My primary research interests lie at the intersection of computation, logic, and algorithms within fundamental, molecular, and evolutionary biology, chemistry, and economics. I am particularly interested in addressing foundational problems in the application of chemistry to biological systems through computational logic and algorithmic methods. In addition, I am drawn to applied econometrics and the quantitative analysis of behavioral patterns, especially within the context of behavioral economics.
- Developing AI-guided quantum models to analyze charge distribution topologies using QTAIM and EDA during CRISPR-Cas9 DNA cleavage, aiming to minimize unintended off-target mutations.
- Using time-resolved quantum simulations to study epigenetic DNA methylation, especially how enzyme internal electric fields act as molecular switches for proton and electron tunneling.
- Applying hybrid quantum machine learning to telomeric G-quadruplex structural dynamics, with focus on 3D macromolecular aromaticity, magnetic properties, quantum coherence, and π–π stacking.
- Designing bit-based and qubit-based biological logic gates for controlling synthesis pathways, catalysts, and biosensors in vitro and in vivo.
- Developing algorithmic optimization frameworks for total synthesis of natural products and pharmaceutical compounds.
- Constructing behavioral estimation models in macroeconomics, including predictive and structural modeling of economic decision-making and voting behavior based on game theory.
