Satyananda Kashyap


Satyananda Kashyap


Staff Scientist


IBM Research - Almaden San Jose, CA USA


I am a staff scientist at IBM Research. I graduated with a PhD from the University of Iowa, where I worked on developing segmentation and quantification to study knee osteoarthritis using graph theory and machine learning.  

At IBM Research, here are the highlights of some of the projects I have worked on:

  • Worked on exploring the intersection of vision, language, and neuroscience, aiming to revolutionize storage systems with integrated intelligence. The hippocampal memory indexing and storage system inspires the work on next-generation computational storage. Developed a prototype based on Modern Hopfield Networks, focusing on enhancing exponential memory storage capacities to achieve computational feasibility at practical scales.
  • Led the development of AI-enhanced Intravascular Ultrasound (IVUS) systems for Boston Scientific. I coordinated and led a 3-way team of five researchers from IBM Research, Boston Scientific, and MIT to innovate stent placement diagnostics. Pioneered AI methodologies that significantly improved stent placement accuracy, culminating in successful prototypes and publications. My contributions were vital to advancing medical interventions and patient care in biomedical engineering.
  • Worked on algorithm development for MicroVention, focusing on enhancing the understanding of device effectiveness in patients. Coordinated and developed AI-based algorithms for improved stent placement analysis in neurovascular aneurysms, contributing to advancements in stent sizing precision.
  • Contributed to pioneering AI applications in radiology at IBM, leading efforts in automated chest radiograph analysis, development of reusable assets for Watson Health Imaging, and creating a deep learning system for radiograph quality assessment. These contributions were instrumental in developing critical assets and tools for IBM, directly contributing to 30M Euro in revenue through enhanced data analytics and deep learning capabilities.

My research interests include leveraging multi-modal and multi-dimensional data to enable the creation of robust, scalable AI solutions across various sectors.

Please check out my Google Scholar Profile for the most up-to-date publications:  Google Scholar



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