Developing robust and scalable manufacturing processes for specialty chemicals and pharmaceuticals is critical for bringing new products to market efficiently. However, traditional experimental approaches to process optimization can be time-consuming and resource intensive. To address this challenge, my work integrates hands-on industrial process development with first-principles computational modeling. My expertise spans from practical process scale-up, technology transfer, and CMC documentation (gained at Corteva Agriscience, Materia, and SABIC) to deep theoretical analysis using density functional theory (DFT) and molecular dynamics (MD). In my Ph.D. research, I developed a computational workflow to rationally design novel macrocyclic polymers for targeted separations of persistent organic pollutants like PFAS from groundwater. This modeling-first approach successfully identified key structure-property relationships, guiding leading to subsequent experimental validation. In my industrial work, I applied process modeling and experimental design to reduce key tox-relevant impurities in a late-stage commercial product pipeline.
Research Interests:
My career interests lie in applying this integrated computational and experimental approach to solve critical challenges in process development, scale-up, and manufacturing for the pharmaceutical and specialty chemical industries. I am seeking a full-time R&D Scientist or Process Development Engineer role where I can contribute to bringing innovative products and advanced materials to market by developing robust developing robust and efficient scalable manufacturing processes.
