Summary
Passara Chanchotisatien is a Biomedical AI PhD candidate and teaching support at the University of Edinburgh with eight years’ experience applying machine learning, signal processing, and wearable sensor analytics to respiratory health. They develop and evaluate time-series models and nonlinear feature engineering methods (e.g., SPAR attractors, PCMCI+ causal analysis) to detect cough, activity, and lung-function patterns from chest-worn accelerometers, collaborating closely with clinicians in the UK and US. In parallel they design and teach IoT and ML labs, assess coursework across AI ethics and software engineering, and translate research prototypes toward real-world monitoring tools. Their background spans practical ML deployments—from transformer fault-classification intern work to web-based model interfaces—to rigorous biomedical studies linking particulate exposure with respiratory outcomes. Passionate about bridging computation and clinical impact, Passara combines deep technical breadth with hands-on teaching and cross-disciplinary collaboration.
8 years of coding experience
Bachelor's degree, Computer Innovation Engineering, Bachelor's degree, Computer Innovation Engineering at King Mongkut's Institute of Technology Ladkrabang
Doctor of Philosophy - PhD, Biomedical AI, Doctor of Philosophy - PhD, Biomedical AI at The University of Edinburgh
Bachelor's degree, BEng in Computer Engineering with Minor in Artificial Intelligence, Bachelor's degree, BEng in Computer Engineering with Minor in Artificial Intelligence at Sirindhorn International Institute of Technology (SIIT), Thammasat University
Summer Program, Internet of Things and Big Data, Summer Program, Internet of Things and Big Data at Chulalongkorn University
Secondary/ Primary Education, Secondary/ Primary Education at RIS Ruamrudee International School
Thai, English, Chinese, German