My name is Phi Nguyen Van (🇻🇳), and I'm passionate about computer vision and natural language processing with an emphasis on applications in medical imaging. I am PhD student on computer science at Technical University of Munich, Germany, focus on MRI-reconstruction, generative modelling and implicit representation. I completed my MSc in Computer Science at Vietnam National University in 2023, with research primarily focused on echocardiography analysis, machine learning in medical imaging, and conversational AI for e-commerce.
My academic journey has led me to specialize in areas within machine learning, particularly in medical imaging for tasks such as echocardiography analysis, segmentation, and synthesis. I am also interested in the development of conversational AI systems for automated processes in e-commerce.
You can reach me at:
- • phinv@vnu.edu.vn for academic and research inquiries
- • gungui98@gmail.com for other matters
Here, you'll also find my blog, where I document and share my research experiences and technical insights into various machine learning applications.
- [19/09/24] I received three prestigious PhD offers from the Technical University of Munich, National University of Singapore and Nanyang Technological University. I am excited to continue my research journey on medical imaging under the supervision of reknown Prof. Dr. Daniel Rueckert at the Technical University of Munich.
- [17/06/24] Our paper Training-Free Condition Video Diffusion Models for Single Frame Spatial-Semantic Echocardiogram Synthesis has been accepted to MICCAI 2024! This work demonstrates a new method for generating echocardiograms without additional training data, presented using 3D-Unet with Temporal Attention Layers.
- [12/04/24] Our paper Echocardiography Video Synthesis from End Diastolic Semantic Map via Diffusion Model has been accepted to ICASSP 2024! This research leverages diffusion models for video synthesis from echocardiogram semantic maps, introducing an innovative approach for single-segment cardiac video generation.
- [08/01/24] Our journal article Ensemble Learning of Myocardial Displacements for Myocardial Infarction Detection in Echocardiography has been published in Frontiers in Cardiovascular Medicine! This paper presents an ensemble method for myocardial infarction detection using echocardiography, enhancing diagnostic accuracy in myocardial tracking applications.
