Mr Ahtisham Ayyub

Research project: Anomaly detection and disease classification in ECG signals using AI-Assisted Decision Making


In England alone, cardiovascular diseases' (CVD) related healthcare costs amount to an estimated £7.4 billion per year, and annual costs to the wider economy being an estimated £15.8 billion. The UK government is focused on telemedicine, and in the next five years, with the help of the NHS, it plans to save at least 150,000 lives each year by avoiding/managing heart attacks.

This project focuses on introducing smart ECG machines which can detect anomalies in ECG signals in real-time. Based on an advanced, artificial intelligence(AI) aided signal processing models, these machines will be able to memorize the sequences of ECG signals. To classify the CVDs, the acquired abnormal signals will be further converted to spectrogram images for input to a 3D image classification model. 


I am a graduate of FAST NUCES (Pakistan). During the masters, I worked on gait-based person recognition using various deep learning models, such as LSTM, BLSTM and CNN-LSTM.

I have worked as a teacher for more than ten years, while I taught college students back in Pakistan. Moreover, I also have experience in working as a teacher assistant for several modules during the masters.

Areas of research interest

  • Machine Learning
  • Deep Learning
  • Computer Vision
  • Image Processing
  • Python
  • Computer Networks


  • MS Computer Science , FAST NUCES
  • MSc Computer Science, GCUF

Funding or awards received

  • Kingston University Studentship