Chang-Le (Charles) Chen

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Email: chc348(at)pitt(dot)edu

Chang-Le (Charles) Chen – Researcher in Neuroscience, Medicine, Computation, and AI

Scientist + Engineer + AI enthusiast

Chang-Le (Charles) is a postdoctoral scholar in EECS at UC Berkeley. He received his PhD in Bioengineering from the University of Pittsburgh, specializing in AI/ML, neuroimaging, and clinical neuroscience. With experience as a research engineer at National Taiwan University College of Medicine and University of Pittsburgh Medical Center, he integrates physics-based modeling, neuroimaging, and machine learning to uncover the mechanisms of brain aging, neurological diseases, and psychiatric disorders. His work focuses on developing scalable algorithms and quantitative biomarkers that bridge research and clinical practice. Driven to transform scientific innovation into real-world impact, Charles develops next-generation neuroimaging technologies and foundation AI systems to improve diagnosis, treatment, and patient outcomes across the global healthcare and life sciences landscape.

Recent work:

My research focuses on, but is not limited to, the following topics:

  • Developing statistical learning and harmonization frameworks to integrate neuroimaging and multi-site biomedical data, reducing site/pipeline bias and enabling large-scale analyses.

  • Creating and validating neuroimaging-derived markers (structural, fluid-dynamics, functional) to detect aberrant brain physiology and pathology, especially in aging and neurological disorders.

  • Building large-scale multimodal prediction paradigms and normative models using deep representation learning (integrating imaging, clinical, demographic, and AI/ML features) for early detection, prognosis, and individualized assessment across brain aging and disease.

  • Designing scalable deep-learning pipelines for multi-site, multi-modal biomedical datasets (neuroimaging, genetics, clinical) that emphasize reproducible prototypes and translational readiness.

  • Bridging interdisciplinary domains (mathematics, physics, neuroscience, AI) to develop foundation AI systems and agentic models in healthcare/life-sciences settings, advancing from algorithmic innovation to clinical workflow integration.

This website presents Charles’s profile, publications, and research interests. For more details, feel free to reach out at chc348(at)pitt(dot)edu.