The Centre for Brain Research (CBR) cordially invites you to attend the third lecture of the CBR Distinguished Visitor Program, generously supported by Ms Nirmala Govindan Pullur. 

 

Title: Multimodal Fusion for Disease Understanding 

 

Speaker: Dr Tanveer Syeda-Mahmood, IBM Fellow and Adjunct Professor, Department of Biomedical Data Science, Stanford University, USA  

 

Date: 12 January 2026, Monday
Time: 3– 4 PM, followed by high tea
Venue: CBR Auditorium  

 

 Abstract:

Understanding the human brain—arguably the most complex biological system—demands integrative frameworks that bridge molecular, structural, functional, and clinical levels of observation. This in turn requires integrating diverse data types including genomic, neuroimaging, and clinical data, which has traditionally been addressed using early, mid, or late fusion methods. Through long-term academic–industrial collaborations, Dr Syeda-Mahmood’s group has been developing novel neural architectures tailored for multimodal fusion. They have applied these architectures to model fusion across diverse diseases ranging from cancer and cardiac diseases to neurodegenerative disorders such as Alzheimer’s disease. Dr Syeda-Mahmood will present a range of approaches, from statistical fusion methods such as sparse canonical correlation analysis to generalized neural fusion models based on multiplexed and multi-layer graph neural networks. She will highlight the translational impact of these methods through a recent study that identified 23 genes associated with cardiac morphology, illustrating the broader potential of multimodal fusion to drive biologically meaningful discovery in brain research and precision neuroscience.  

 

Speaker’s profile:

Dr Tanveer Syeda-Mahmood is an IBM Fellow and an Adjunct Professor in the Department of Biomedical Data Science at Stanford University. As a worldwide expert in healthcare imaging, her research career has centered on foundational and translational multimodal healthcare AI—integrating clinical, imaging, genomic, and laboratory data to advance diagnostic decision-support, predictive modeling, and patient-outcome analysis. At IBM, she led major multi-institutional initiatives such as Medical Sieve and AALIM, overseeing the development of multimodal diagnostic decision-support systems and guiding interdisciplinary teams from exploratory research through clinical validation, productization, and deployment. Collectively, these efforts have resulted in more than 250 peer-reviewed publications, 180 patents, multiple best-paper awards, widely used datasets, and several FDA-cleared products. Through sustained contributions across academia and industry, her leadership continues to influence the future of intelligent healthcare systems worldwide. 

 

Dr Tanveer Syeda-Mahmood graduated with a PhD from the MIT Artificial Intelligence Lab in 1993. Prior to joining IBM, she led the image indexing program at Xerox Research and was one of the early originators of the field of content-based image and video retrieval. Dr Syeda-Mahmood has chaired many international conferences over the years including MICCAI (2023), IEEE ISBI (2022), HISB (2011), and IEEE CVPR (2008). She is a Fellow of IEEE, AIMBE (American Institute for Medical and Biological Engineering), AAIA (Asian Association of Artificial Intelligence), and MICCAI (Medical Imaging and Computer-Assisted Intervention Society). She recently received the 2025 IEEE EMBS Professional Career Achievement Award for outstanding technical achievement and leadership in multimodal decision support with lasting impact to academia/industry in multimodal healthcare AI.

 

This is an in-person event; registration is not required for participation.  

 

—- ALL ARE WELCOME—-

Previous editions of the CBR DVP Lecture were delivered by Prof. Rema Raman and Prof. Barbara B. Bendlin.

 

=======================