Curriculum Vitae

Education

• Ph.D Process Systems Engineering, MPI-Magdeburg and Otto von Guericke University, 2024 (expected)
• M.Sc. Advanced Chemical Engineering with Process Systems Engineering, Imperial College London, 2019
• B.Eng. Chemical Engineering, UNAM, 2018

Research experience

• Visiting researcher — (Sep 2023 - Nov 2023)
  • Carnegie Mellon University, USA – In group of Gabe Gomes
  • AI for chemistry. Training GNNs on large molecular datasets. Automatic literature data retrieval. Embedding thermodynamics into GNNs.
• Doctoral researcher — (Nov 2019 - present)
  • Max Planck Institute for Dynamics of Complex Technical System, Germany – In group of Kai Sundmacher
  • GNNs for molecular and mixture property prediction. ML for process optimization.
• Research intern — (May 2018 - Jul 2018)
  • The University of Manchester/Imperial College London, UK – In group of Antonio del Rio Chanona and Dongda Zhang
  • Coded several stochastic optimization algorithms in Python
• Research assistant — (Jun 2017 - Sep 2017)
  • McMaster University, Canada – In group of Thomas A. Adams II
  • Studied semi-continuous distillation systems using Aspen Plus
• Research assistant — (Feb 2017 - Jun 2017)
  • University of California - Riverside, USA – In group of Haizhou Liu
  • Light dispersion experiments for antiscalants analysis
• Research intern — (Jun 2016 - Aug 2016)
  • University of Maryland, USA – In group of Jeffery B. Klauda
  • Molecular dynamics using NAMD and VMD

Work experience

• Electricity Market Analyst — (Nov 2017 - Feb 2018)
  • Bravos Energia, Mexico
  • Developed a Mexican electricity tariffs model for forecasting

M.Sc. Theses supervised

• 2023 Christoph Griehl (now PhD researcher at MPI Magdeburg), Phosphine ligand selection for homogeneous catalysis applications embedding Machine Learning methods, OVGU.
• 2023 Sreekanth Kunchapu (now PhD researcher at University of Jena), Prediction of Infinite Dilution Activity Coefficients in Polymer Solutions Using Graph Neural Networks, OVGU.
• 2022 Rahul Bankala (now project manager at AKKA Technologies), Multi-objective optimization of an organic Rankine cycle system using Gaussian processes, OVGU.
• 2021 Anahita Iravanizad (now PhD researcher at MPI Magdeburg), Enriching Graph Neural Network Input via Random Walks on Graphs, TU-Chemnitz.
• 2021 Manoj Mangipudi (now PhD researcher at KIT), Gaussian processes for the prediction of molecular Environmental, Health and Safety (EHS) properties, OVGU.
• 2021 Viswa Sunkavalli (now Research assistant at BAM), Graph Neural Networks for the prediction of environmental indicators of molecules, OVGU.

Publications

See my my Google Scholar profile.

Teaching

Machine Learning in Chemical Engineering (lectures)

Process Systems Engineering (tutorials)

Machine Learning in Chemical Engineering (tutorials)

Service and leadership

• Mentor — (Sep 2023 - Mar 2024)
  • Process Systems Engineering in Mexico, Mexico
  • Duties: mentorship and supervision of a PhD student as part of the workshop mentorship program.
  • The work lead to this publication.
• Executive Board member — (Dec 2021 - Oct 2022)
  • RIIAA, LATAM
  • Duties: Strategic management of RIIAA and Summer school organization
• Chair — (Sep 2020 - Nov 2021)
  • RIIAA, LATAM
  • Duties: Leader of the Summer school organization team
• Organizing member — (Dec 2019 - Sep 2020)
  • RIIAA, LATAM
  • Duties: Summer school organization