My research focuses on signal processing, personal model development, and machine learning / deep learning, including CNN, LSTM, and GAN-based methods, as well as LLMs. I develop and apply these techniques to mHealth and digital health applications, extracting personalized insights from physiological, behavioral, and contextual data collected from multiple data sources, such as smartwatches. With hands-on experience in real-world applications, I have developed my analytical and problem-solving skills, along with proficiency in Python programming, enabling me to effectively develop and implement AI solutions. Throughout my journey, I have had dynamic collaborations across academia, industry, and the healthcare sectors, resulting in the publication of over 50 peer-reviewed papers in both medical and technological venues.