Ian Daly

About

Ian Daly is a leading researcher in brain-computer interfaces (BCIs), with a particular focus on steady-state visual evoked potentials (SSVEPs) and their application to real-world control systems. His most cited work, "Squeeze and Excitation-Based Multiscale CNN for Classification of Steady-State Visual Evoked Potentials" (2024, 9 citations), introduces a novel deep learning architecture that significantly improves the accuracy and speed of SSVEP signal classification. This contribution directly addresses a key challenge in BCI technology: translating neural signals into reliable, real-time commands. Daly’s research bridges the gap between fundamental neuroscience and practical IoT device control, demonstrating how BCIs can be integrated into smart healthcare, smart homes, and other assistive technologies. By enhancing the robustness of SSVEP-based systems, his work paves the way for more intuitive and accessible interfaces for individuals with motor impairments. With a growing citation impact, Daly is establishing himself as a key innovator in applied BCI research, where his focus on deep learning and signal processing continues to push the boundaries of what is possible in human-computer interaction.

Research Focus

Key Achievements

Top Papers

1. 1
   Squeeze and Excitation-Based Multiscale CNN for Classification of Steady-State Visual Evoked Potentials

   9 citations · 2024

Key Collaborators

Contact & Links