AiNed Fellowship Grant for Aaqib Saeed

March 21, 2024

With this fellowship, Dr. Aaqib Saeed will address the challenges of harnessing decentralized audio data using artificial intelligence (AI) in order to generate clinically actionable insights.

aaqib saeed

The sounds that permeate our daily lives – from speech and breathing patterns to heartbeat rhythms – contain a wealth of physiological information that could reveal valuable insights into human health and well-being, such as heart and pulmonary conditions. What’s more, audio signals that capture these sounds can now easily be acquired from consumer devices equipped with multiple microphones, like smart speakers, smartphones and other Internet of Things (IoT) devices. This is a field in which Dr. Aaqib Saeed will combine his longstanding research interests in human-centric AI, self-supervised learning, federated learning and audio understanding into applications that improve personal health – something he intends to pursue as the winner of the AiNed Fellowship Grant.

 

I am thrilled and honored to be selected as an AiNed Fellowship Grant recipient. This prestigious award will catalyze my mission to advance decentralized AI for revolutionizing audio-based health monitoring. By leveraging the power of federated learning, I aim to transform sounds into vital clinical insights while safeguarding user privacy. My team and I are eager to push the boundaries of health diagnostics and lead the charge towards a new era of collaborative and trustworthy AI.

Privacy and potential

In the ‘Private Ears, Shared Insights: Scaling Clinical Audio Understanding with Federated Learning’ project, Dr. Saeed will develop fundamental decentralized AI techniques that can systematically analyze distributed audio data and build data-driven models capable of attaining clinical precision. Until now, the development of such techniques has been hindered by little to no access to audio due to the private nature of the data. The project will therefore focus on safe and fair results that address regulatory barriers (such as the EU AI Act and the General Date Protection Regulation) and, most critically, ensure the privacy of users. Ultimately, this will advance collaborative AI in a real-world context to tackle health-related challenges at a national scale.

Passing on experience

Through the AiNed Fellowship grants of the National Growth Fund program, the Dutch Research Council aims to attract AI talent to Dutch academic research organizations in view of the international competition for AI talent. Dr. Saeed is one such talent, with experience ranging from work as a Research Scientist in AI for Personal Health at Philips Research, a position as a Visiting Industrial Fellow at the University of Cambridge, and multiple internships at Google Research with a focus on self-supervised learning and machine intelligence. Today, Dr. Saeed is an Assistant Professor in the Department of Industrial Design with a secondary appointment in the Department of Mathematics and Computer Science at TU/e, where he also received his PhD cum-laude in Computer Science in 2021. With the awarding of the AiNed Fellowship Grant, Dr. Saeed will be able to establish his own research team of five to six PhDs and postdocs, providing an excellent opportunity to pass on his knowledge and experience to current students in the field of decentralized AI or related domains.

About the AiNed Fellowship grants

AiNed Fellowship grants help Dutch academic knowledge institutions to attract AI talents, who are usually able to choose between several competitive job offers. The focus is on exceptional AI talents who focus on the challenges that make up the AI Research Agenda for the Netherlands (AIREA-NL) and who can be deployed in AI disciplines ranging from technology to the social sciences and humanities. AiNed Fellowship grants therefore increase the number of PhDs and postdoc researchers at Dutch academic knowledge institutions and, in doing so, consolidate the AI knowledge and education base in the Netherlands and strengthen the national AI ecosystem.