(4gu) Computational Explorations of Self-Assembly and Collective Dynamics in Living and Non-Living Systems

I am fascinated by the complexity of self-assembled natural systems. My research involves developing computational models of observed systems and using them to evaluate general guiding principles and predict relevant properties, as well as design useful applications. The increasing capacity and availability of advanced computing systems offers the field of computational modeling ever-growing power and relevance, so that the characterization of individual component interactions at the nano- to macro-scale is able to inform the understanding and predictions of materials and processes within engineering. I have experience with developing and using a variety of modeling tools evaluating systems from the subatomic to macroscopic scales, including quantum chemistry calculations, molecular dynamics, Monte Carlo simulations, agent based particle models, finite element method, and tissue models.

My doctoral research experience focused on developing and applying molecular modeling methods to characterize carbon-based systems. In the Computational Modelling Group at the University of Cambridge, I worked to elucidate the mechanisms that control the formation and structure of carbonaceous soot nanoparticles in combustion environments. Some highlights from this work have included establishing an advanced computational model of heterogeneous soot particles, conducting the first dynamic study showing that long-range electrostatic interactions may be important in soot particle nucleation, quantifying the nanostructure and surface properties of heterogeneous soot particles, and developing a stochastic method for aromatic molecules to enable the efficient evaluation of large systems. This work has been well-received in journals and conferences across a number of academic communities, including chemistry, carbon materials, nanotechnology, molecular modeling, combustion, and chemical engineering. This research advanced our fundamental understanding of the mechanisms that control the formation and structure of carbonaceous particles and provided computational tools useful for investigating size and shape diversity in self-assembled hydrocarbon systems.

As a postdoctoral researcher, I have expanded into living systems and am especially interested in using computational tools to investigate emergent intelligence from self-organizing collective systems. At the Delft University of Technology, I explored theoretical biophysical approaches to microbial systems. I expanded an agent based model of self-propelled particles to capture key physical and chemical behaviours of bacterial cells, allowing cooperative and competitive interactions to be interrogated within and between heterogeneous colonies. This work focused on how the role of cell shape influences collective behaviors. At Boston University, I am currently using computational and experimental techniques to investigate the spatiotemporal patterning of biofilms. Through a combination of approaches at different scales, I am working to connect individual cell properties to colony-level behaviors, focusing especially on the interactions between swimming motile cells and stationary matrix-producing cells.

I am interested in computational modeling, self-assembly, and intelligent collective design. I have remained rooted in chemical engineering because I value how it integrates chemistry, physics, mathematics, and biology to address relevant problems.

Teaching Interests

I have been involved in nearly every aspect of student teaching and mentoring available, including planning and delivering an undergraduate course to a large class (139 students), teaching undergraduate tutorials (both academic and study skills), developing academic modules, giving departmental seminars, marking laboratory reports, and demonstrating and marking computing courses. I have also been involved in extracurricular student engagement and public outreach, for example participating in science fairs, public science festivals, mentorship programs, and departmental alumni outreach events.

My teaching philosophy is to foster an environment that promotes enthusiasm, connection to the real world, and active and life-long learning. My goal is to help students become motivated and inspired by the material, leave equipped to apply it, enabled to continue learning and growing. This is a continuously evolving journey for the teacher as well, as continued professional development in teaching is imperative for developing and implementing new ideas to improve teaching design, delivery, and assessment.

I have taught computing, chemistry, fluids, and molecular modeling, and am keen to be involved in fundamental engineering courses. I enjoy the fresh discovery and openness of new students so would be particularly interested in being involved in first year courses. I also believe that computing skills and modeling are increasingly important in all fields and would like to be involved in sharing this, at both the undergraduate and graduate levels. Mentorship, especially within a research context, is also a vital teaching outlet and I strive to be intentional in promoting academic and personal growth in these relationships.