I am an AI Research Engineer working across computer vision, biomedical and neuroimaging, natural language processing, and brain–computer interfaces. My work centers on the development of robust, well-structured machine learning systems, encompassing model architecture design, multimodal data preprocessing, signal analysis, and the construction of end-to-end research pipelines. I engage with a wide range of data modalities—images, video, text, and biosignals—drawing on methods in deep learning, multimodal modeling, and advanced computational signal processing. My approach emphasizes methodological rigor, reproducibility, and the alignment of technical development with scientific inquiry.

My broader motivation is shaped by a long-standing interest in the philosophy of mind and the foundations of scientific explanation. This perspective informs my research by grounding it in questions about cognition, representation, and the nature of intelligence. It also guides my commitment to developing AI systems that are analytically sound, ethically aware, and capable of contributing to deeper understanding within medical imaging, neurotechnology, and the study of intelligent systems.