Invited Speakers

Speaker: Eran Hornstein, Professor, Weizmann institute of science

Speaker Bio: The Hornstein laboratory has pioneered research on RNA biology in ALS for 15 years, and has transformed into a machine learning–driven research hub, and now lead the integration of computational biology, AI, and advanced imaging into neurodegeneration research. With the unique expertise at the interface of neuroscience and data science, we are positioned to deliver transformative insights into the mechanisms of motor neuron death and to establish new therapeutic avenues for ALS and related disorders.

Speaker: Olivier Gevaert, Associate Professor, Stanford University

Speaker Bio: Dr. Olivier Gevaert is an associate professor at Stanford University focusing on developing machine-learning methods for biomedical decision support from multi-scale data. He is an electrical engineer by training with additional training in artificial intelligence, and a PhD in bioinformatics at the University of Leuven, Belgium. He continued his work as a postdoc in radiology at Stanford and then established his lab in the department of medicine in biomedical informatics. The Gevaert lab focuses on multi-scale biomedical data fusion primarily in oncology and neuroscience. The lab develops machine learning methods including Bayesian, kernel methods, regularized regression and deep learning to integrate molecular data or omics. The lab also investigates linking omics data with cellular and tissue data in the context of computational pathology, imaging genomics & radiogenomics. Dr. Gevaert joined BMIR in 2015 as an Assistant Professor of Medicine.
Speaker: Daguang Xu, Research Manager, NVIDIA.

Speaker Bio: Daguang Xu is now a research manager at AI-Infra of NVIDIA. He is leading a research team in healthcare AI, focusing on developing world-class machine learning and deep learning-based methods to solve the challenging problems in medical domain. His current research interest includes but not limited to medical imaging analysis, EHR analysis, computer aided diagnosis, deep learning, pattern recognition and computer vision, etc. He has published 90+ papers on top journals and conferences and has ~50 granted or in-application patents. His team is the main developer of open source software (OSS) MONAI (https://github.com/project-monai) and NVIDIA Flare (https://github.com/nvidia/nvflare).
Speaker: Vivek Gopal Ramaswamy, Senior Software Engineer, UCSF Gladstone Institutes.

Speaker Bio: Vivek Gopal Ramaswamy is a Senior Software Engineer at the Gladstone Institutes, where he develops next-generation AI systems at the intersection of computer vision, robotics and biomedical research. His work focuses on building biology-specific foundational models that classify, track, and predict cell fate, and on creating generative-AI–based vision tools to uncover novel cellular and brain-tissue phenotypes. By integrating these phenotypes with transcriptomic data, his research advances multimodal foundation models for precision medicine. He has expertise in designing intelligent imaging systems that integrate AI with robotic control, precision motor calibration, and adaptive feedback to enable autonomous and dynamic experimentation. He also leads efforts in scalable image-analysis pipelines capable of processing thousands of whole-slide images using distributed frameworks such as Docker, Kafka, and Kubernetes. His deep learning research spans multi-scale CNNs, Vision Transformers, and multimodal foundation models trained with techniques such as QLoRA and contrastive learning. Across his work, Vivek bridges AI, imaging, and biology to build intelligent, scalable systems accelerating discovery in neuroscience and disease pathology.