###### Abstract  
Interdisciplinary research catalyzes innovation in mobile health (mHealth) by converging medical, technological, and social science expertise, driving critical advancements in this multifaceted field. Our longitudinal analysis evaluates how the NIH mHealth Training Institute (mHTI) program stimulates changes in research trajectories through a computational examination of 16,580 publications from 176 scholars (2015-2022 cohorts). We develop a hybrid analytical framework combining large language model (LLM) embeddings, Uniform Manifold Approximation and Projection (UMAP) dimensionality reduction, and Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) clustering to construct a semantic research landscape containing 329 micro-topics aggregated into 14 domains. GPT-4o-assisted labeling identified mHealth-related publications occupying central positions in the semantic space, functioning as conceptual bridges between disciplinary clusters such as clinical medicine, public health, and technological innovation. Kernel density estimation of research migration patterns revealed 63.8% of scholars visibly shifted their publication focus toward mHealth-dense regions within three years post-training. The reorientation demonstrates mHTI's effectiveness in fostering interdisciplinary intellect with sustained engagement, evidenced by growth in mHealth-aligned publications from the mHTI scholars. Our methodology advances science of team science research by demonstrating how LLM-enhanced topic modeling coupled with spatial probability analysis can track knowledge evolution in interdisciplinary fields. The findings provide empirical validation for structured training programs' capacity to stimulate convergent research, while offering a scalable framework for evaluating inter/transdisciplinary initiatives. The dual contribution bridges methodological innovation in natural language processing with practical insights for cultivating next-generation mHealth scholarship. 2020 IEEE/RSJ International Conference on Intelligent Intelligent Systems (IEEE)  
from science of science and team science domains, which investigate both knowledge production dynamics and the evolution of scientific collaborations [6; 7; 8]. The mHealth Training Institute (mHTI) represents a strategic implementation of these principles [9], creating an ecosystem where interdisciplinary collaboration in mobile health (mHealth) flourishes through structured convergence of medical, technological, and social science expertise. As an NIH-funded initiative, mHTI annually recruits 30 scholars from diverse disciplines to collaboratively address pressing healthcare challenges through intensive team-based projects. The program's unique structure combines webinars, sandboxes, and in-person collaborations to facilitate knowledge integration across disciplines. The mHTI serves as a unique observatory for analyzing interdisciplinary collaboration dynamics and knowledge evolution across three dimensions: formation mechanisms, topic emergence, and intellectual diffusion patterns. Here, we focus on the last two dimensions. This study is driven by a set of interconnected research questions designed to unravel the complexities and the migration of research topics within the mHealth domain. At its core, this investigation begins by addressing a foundational question (Q1): What research topics have the mHTI scholars published on? Identifying the thematic areas explored by researchers is crucial for mapping the intellectual landscape and laying the foundation for further knowledge discovery. Building on this foundation, this study delves into a second critical question (Q2): Of all the articles published by the mHTI scholars, which are related to mHealth topics and how? Addressing this question is essential for evaluating how effectively mHTI sustains scholarly engagement with mHealth--a core mandate of the training initiative.