معرفی
David Carlson is the Yoh Family Associate Professor of Civil and Environmental Engineering at Duke University, with additional appointments in Biostatistics & Bioinformatics, Computer Science, and Electrical and Computer Engineering. He is a faculty network member of the Duke Institute for Brain Sciences and actively contributes to interdisciplinary research bridging engineering, neuroscience, and medicine.
His research interests include machine learning, predictive modeling, health data science, and statistical neuroscience. He focuses on developing explainable and reproducible AI methods to analyze complex datasets, particularly in environmental health, mental health, and neuroscience. His work emphasizes both theoretical innovation and practical application, often involving collaborations with clinicians and domain experts.
Carlson's recent publications reveal a strong focus on applying deep learning and statistical models to neuroscience (e.g., EEG, neural dynamics), environmental monitoring (e.g., air quality, urban heat), and health data. His 2025 work includes transformer models for genomics, reproducibility checklists for neural engineering, and scalable Gaussian processes for climate data, indicating a sustained emphasis on robust, interpretable machine learning across domains.
Scientific Awards:
- Yoh Family Associate Professor of Civil and Environmental Engineering
Advising and Grants: David Carlson has advised numerous students across multiple publications in machine learning, neuroscience, and environmental engineering. His research is supported by interdisciplinary collaborations and likely institutional or federal grants, though specific grant details are not mentioned in the text. He teaches a variety of advanced and independent study courses, indicating active mentorship.
Labs and Teams: While no specific lab name is mentioned, Carlson is deeply integrated into collaborative research teams, particularly with the Duke Institute for Brain Sciences and medical center partners like Dr. Kafui Dzirasa. His work involves multi-institutional and cross-departmental teams focused on neural engineering, environmental health, and AI for medicine.
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