Miguel A. Modestino is the Director of the Sustainable Engineering Initiative and the Donald F. Othmer Associate Professor of Chemical Engineering at New York University (NYU). Miguel obtained his B.S in Chemical Engineering (2007) and M.S. in Chemical Engineering Practice (2008) from the Massachusetts Institute of Technology, and his Ph.D. in Chemical Engineering from the University of California, Berkeley (2013). From 2013-2016, he was a post-doctoral researcher at the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland where he served as project manager for the Solar Hydrogen Integrated Nano-electrolysis (SHINE) project.
He is a winner of the Global Change Award from the H&M Foundation (2016), the MIT Technology Review Innovators Under 35 Award in Latin America (2017) and Globally (2020), the ACS Petroleum Research Fund Doctoral New Investigator Award (2018), the NSF CAREER Award (2019), the Inaugural NYU Tandon Junior Faculty Research Award (2020), and TED Idea Search Latin America (2021).His research group at NYU focusses on the development of electrochemical technologies for the incorporation of renewable energy into chemical manufacturing. He is also co-founder of Sunthetics Inc., a startup developing machine learning solutions to accelerate the development of sustainable chemical processes.
Read Miguel’s Emerging Investigator article, ‘Chemically-informed data-driven optimization (ChIDDO): leveraging physical models and Bayesian learning to accelerate chemical research‘, DOI: 10.1039/D2RE00005A
1. How do you feel about RCE as a place to publish research on this topic?
Over the past few years, RCE has became the home of the reaction engineering community, and we are proud to have contributed to its growth by publishing our work on electro-organic reactions and machine learning optimization applied to chemical systems. While our team publishes in many different venues, we see RCE as the central journal for our community and a perfect venue for our core reaction engineering work.
In recent years, RCE has emerged as one of the most important journals for the reaction engineering community, and we take great pride in our contributions to its growth. Our team’s research on electro-organic reactions and machine learning optimization applied to chemical systems has been published in the journal as we recognize RCE as the core publication of our field.
2. What aspect of your work are you most excited about at the moment and what do you find most challenging about your research?
I am very excited about our recent work at the interface of electrochemical reaction engineering, automation, and machine learning optimization. The mission of our group is to help decarbonize the chemical manufacturing industry via electrochemistry, and we recognize that it is a daunting challenge. To that end, we are rapidly building high-throughput electrochemical reactors and implementing machine learning optimization algorithms to accelerate the path from idea to discovery to scale-up, and hope to contribute solutions in the short timeframe that we have to decarbonize our industry.
3. In your opinion, what are the most important questions to be asked/answered in this field of research?
The central question that we aim to answer is how to develop cost-competitive electrochemical processes with high selectivity, efficiency, and throughput, which can operate stably at scale over long periods of time.
4. Can you share one piece of career-related advice or wisdom with other early career scientists?
Follow your passion, think critically, and inspire the next generation to pursue impactful careers that address society’s biggest problems.