Research Teams

Endocrine Transitions and Cognitive-Emotional Regulation in Postpartum Depression

Although postpartum psychology has been extensively studied through depression, anxiety, and maternal mood, considerably less is known about how postpartum endocrine changes interact with specific cognitive-emotional processes underlying these conditions.

Evolutionary Conservation of Dormancy Mechanisms Across the Tree of Life

Dormancy has evolved independently across nearly every major branch of life, allowing organisms to survive prolonged periods of environmental stress through states such as diapause, hibernation, quiescence, anhydrobiosis, seed dormancy, and microbial persistence.

Spectral Stability of Graph Laplacians Under Structured Edge Perturbations

This project asks whether structured edge perturbations lead to consistent patterns of spectral change that are independent of the underlying graph construction.

Persistent Homology as a Framework for Detecting Structural Phase Transitions in Dynamic Social Networks

This project asks whether topological invariants derived from persistent homology identify structural transitions in dynamic networks more effectively than conventional graph statistics.

Spatial Transcriptomic Profiling of Tumor-Associated Macrophage Polarization States Mediated by TGF-β1 Signaling Gradient in Pancreatic Ductal Adenocarcinoma Microenvironment

This literature review will examine the spatial heterogeneity and functional plasticity of tumor-associated macrophages (TAMs) within the pancreatic ductal adenocarcinoma (PDAC) microenvironment, emphasizing how gradients of transforming growth factor-beta 1 (TGF-β1) regulate macrophage polarization and contribute to tumor progression.

Epigenetic Aging as a Predictor of Immune Decline Across the Human Lifespan

This project investigates whether epigenetic age acceleration is associated with measurable changes in immune system composition and function using large population-based cohorts containing paired DNA methylation profiles and immunological measurements.

Graph-Based Evidence Selection for Improving Retrieval-Augmented Generation in Large Language Models

This project investigates whether retrieval can be improved by optimizing the diversity and complementary information content of retrieved evidence rather than maximizing similarity scores alone.

Graph Neural Networks for Individualized Prediction of Alzheimer's Disease Progression

Alzheimer's pathology spreads along connected brain regions, yet most models treat regional measurements as independent. This team models each patient's brain as a connectivity graph and tests whether graph neural networks forecast individual disease progression better than non-graph baselines on the same features.