligencia artificial y simulación en Ingeniería Química: Ampliando los horizontes del diseño y la optimización

Machine Learning for Accelerating Materials Development for Electrochemical Systems: Fuel Cells and Electrochemical Separations

Teaching

Assistant Professor

Teacher Assistant

Service and leadership