| Apr 10, 2026 | Very exciting news! I have accepted an offer to join Carnegie Mellon University’s Department of Chemical Engineering as an Assistant Professor, starting August 2026! My group will develop hybrid scientific machine learning that merges first-principles physics with data-driven models for process design, control, optimization, and uncertainty quantification, with a strong focus on open-source tools for the chemical, energy, and biopharmaceutical sectors. |
| Apr 2, 2026 | Updated preprint! “A Simultaneous Approach for Training Neural Differential-Algebraic Systems of Equations” trains neural DAEs, a class of hybrid models that merges physics and machine learning, all at once via nonlinear programming. Check it out on arXiv. |
| Jan 27, 2026 | New co-authored preprint! We benchmark machine learning fault-detection methods on the classic Tennessee Eastman Process dataset. Available on ChemRxiv. |
| Jan 27, 2026 | New preprint! “Generative machine learning approaches to optimization” reframes root-finding, optimization, and parameter estimation as sampling from a learned distribution. Read it on ChemRxiv. |
| Jul 31, 2025 | New paper out! “Mapping uncertainty using differentiable programming” propagates and inverts uncertainty faster than Monte Carlo using a single model implementation. This is now available in the AIChE Journal. |
| Jan 22, 2025 | Our Comment “Beyond the fourth paradigm of modeling in chemical engineering” is out in Nature Chemical Engineering — we make the case that differentiable programming is reshaping how we model, teach, and practice chemical engineering! |
| Oct 22, 2024 | New paper as a co-author available! We employed a system identification technique using Gaussian processes. Available at the 2024 Power ASME proceedings |
| Oct 5, 2024 | New paper released! “On the selection of control structures using process operability analysis” presents a novel way to select control structures of plantwide systems, by taking advantage of process operability principles, namely the Operability Index (OI). It’s available on the Control Engineering Practice Journal |
| May 6, 2024 | I have joined Carnegie Mellon University as a Postdoctoral Fellow, under the supervision of Carl Laird and John Kitchin! |
| Apr 17, 2024 | I have successfully defended my PhD thesis under Dr. Fernando V Lima’s supervision, entitled “Strategies for Process Systems Mapping and Control Based on Operability Analysis”. You can download the thesis here. |
| Feb 6, 2024 | Our new paper on the opyrability Python package for advanced process operability analysis is now available in The Journal of Open Source Software! |
| Nov 8, 2023 | I presented our recent work entitled “An Implicit Mapping Approach for Process Systems Engineering Applications Using Automatic Differentiation and the Implicit Function Theorem” at the AIChE Annual meeting - Orlando, Florida. |
| Oct 30, 2023 | Our new paper on advanced hydrogen production using membrane reactors is now available in the Industrial and Engineering Chemistry Research Journal |
| Aug 10, 2023 | I presented my recent work of opyrability at the Mid-Atlantic Process Control (MPC) Academy Meeting, at The Ohio State University. |
| Apr 25, 2023 | Journal publication available at the AIChE Journal on a new approach for performing inverse mapping! |