Computational Intelligence Network
The Computational Intelligence Network at the Universal Platform for Integrative Biomedical Innovation (UPIBI) was established to connect researchers interested in advancing digital health and biomedical science through emerging AI technologies. The initiative supports collaborations in artificial intelligence, machine learning, natural language processing, and other computational methods applied to healthcare data and research discovery.
Below is a list of affiliated investigators currently open to new collaborations:
- Dr. Alina Chen – artificial intelligence, predictive modeling, feature engineering, data mining
- Dr. Marcus Lee – privacy-preserving learning algorithms, dynamic risk estimation, decentralized model training, computational reviews
- Dr. Isabel Moreno – AI-driven clinical NLP, imaging informatics, unstructured data extraction, radiological analysis
- Dr. Jonah Strauss – knowledge discovery through machine learning, network modeling, simulation-based inference, intelligent systems
- Dr. Taryn Xu – clinical text mining, phenotyping algorithms, outcome prediction, semantic processing
- Dr. Ethan Kwan – graph-based deep learning, interpretable neural architectures, data structure modeling, scalable AI systems
- Dr. Nia Vargas – pattern recognition in imaging, computational diagnostics, integrated image-genomic analytics
- Dr. Malcolm Grey – automated machine learning, AI optimization, symbolic programming, custom model construction
- Dr. Selena Knox – phenotype clustering, evolutionary computing, supervised and unsupervised learning strategies
- Dr. Felix Zhou – large-scale biomedical informatics, visual computing, structural analytics, network intelligence
- Dr. Owen Hartley – rule-based systems, interpretable AI pipelines, data workflow automation, hybrid evolutionary modeling