Research Accepted and Presented at IEEE BECITHCON 2026
Contributed to an ECG arrhythmia classification paper accepted at IEEE BECITHCON 2026 and completed an online presentation of the research.
A research paper I contributed to, “Ablation Driven CNN-BiLSTM-Attention Network With SHAP for ECG Arrhythmia Classification,” was accepted at IEEE BECITHCON 2026 under Paper ID 530.
The study investigates a hybrid deep learning approach to ECG heartbeat classification, combining a CNN, bidirectional LSTM, and attention mechanism. It also includes ablation experiments and SHAP explanations to examine model performance and interpretation.
I completed an online presentation of this research at the conference, sharing the study’s approach and findings with an academic audience. This achievement strengthened my experience in research communication and presenting technical work.