Tanveer Syeda-Mahmood

Dr. Tanveer Syeda-Mahmood is an IBM Fellow and Global Imaging AI Leader in IBM Research.  Currently, her group is leading the charge on advancing multimodal and bioinspired AI. The goal is to advance the science of AI by drawing inspiration from computational models of various brain functions such as memory and learning and modeling the fusion of multiple modalities for information processing. The applications of the core technologies developed in the group are in various domains ranging from healthcare decision support, accelerated scientific discovery, to the building of next generation hybrid cloud data management and storage infrastructures. Among the projects in the team is one called Bioinspired Memories that is at the intersection area of AI, Neuroscience and Cloud technologies. It has healthcare applications for the memory-impaired individuals but also key to generating a new technological infrastructure for next generation storage systems modeled after human declarative memory.

Previously, she was the Chief Scientist/overall lead for the Medical Sieve Radiology Grand Challenge project in IBM Research, Almaden. This was  a large exploratory research project with global participation from many IBM Research Labs around the world including Almaden Labs in San Jose, CA, Haifa Research Labs in Israel and Melbourne Research Lab in Australia. The goal of this project was to develop automated radiology and cardiology assistants of the future that help clinicians in their decision making. The project has led to the introduction of AI in radiology through successful partnerships such as with RSNA (Radiological Society of North America) with the Eyes of Watson Exhibit (https://medcitynews.com/2016/12/ibm-watson-image-interpretation/) and the launch of the Watson Health Imaging business from the acquisition of Merge Healthcare. The first AI in radiology products from IBM Watson Health called Patient Synopsis (https://www.ibm.com/products/watson-imaging-patient-synopsis) and Clinical Review (https://www.ibm.com/products/watson-imaging-clinical-review) as well as the underlying platform are based on the technology piloted in the Medical Sieve and its feeder projects.

The work from her team has produced over 10 best paper awards at major healthcare forums such as MICCAI, AMIA, including the Homer Warner Award for outstanding contribution to the field of Biomedical Informatics at AMIA'2020. Their paper on multiplexed graph neural networks was a MICCAI Young Scientist Award Finalist at MICCAI 2022.

Dr. Syeda-Mahmood graduated from the MIT AI Lab in 1993 with a Ph.D in Computer Science. Prior to IBM, she worked as a Research Staff Member at Xerox Webster Research Center, Webster, NY. She joined IBM Almaden Research Center in 1998.

Prior to coming to IBM, Dr. Syeda-Mahmood 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. Currently, she is working on applications of content-based retrieval in healthcare and medical imaging. Over the past 30 years, her research interests have been in a variety of areas relating to artificial intelligence including computer vision, image and video databases, medical image analysis, bioinformatics, signal processing, document analysis, and distributed computing frameworks. She has over 250 refereed publications and over 120 patents filed.

Dr. Syeda-Mahmood is the General co-Chair of MICCAI 2023, the premier conference in medical imaging. She is also the Program co-Chair of IEEE ISBI 2022 to be held in Calcutta, India. She was the General Chair of the First IEEE International Conference on Healthcare Informatics, Imaging,and Systems Biology, San Jose, CA 2011. She was also the program co-chair of CVPR 2008.

Dr. Syeda-Mahmood is a Fellow of IEEE.  She is also the first IBMer to become an AIMBE Fellow and a MICCAI Fellow. She is also a member of IBM Academy of Technology. Dr. Syeda-Mahmood was declared Master Inventor in 2011, 2019, and 2022. She is the recipient of key awards including IBM Corporate Award 2015, Best of IBM Award 2015, 2016 and several outstanding innovation awards.

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