Dr. Khalid Malik is a Professor in the College of Innovation and Technology at the University of Michigan–Flint. He earned his Ph.D. from the Tokyo Institute of Technology in Japan in 2010. Before joining academia, he spent more than eight years conducting large-scale industrial research and development at Sanyo Electric and DTS Inc. in Japan, where he gained extensive experience in applied research and technology innovation within the corporate sector.

Dr. Malik’s research focuses on the development of intelligent clinical decision support systems, with particular expertise in neuro-symbolic artificial intelligence, medical image analytics, and multimodal data analysis. His broader research interests include trustworthy AI, neurosymbolic approaches to the clinical management of neurological disorders, deepfake detection, and cybersecurity.

His work has been supported by numerous national and international funding agencies and organizations, including the National Science Foundation (NSF), the U.S. Department of Energy (DOE), the U.S. Army, MTRAC, and the Brain Aneurysm Foundation. Through his research, Dr. Malik seeks to advance the development of innovative, trustworthy AI technologies that improve clinical decision-making and patient care.

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What led you to become involved with brain aneurysm research?
My work in brain aneurysm research traces back to 2015, when I was involved in a data integration project with Henry Ford Health. It was during this project that I became acutely aware of the difficulties neurosurgeons encounter in predicting aneurysm rupture risk, particularly in reaching consensus for patients presenting with borderline cases. This experience became the driving force behind my efforts to develop AI-based clinical decision support tools capable of helping physicians assess rupture risk with greater accuracy and consistency.

In the simplest terms, what is the purpose of your project?
The objective of our project is to develop an artificial intelligence system that supports neurosurgeons in making more accurate and timely treatment decisions for patients with brain aneurysms. By integrating brain imaging, electronic health records, and computational fluid dynamics (CFD) within a neuro-symbolic AI framework, the system generates individualized estimates of aneurysm rupture risk while offering transparent, explainable recommendations to guide clinical decision-making. Ultimately, this work seeks to improve patient outcomes, reduce unnecessary procedures, strengthen physician decision-making, and advance medical education.

In the simplest terms, what do you hope will change through your research findings?
We hope our findings will provide the first ever biological data on how vaping and synthetic nicotine products influence brain aneurysm formation and rupture. These results could help guide public health recommendations and policies, inform patients and healthcare providers about potential risks, and lay the foundation for future therapies and prevention strategieI hope our research will help doctors better predict when a brain aneurysm is likely to grow or rupture, so patients can get the right treatment at the right time. We’re building AI tools that doctors can trust and understand — not a “black box” — by combining medical imaging, patient health records, and advanced reasoning methods. Our goal is simple: help catch dangerous aneurysms before they rupture, avoid unnecessary surgeries for patients who don’t need them, and ultimately give patients better outcomes and better care..

Why is the funding you are receiving through the Brain Aneurysm Foundation so important?
Support from the Brain Aneurysm Foundation is essential to our work, as it allows us to pursue research that would otherwise be difficult to undertake given the demands of large-scale imaging datasets, electronic health records, and multidisciplinary collaboration. This funding enables our team to develop advanced AI methods that draw on multimodal imaging and clinical data, to investigate aneurysm growth and rupture prediction, and to share the resulting tools and datasets with the broader research community. Just as importantly, it lays the groundwork for future large-scale research supported by agencies such as the NIH, NSF, and MTRAC, helping to accelerate progress toward more effective diagnosis and treatment of brain aneurysms.