Dr. Amir Koushyar Ziabari is a Senior R&D Staff Data Scientist at Oak Ridge National Laboratory (ORNL), working in the Multimodal Sensor Analytics group under the Electrification and Energy Infrastructure Division. His career spans advanced research in physics-informed computational imaging, signal processing, and machine learning applications for scientific imaging. Education: PhD in Electrical and Computer Engineering, Purdue University (2012-2016) MS in Electrical and Computer Engineering, University of California Santa Cruz (2009-2012) MS in Electrical and Computer Engineering, Sharif University of Technology (2006-2008) BS in Electrical and Computer Engineering, Amirkabir University of Technology (2001-2005) Dr. Ziabari's research focuses on "data science for science", combining data-driven and physics-based methodologies to develop computational imaging and machine learning algorithms. His work addresses image reconstruction, segmentation, and classification challenges across domains like advanced manufacturing, medical imaging, nuclear materials, and materials science. Key innovations include the SIMURGH software for X-ray CT reconstruction and diffusiveINR for energy-efficient foundation models. Recent publication trends show expertise in multi-modal imaging for additive manufacturing, thermal transport analysis at nanoscale, and physics-informed neural networks. His scientific awards include the R&D 100 Finalist, IEEE Senior Member (2022), IEEE Computational Imaging Technical Committee Member (2023), and multiple best paper recognitions. He has secured $3.5M+ in funding as PI/Co-PI and holds patents in tomographic reconstruction and thermal imaging. Dr. Ziabari contributes to professional societies (IEEE, ASTM, OSA), organizes symposia on additive manufacturing imaging, and mentors postdocs to build inclusive research environments. His collaborations with ZEISS, INL, and NIST demonstrate his ability to bridge academic research with industrial applications.
