Research Areas
Big Data in Biomedical Research focuses on model adaptability and data efficacy through various deep learning techniques.
Our team conduct comprehensive research into a range of complex neurological disorders, working to advance the field of diagnosis techniques using various deep learning techniques.
Our team applies deep learning methods to analyze EEG signals in Brain-Computer Interfaces (BCIs). We aim to provide personalized solutions for individual users, while also working on frameworks that have broader applicability.
Our team excels in the field of Molecular AI, unraveling the intricacies of molecular behaviors through innovative research. We are now pioneering research in Molecular Optimization, aiming to automate the refinement of molecular structure.
To gain a deeper understanding of brain function, our team aimed to enhance the accuracy of calcium signals by refining the processing of calcium imaging data. We employ deep learning techniques for the processing of calcium imaging data.
Our team leverages reinforcement learning for personalized medical decision-making, continuous learning, and research in areas like ROI and EEG-based medical traits, with a focus on enhancing care and patient outcomes.