We are pleased to welcome visiting Associate Professor of Computer Science Dr Mai Alzamel based at King Saud University who will deliver the seminar "Listening to the Crowd: Using Online Search Data and Recurrent Neural Networks to Predict Infectious Diseases" followed by a short workshop.

This is a hybrid seminar but we encourage attendance in-person.

• Date & time: Tuesday 19 January at 1pm
• Venue: 6th floor Seminar Room, Addison House, Guy's campus
• Format: hybrid

Join the seminar online

Seminar (25 minutes):

Listening to the Crowd: Using Online Search Data and Recurrent Neural Networks to Predict Infectious Diseases

This seminar explores how artificial intelligence can turn everyday online search behaviour into early warning signals for infectious disease outbreaks. It shows how recurrent neural networks (RNNs), including LSTM, BiLSTM and GRU, can learn from search trends and past case records to forecast infections and flag unusual increases before they escalate. The session highlights what this means for public health, from earlier detection to faster, better-informed decisions.

Workshop (25 minutes):

Search Signals: Extracting and Analyzing Google Trends Data for Health Surveillance

This session shows participants how to turn Google Trends into a usable health research dataset. It covers how relative search volume works, how to choose and refine keywords, how to extract data by region and time period, and how to prepare it for analysis alongside health statistics. It builds directly on the seminar by covering the data collection and preparation that come before any forecasting model. No advanced programming knowledge is required.

The two activities are closely related: the seminar presents the forecasting approach, and the workshop covers the data extraction and analysis that support it.

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Biography:

Dr Mai Alzamel is an Associate Professor of Computer Science at King Saud University, Director of the Research Centre at the College of Computer and Information Sciences (CCIS), and a Visiting Research Fellow in Population Health Sciences at King’s College London. Her expertise is in bioinformatics and digital health, focusing on forecasting, data-driven decision-making and anomaly detection, turning complex health and biological data into actionable insights that improve outcomes and strengthen system reliability and data security.

Dr Alzamel completed her PhD in Algorithms and Data Analysis at King’s College London and her MSc in Advanced Computer Science at the University of Sheffield, and previously worked as a Research Fellow at UCL on AI for health in collaboration with Google.