Faculty Application Package Overview

Overview

I aim to build an inclusive, collaborative research and teaching program at the intersection of machine learning and materials science. As a faculty member, I will contribute: (1) a vision for AI-driven experimentation to accelerate discovery of sustainable soft materials; (2) student-centered teaching that blends statistical rigor with modern computing; and (3) sustained, values-driven service to broaden participation in STEM and strengthen our scientific community.

Research Program (high-level)

My research focuses on discovering sustainable soft materials at scale using AI-driven experimentation. I develop interpretable, data-efficient models and closed-loop optimization frameworks that connect experimental observables to structure–property relationships. The proposed program integrates three thrusts: (i) autonomous, feedback-driven experimental design; (ii) geometry- and physics-informed learning for small, noisy datasets; and (iii) multimodal characterization workflows that link scattering/spectroscopy to predictive modeling. The goal is a practical path to self-driving laboratories that accelerate discovery while maintaining scientific rigor and reproducibility.

Key outcomes include robust representations for soft matter systems, uncertainty-aware decision making for experiment planning, and community-facing software to democratize autonomous workflows.

Teaching Statement (high-level)

I take an open, iterative approach to teaching—grounded in real-world examples, active learning, and accessible materials. At UW, I designed and delivered a graduate course on modern design of experiments for chemical engineers and materials scientists, receiving strong student feedback (4.2/5). I plan to develop advanced courses such as Data-Driven Soft Materials Characterization and Stochastic Optimization and Feedback Control, emphasizing hands-on computation, uncertainty quantification, and rigorous statistical thinking. My classrooms are inclusive, feedback-rich, and designed to prepare students for interdisciplinary careers.

Service and Closing

My service philosophy centers on outreach, inclusive mentoring, and professional community building. Past activities include leading community initiatives during my undergraduate years, mentoring students from underrepresented institutions, supporting international scholars, and contributing as a journal reviewer (recognized with RSC Digital Discovery Outstanding Reviewers Award, 2023). Looking ahead, I will expand outreach with local schools, create research pathways for students from minority-serving institutions, and contribute to society leadership in autonomous experimentation and data-driven materials discovery.

I am committed to building a vibrant, equitable research group and to advancing the broader STEM community. I look forward to contributing to departmental excellence through impactful research, inspiring teaching, and sustained service.