Jeya Maria Jose

Hi!, I am a 3rd year Ph.D. student at Johns Hopkins University, in the Department of Electrical and Computer Engineering where I am working in Vision and Image Understanding Lab , advised by Dr. Vishal M Patel .

My research focus lies within the intersection of Computer Vision, Machine Learning, and Medical Imaging. More specifically, I work on image/3D segmentation, image enhancement, image-to-image translation for large-scale vision and medical imaging tasks.

I interned at Adobe in the summer of 2021 where I worked on image harmonization problems. During my undergrad days, I worked at the Medical Mechatronics Lab in National University of Singapore on medical image segmentation and survival prediction problems. I graduated from NIT Trichy, India in 2019 with my Bachelor's degree majoring in Instrumentation and Control.

Email / CV / Google Scholar / Github / LinkedIn

News

June, 2021 - 2 papers accepted at MICCAI 2021 .
May, 2021 - Joined Adobe as a Research Intern.
May, 2021 - 1 paper accepted at ICIP 2021 .
November, 2020 - 1 paper accepted in IEEE Journal of Selected Topics in Signal Processing .
November, 2020 - 1 paper accepted at WACV 2021 .
July, 2020 - Recipient of MICCAI Student Travel Award for the year 2020.
May, 2020 - 1 paper accepted in the IEEE Journal of Selected Topics in Signal Processing .
May, 2020 - 1 paper accepted at MICCAI 2020 (Early Acceptance).

Best Student Paper award

CVIP 2019

August, 2019 - Joined Johns Hopkins University for my Ph.D with ECE fellowship.

Teaching

Teaching Assistant: Deep Learning EN.520.638.01.SP21, Spring 2021, Johns Hopkins University

Research

	R2D: Learning Shadow Removal to Enhance Fine-Context Shadow Detection arXiv Preprint 2021 Jeya Maria Jose, Christina Chen, and Vishal M. Patel Paper
	SPIN Road Mapper: Extracting Roads from Aerial Images via Spatial and Interaction Space Graph Reasoning for Autonomous Driving arXiv Preprint (under review at ICRA 2022) Chaminda Bandara, Jeya Maria Jose, and Vishal M. Patel Paper \| Code
	Medical Transformer: Gated Axial-Attention for Medical Image Segmentation MICCAI 2021 Jeya Maria Jose, Poojan Oza, Ilker Hacihaliloglu, Vishal M. Patel Paper \| Code
	Over-and-Under Complete Convolutional RNN for MRI Reconstruction MICCAI 2021 Pengfei Guo, Jeya Maria Jose, Puyang Wang, Jinyuan Zhou,Shanshan Jiang, Vishal M. Patel Paper \| Code
	KiU-Net: Overcomplete Convolutional Architectures for Biomedical Image and Volumetric Segmentation Preprint, Under Review at IEEE TMI Jeya Maria Jose, Vishwanath Sindagi, Ilker Hacihaliloglu, Vishal M. Patel Paper \| Code \| Project
	Overcomplete Deep Subspace Clustering Networks WACV 2021 Jeya Maria Jose and Vishal M. Patel Paper \| Code
	Overcomplete Representations against Adversarial Videos ICIP 2021 Shao-Yuan Lo, Jeya Maria Jose, and Vishal M. Patel Paper
	Exploring Overcomplete Representations for Single Image Deraining using CNNs IEEE Journal of Selected Topics in Signal Processing Rajeev Yasarla, Jeya Maria Jose, Vishal M. Patel *equal contribution Paper \| Code
	KiU-Net: Towards Accurate Segmentation of Biomedical Images using Over-complete Representations MICCAI 2020 Jeya Maria Jose, Vishwanath Sindagi, Ilker Hacihaliloglu, Vishal M. Patel Paper \| Code \| Project
	Learning to Segment Brain Anatomy from 2D Ultrasound with Less Data IEEE Journal of Selected Topics in Signal Processing Jeya Maria Jose, Rajeev Yasarla, Puyang Wang, Ilker Hacihaliloglu, Vishal M. Patel Paper
	Tackling Multiple Visual Artifacts: Blind Image Restoration using Conditional Adversarial Networks CVIP 2019 (Best Student Paper Award) M Anand, A Ashwin Natraj, Jeya Maria Jose, K Subramanian, S Deivalakshmi Paper \| Code
	Brain Tumor Segmentation and Survival Prediction using 3D Attention UNet BraTS, MICCAI Workshop 2019 Mobarakol Islam, Vibashan VS, Jeya Maria Jose, Navodini Wijethilake, Uppal Utkarsh, Hongliang Ren Paper
	BP-Net: Cuff-less Blood Pressure Prediction using Convolutional and Long Short-term Memory Networks from ECG and PPG signals Jeya Maria Jose, M Anand, Geerthy T, M Siddarth, K Subramanian, G Uma Paper (Feature Analysis using ML) \| Code \| Paper (BP-Net) - Coming Soon
	Glioma Prognosis: Segmentation of the Tumor and Survival Prediction using Shape, Geometric and Clinical Information BraTS, MICCAI Workshop 2018 Mobarakol Islam, Jeya Maria Jose, Hongliang Ren Paper \| Poster