About me
I am a Postdoctoral Scientist at Johnson & Johnson, working at the intersection of multi-modal AI and drug discovery.
I recently defended my PhD at Queen Mary University of London, where I worked on Cardiac Image Segmentation using deep learning. My PhD was supervised by Professor Greg Slabaugh, Professor Martin Benning, Dr. Caroline Roney, and Dr. Muhammad Asad.
My PhD was funded by the mini-CTD program at Queen Mary University of London, with industrial partners, including NVIDIA Corporation, Circle Cardiovascular Imaging, and Conavi Medical. I was also part of Queen Mary’s Digital Environment Research Institute.
I was also a Research Intern at KeenAI. My work focused on developing AI-based approaches to segment steelwork and rust accurately in transmission tower images. The work aimed to predict steelwork and estimate rust proportions across various backgrounds.
The image below summarizes my PhD research journey (Deep learning-based Cardiac Image Segmentation ), April 2022 - May 2025.
Previously, I was fortunate to work at the University of Cambridge with Liliana Janik and Hatice Gunes at Affective Intelligence & Robotics Lab. I also had the privilege to work at Core Research Institute of Intelligent Robots, where I completed my Master’s Degree under the supervision of Hyongsuk Kim.
Research Interests
- Computer Vision, Deep Learning, Pattern Recognition
- Application of AI in healthcare, Medical Image Segmentation, Precision Agriculture
- Multi-modal AI, Compositional AI, Vision-Language Modeling
Honors and Awards
- ISBI 2024 Student Travel Grant
- MICCAI LAScarQS 2022 Challenge Best Paper Award
- Queen Mary PhD Studentship Award
- Brain Korea Master Scholarship Award
- CERN 2017 Summer Student Award
- Bachelor’s Degree Final Year Best Project Award
- Magna Cum Laude Highest Academic Excellence Award (Bachelor Degree)
Site Credits
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