Patrick Langer

Background

About Patrick Langer

I am a doctoral researcher at Stanford and ETH Zurich in Computer Science and Machine Learning. In my research, I develop machine learning, deep learning, and explainable AI methods to transform multimodal digital health data into actionable healthcare insights. My research areas include models for asthma, cough detection, aging, circadian rhythm monitoring, physical activity, and BMI estimation. I routinely develop Android, WearOS, and iOS applications, deploying machine learning models on smartphones and smartwatches (Galaxy Watch, Pixel Watch) to translate research findings into real-world applications. Having started programming at age 11, I have built a strong foundation in computer science, particularly in machine learning, deep learning, and software frameworks. I have contributed to numerous projects involving machine learning, computer vision, and explainable AI across cloud, edge, mobile, and wearable devices, and FPGAs. I launched open-source initiatives such as CLAID (claid.ch), a cross-platform mobile machine learning framework. I am one of the winners of Jugend forscht 2016, for which I designed and built a human-computer interface based on Electromyography (EMG) from scratch, allowing handicapped people to write texts or play games using action potentials digitalized via an Arduino.