We are living in a transformative period in medicine and biology, characterized by an unprecedented expansion of data from clinical records, epidemiologic studies, and multi-omics platforms. While this growth creates extraordinary opportunities for discovery, it also demands a new form of literacy—one that enables trainees to interpret, analyze, and critically evaluate complex datasets. With formal training in statistics, biomedical informatics, and clinical investigation, my work lies at the intersection of data science and medicine. I am particularly motivated by helping others navigate this landscape with clarity, confidence, and purpose.
Teaching at this intersection provides a valuable opportunity to train students—especially those in medicine—to think across disciplines and approach complex problems from multiple perspectives. My teaching philosophy centers on fostering an interdisciplinary mindset that allows learners to integrate concepts from biology, medicine, computer science, statistics, and public health.
A central component of my approach is making quantitative methods accessible to learners from clinical and biological backgrounds. I aim to cultivate both curiosity and analytical confidence. Over the past decade, I have taught or co-taught more than a dozen seminars and workshops in informatics and biostatistics. In summer 2025, I will lead PH302: Introduction to Biostatistics at Northwestern University, a course I have redesigned to integrate foundational theory with hands-on, lab-based applications. This emphasis on applied learning helps students connect quantitative methods to real-world clinical and research contexts.
My academic training reflects a sustained commitment to interdisciplinary scholarship. I began in chemical biology and mathematics at UC Berkeley, and later earned a Ph.D. in biomedical informatics along with M.S. degrees in statistics and clinical investigation at Northwestern. I completed a postdoctoral fellowship and now serve as a team scientist with faculty appointments in dermatology and preventive medicine. Although informatics and dermatology may seem like an unconventional combination, this intersection has proven highly impactful. Dermatology is increasingly data-intensive, yet relatively few departments have dedicated informatics expertise. My role allows me to bridge clinicians and researchers by supporting study design, data analysis, and statistical interpretation.
In addition, as Director of the Bioinformatics and Statistics Program at the TEST IT² Skin Biology & Diseases Resource-Based Center (SBDRC), I collaborate with investigators across disciplines who require specialized expertise in skin biology and data science. These experiences strongly inform my teaching. In today’s biomedical environment, meaningful advances depend on collaborative, cross-disciplinary work. In my courses and workshops, I draw on examples from skin biology, transcriptomics, climate data, and clinical epidemiology to illustrate how data-driven methods inform both medical decision-making and public health policy.
My goal in interdisciplinary training extends beyond technical proficiency. I emphasize critical thinking, intellectual flexibility, and collaborative problem-solving. Students learn to examine the assumptions underlying statistical models, interpret findings in appropriate clinical contexts, and consider the ethical dimensions of working with large-scale biomedical data. Communication is also a key focus—students practice translating complex quantitative results into clear, accessible narratives for diverse audiences, including clinicians, scientists, and policymakers.
Looking ahead, I plan to expand my teaching through the development of structured, modular programs that combine rigorous instruction with project-based learning. Potential offerings include courses on clinical database analysis, RNA-seq interpretation, and reproducible workflows for multi-omics research, all grounded in collaborative, hands-on experience. I am equally committed to ongoing faculty development and continuous evaluation to ensure that my teaching remains effective and responsive.
My commitment to interdisciplinary education is also reflected in my mentorship. I have worked with trainees across a range of levels and disciplines, many of whom have contributed to NIH-funded research in genetics, transcriptomics, environmental health, and dermatology. Through co-mentorship with faculty in dermatology, pathology, and bioinformatics, I ensure that mentees are exposed to diverse perspectives and methodologies. Several of my mentees have gone on to research careers in academia and industry, where they continue to build on their interdisciplinary training. I prioritize individualized mentorship that aligns with each trainee’s goals while preparing them to work effectively across fields.
In my leadership role within the SBDRC, I am also developing educational infrastructure to support interdisciplinary learning communities. This includes initiatives such as creating accessible databases for single-cell RNA-seq data and organizing collaborative workshops and cross-departmental programs that bring together faculty and trainees to address shared scientific challenges.
The Searle Fellowship has played an important role in my development as an educator by providing a collaborative, interdisciplinary environment and sustained mentorship. Through engagement with faculty mentors, program coordinators, and peer fellows, I have had the opportunity to reflect on and refine my teaching practices while exploring innovative, evidence-based approaches. Program components—including retreats, Teaching Salons, and project-based sessions—have supported the development of my teaching initiative focused on enhancing statistical education for medical students and clinical researchers through the use of AI tools.
Ultimately, I view data science not simply as a technical skill set, but as a language essential to modern biomedical research. My goal is to equip students and collaborators with the fluency to ask meaningful questions and the tools to pursue rigorous, evidence-based answers. It is a privilege to teach at this pivotal moment in biomedical science, and I remain motivated by the discoveries and progress that interdisciplinary learning makes possible.