Keynotes

Dr. Krithika Iyer is a Postdoctoral Research Fellow at the Sheikh Zayed Institute for Pediatric Surgical Innovation at Children's National Hospital in Washington, D.C., where she works in the Pediatric Accelerated Intelligence (PAI) Lab under the mentorship of Dr. Marius George Linguraru. Her research develops machine learning and shape analysis methods for medical imaging, with a current focus on pediatric neuroimaging including MRI-to-CT synthesis for infant skull visualization, super-resolution for ultra-low-field brain MRI, and cognitive outcome prediction to improve access in low-resource settings.

She earned her Ph.D. from the Scientific Computing and Imaging Institute at the University of Utah, where she was advised by Dr. Shireen Elhabian. Dr. Iyer's work has contributed significantly to advancing shape analysis from complex anatomical data. She has developed methods such as Mesh2SSM and Mesh2SSM++, frameworks for learning statistical shape models from anatomical surface meshes, and ScorP, a statistics-informed dense correspondence prediction framework for unsegmented medical images. More recently, she developed LEDA, a Log-Euclidean Diffeomorphic Autoencoder for efficient statistical analysis of anatomical deformations, and MORPH-LER, a population-aware diffeomorphic image registration framework using Log-Euclidean regularization for anatomically consistent morphological analysis.

Her research has appeared in leading venues including MICCAI, IPMI, ISBI, MIUA, Medical Image Analysis, Frontiers in Bioengineering and Biotechnology, and ShapeMI workshop. She received the Best Paper Award in Medical Images and Computational Models at MIUA 2024 and has actively contributed to the medical imaging community through conference reviewing and academic leadership roles.

Dr. Ferrante completed his PhD in Computer Science at Université Paris-Saclay and INRIA (Paris, France), carried out postdoctoral research at Imperial College London (UK), and earned a Systems Engineering degree from UNICEN University (Tandil, Argentina). He has also been a visiting PhD student at Stanford University, a Fulbright Visiting Researcher at Harvard Medical School in Boston, Invited Professor at Université Paris-Saclay, France, and Von Humboldt Visiting Researcher at the Technical University of Munich.

His research interests span machine learning for computer vision and NLP, with a focus on fairness and robustness in biomedical imaging. His papers have been published in top tier conferences like MICCAI, ICLR, ECCV, ICCV, ACL and journals like PNAS, Nature Machine Intelligence, Nature Communications, MedIA, IEEE TMI, The Lancet Digital Health, the BMJ among others.

He is currently a Staff Research Scientist at the Institute of Computer Sciences of University of Buenos Aires and Argentina’s National Research Council (CONICET), where he leads a group at the Applied Artificial Intelligence Lab. His research has been recognized with several awards, such as the Google Award for Inclusion Research, the Distinguished International Associate Award from the UK Royal Academy of Engineering, and the Friederich Wilhelm Bessel Award from the Von Humboldt Foundation, among others.