I am a research scientist located at RIKEN, Japan. My main research goal is to formulate a theory which can predict the behavior of chemical reaction networks.
Many chemical processes we are interested in consist of multiple chemical reactions. For example, catalytic reactions typically involve at least two steps: First, the reactant must adsorb on the catalyst, and afterwards, the reactant must desorb to yield the product. In reality, the true mechanism is more complex with many more steps involved, thus resulting in a network of multiple chemical reactions. Right now, it is difficult to accurately predict the properties of a chemical reaction, such as the reaction rate or stability, because the kinetics of a reaction are difficult to formulate. Breaking this barrier and paving the way towards quantitative prediction of catalyst properties is my major research goal.
Due to the ubiquity of chemical reaction networks, such a theory may eventually contribute to our understanding of systems beyond catalysis. For example, biological metabolism is a network of biochemical reactions catalyzed by enzymes. The carbon (CO2) cycle is also a chemical reaction network which occurs at the ecological scale. In this way, the abstract level of understanding provided by chemical reaction networks may help us solve important challenges facing society today.
My endeavor to answer these questions has lead me to learn new techniques. After starting out as an experimental spectroelectrochemist, I have self-taught myself the basics of chemical reaction network theory which is a branch of applied mathematics, Python (numerical simulations, machine learning, bioinformatics), and introduced myself to complexity and chaos. I am always eager to learn something new, and I believe that the freedom to do so is one of the greatest joys of being a scientist.