Biography

Alaa Alahmadi is a Lecturer in Computing at the School of Computing, based in the Interdisciplinary Computing and Complex BioSystems (ICOS) research group. She has also held an honorary position at the University of Manchester since 2021.

She completed her MSc and PhD at the University of Manchester (2016-2021), working on data visualization across multiple clinical trials (with AstraZeneca) during her MSc, and then devising, developing and evaluating novel interdisciplinary methods for intuitively monitoring drug-induced acquired Long QT Syndrome (LQTS) during her PhD using explainable artificial intelligence and science-of-perception-based novel data visualisations approaches, collaborating with The Christie NHS Foundation Trust, Cancer Research UK, and AstraZeneca. She is currently establishing her research team and shaping her research vision at Newcastle University, leading a number of basic and translational research projects to build on her strong foundational work in intuitive ECG monitoring using explainable human-like AI, moving into a more holistic view of cardiotoxicity, pharmacogenomics & sudden cardiac death mechanisms. The research vision aims to advance ECG monitoring for life-threatening changes within cardio-oncology and beyond.

Research Interests

Alahmadi is passionate about interdisciplinary research that crosses the fields of Computer Science, Cognitive Science, and Medicine. She has a special interest in advancing Artificial Intelligence via understanding human perception and reasoning to better engineer Collaborative AI & Healthcare Technologies - integrating concepts, theories, perspectives, and computational & clinical knowledge within the design and innovation process. Current projects explore this approach across different fields include advancing Neurosymbolic AI in Medical Image Analysis, better understanding of Brain-Heart Interactions in Epilepsy, and developing new methods for Cardiac Digital Twin (CDT) in Cardio-Oncology to personalise cancer medicine and advance its early trials. Using this creative interdisciplinary approach, her research has transformed the monitoring of a life-threatening condition (long QT syndrome, caused by many commonly prescribed medications) by devising a novel colour-coding technique & explainable AI algorithm. The research has been recognised with numerous accolades, including the MIT Innovators Under 35 Award, the IET Healthcare Technology Awards (Highly Commended), and the Parliamentary and Scientific Committee STEM for Britain Awards (only Computer Science finalist). She also won multiple university awards, including the University of Manchester Outstanding Doctoral Paper in Computer Science (2019), Outstanding Doctoral Thesis in Computer Science (Runner Up, 2022), and UK-SACB Saudi Excellence Doctoral Research Awards in 2019, 2020 and 2021.

• Articles

  • A, Alahmadi, A, Davies, M, Vigo, C, Jay. Personalized, intuitive & visual QT-prolongation monitoring using patient-specific QTc threshold with pseudo-coloring and explainable AI. Journal of Electrocardiology 2023.
  • Sqalli, MT, Al-Thani, D, Elshazly, MB, Al-Hijji, M, Alahmadi, A, Houssaini, YS. Understanding Cardiology Practitioners’ Interpretations of Electrocardiograms: An Eye-Tracking Study. 2022.
  • Alahmadi, A, Davies, A, Royle, J, Goodwin, L, Cresswell, K, Arain, Z, Vigo, M, Jay, C. An explainable algorithm for detecting drug-induced QT-prolongation at risk of torsades de pointes (TdP) regardless of heart rate and T-wave morphology. 2021.
  • Alahmadi, A, Davies, A, Vigo, M, Jay, C. Pseudo-colouring an ECG enables lay people to detect QT-interval prolongation regardless of heart rate. 2020. In Preparation.
  • Alahmadi, A, Davies, A, Vigo, M, Jay, C. Can laypeople identify a drug-induced QT interval prolongation? A psychophysical and eye-tracking experiment examining the ability of nonexperts to interpret an ECG. 2019. In Preparation.

• Book Chapter

  • Alahmadi, A, Davies, A, Vigo, M, Dempsey, K, Jay, C. Human-Machine Perception of Complex Signal Data. 2022. In Preparation.

• Conference Proceedings (inc. Abstract)

  • Alahmadi, A, Davies, A, Royle, J, Vigo, M, Jay, C. Evaluating the impact of pseudo-colour and coordinate system on the detection of medication-induced ECG changes. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (pp. 1-13). 2019.