Self-Supervised Learning paper is in MedIA!
Congrats to Ke and Li for their recent paper in MedIA! This is a way to go for Self-Supervised Learning in medical imaging .
Our fast diffusion paper is accepted in NeurIPs!
Congrats to Yanwu for his second NeurIPs paper! We are going to have more development in this direction soon!
Our paper about shortcut learning is accepted to TMLR!
Congratulations to Niahl for his first journal paper in TMLR! The pre-print is available here and the final camera-ready, code and video will be out soon!
Two early acceptances in MICCAI 2023!
Congratulations to Shantanu and Matthew for their first papers in MICCAI, both early accept! I am very proud of them. Links to the paper and code are coming out soon.
Imaging-Transcriptomics paper is accept to the COPD journal!
We use DL techniques to define new COPD axes using CT imaging and gene expression data. Congratulation to Junxiang for his paper in the COPD Journal! The pre-print is here!
One paper is accepted to ICML 23!
Congratulations to Shantanu and Ke! Their first paper is accepted to ICML 2023. Find the paper, code, and more on the project page.
One paper is accepted to WACV!
Congrats to Sumedha and Nihal for their paper in WACV! They showed how our previous work on Counterfactual Explainer could be used to fix an overconfident BlackBox classifier!
Yingci’s manuscript is accepted to the oral oncology!
Happy for Yingci! Her manuscript has been accepted to Oral Oncology!
Counterfactual blackbox explanation paper is accepted to MedIA!
Congratulation to Sumedha and her team! Her manuscript on counterfactual model explanation paper is finally accepted for a special issue in MedIA about XAI! The very initial pre-print is here; the full version is coming out soon! I am thankful to Motahare for her amazing contribution to the paper.
An efficient 3D GANs is finally out!
Congratulations to Li and his team for their big paper in IEEE JBHI that makes volumetric GANs possible for high-resolution medical images. They made a huge effort, and I am proud of them!
Yanwu’s Paper about Adversarial Spatial Perturbation is accepted to CVPR!
Congratulations to Yanwu for his CVPR paper! His method uses the Maximal Spatial Perturbation idea that significantly enhances image-to-image translation!
Our paper about Knowledge Distillation is accepted to AAAI 21!
Congratulations to Ardavan, Li! Their paper is accepted to AAAI 21! The link and code will be posted soon.
Our collaborative work with MIT is accepted to NeurIPS!
Our collaborative work with Suvrit’s group about shortcuts in Self-supervised Learning is accepted to NeurIPS! Congratulations to Joshua, Li, and Ke!
Our paper is accepted to Radiology AI!
Congratulations to Brian! His paper about estimating liver elastography is accepted to the Radiology AI journal!
Two papers are accepted to MICCAI 2021!
Two papers are accepted in the MICCAI 2021! Congratulations to Sumedha and Rohit!
Invited for Senior Vice Chancellor’s Research Seminar!
I’m very honored to give Senior Vice Chancellor’s Research Seminar today. I’ll present research done by brilliant students and postdocs at BatmanLab!
One Early Acceptance to MICCAI!
I am excited for Rohit Jena! His paper received Early Acceptance in MICCAI 2021! Pre-print is here!
One paper is accepted to AAAI 2021!
Congratulations to Li Sun and Ke Yu for their joint paper in AAAI 2021! Their paper show how to incorporate anatomically relevant context to self-supervised learning!
Ke’s journal is accepted to ACM JCIM!
Congratulations to Ke Yu! His paper is accepted to the Journal of Chemical Information and Modeling. The method integrates drug taxonomy with chemical structure and enables localizing novel molecules in the context of the clinically approved drugs.
Our paper is accepted to the Oxford Bioinformatics Journal!
Congratulations to Mingming Gong! His awesome paper (Preprint) is accepted to the Oxford Bioinformatics Journal! Fundamental and rigorous research for inference of statical independence which uses unpaired data!
Giving talk at the Oxford ML Summer School!
I am excited to present at the Oxford ML Summer School (OxML 2020)! I will talk about various applications and challenges of Machine Learning in Medical Imaging!
Giving a talk in DeepMind about XAI for Healthcare!
Excited to give a talk in DeepMind about Real-World Applications of Explainable Models in Medical Imaging!
Giving a talk at SAP Machine Learning Retreat!
Excited to give a talk about our recent NeurIPS paper at SAP Research Retreat!
Our paper is accepted to NeurIPs as a spotlight paper!
Our manuscript is accepted to NeurIPS 2019 (Spotlight 2.4%)! Big congrats to Mingming and Yanwu! The code is in this repo.
Mingming will be Lecturer at Stat Department in Melbourne University!
First BatmanLab alumni! Congratulation to Mingming for accepting a new position as a lecturer (Assistant Professor) at the School of Mathematics and Statistics at the University of Melbourne!
We are awarded a large R01 ($2.8M with indirect) to develop an approach to integrate Radiomic data with Genetic for characterization of Chronic Obstructive Pulmonary Disease (COPD).
Congratulations to Sumedha for the Early Acceptance of her first paper to MICCAI!
We are awarded $390K to develop methods for multimodal learning in collaboration with SAP research.
Congratulations to Mingming Gong–two CVPR papers have been accepted!