Sophie Voisin

Dr. Sophie Voisin is a seasoned leader and expert in software engineering, data engineering, and computational science. She has been a valued member of Oak Ridge National Laboratory (ORNL) since 2010, when she joined as a Postdoctoral Research Associate with the Neutron Imaging Team at the Spallation Neutron Source (SNS). Across her career, Dr. Voisin has contributed to cutting-edge advancements in software engineering, data analytics, image processing, and high-performance computing, while establishing a reputation for leading innovative and collaborative efforts.

Dr. Voisin currently serves as Group Leader of the Data and Software Engineering Group, a position she formally took on in 2024. Under her leadership, the group focuses on building high-performance tools and solutions to address scientific challenges, with a focus on integrating data-driven methodologies and advancing software engineering practices to solve complex problems. Prior to her leadership roles, she served as a Software Engineer in various capacities at ORNL, where she developed robust software and geospatial solutions, supported augmented intelligence initiatives, and contributed to multi-modal analysis frameworks.

During her earlier career, Dr. Voisin played a key role in developing intelligent image and signal processing techniques for neutron imaging applications, as well as driving advancements in biomedical sciences. As a Postdoctoral Research Associate with the Biomedical Science & Engineering Center, she collaborated on projects integrating image analysis with eye-tracking data, aiding the creation of clinical decision support systems aimed at reducing medical errors. Her research successfully combined multi-modal image analytics with innovative software solutions to contribute to the broader goal of improving accuracy in visual examination tasks.

Dr. Voisin’s expertise spans software engineering, image understanding in 2D and 3D, geospatial data processing, machine learning, and high-performance computing. Her growing interest in data engineering has led her to explore novel techniques in data modeling, integration, and analysis, further expanding the impact of her contributions in computational science