Krithika Iyer

Scientific Computing & Imaging Institute

Kahlert School of Computing

University of Utah

About Me

I'm currently a Ph.D. student at the Scientific Computing and Imaging Institute, University of Utah, working under the guidance of Dr. Shireen Elhabian. Prior to this, I earned my Bachelor of Engineering from Maharashtra Institute of Technology, University of Pune. After completing my undergraduate studies, I gained valuable experience as an Associate System Engineer at IBM Global Business Services.

My research focuses on machine learning, probabilistic modeling, deep learning, and statistical shape modeling. I am particularly passionate about exploring the applications of these areas in healthcare, aiming to contribute to advancements in diagnosis and treatment.

If you have any questions or are interested in collaborating, please don't hesitate to contact me.

Please visit my new website: http://iyerkrithika21.github.io/

Recent News

My new paper, 'Probabilistic 3D Correspondence Prediction from Sparse Unsegmented Images,' was accepted at the Machine Learning in Medical Imaging workshop held in conjunction with MICCAI 2024
SCorP was awarded the "Best Paper" award in the Medical Images and Computational Models category at MIUA 2024
My new paper, 'SCorP: Statistics-Informed Dense Correspondence Prediction Directly from Unsegmented Medical Images,' was accepted at the UK's 28th MIUA Conference 2024

My new paper, 'Mesh2SSM: From surface meshes to statistical shape models of anatomy,' was early accepted at MICCAI 2023

The paper I mentored, "ADASSM: Adversarial Data Augmentation in Statistical Shape Models From Images," was accepted at the ShapeMI workshop held in conjunction with MICCAI 2023.
Represented my lab in the undergraduate research symposium held at the University of Utah to introduce and encourage undergraduate students to pursue research.

My paper about the comprehensive analysis of shared boundary shape models, "Statistical Shape Modeling of Multi-Organ Anatomies with Shared Boundaries: A Data-Driven Approach," was published in Frontiers in Bioengineering and Biotechnology 10 (2022)
My paper, "Statistical Shape Modeling of Biventricular Anatomy with Shared Boundary," was accepted at the STACOM 2022 workshop held in conjunction with MICCAI 2022.
My paper "Relevance Encoding Networks: RENs" is available on archive.