Jeya Maria Jose

Jeya Maria Jose

I am a postdoctoral researcher at Stanford University, working with Andrew Ng and Curtis Langlotz. I obtained my Ph.D. and M.S from Johns Hopkins University advised by Vishal M Patel . I study Computer Vision, Machine Learning, and AI.

I co-lead the AI for Healthcare bootcamp at Stanford.

My research aims to overcome the challenges that arise when translating machine learning models to practical applications for healthcare and engineering sectors. I have worked on several topics like designing effective deep architectures, model adaptability to changing environments, role of data and annotations, multi-modal learning and taming large models for computer vision and healthcare tasks.

I am glad to be recognized as an Amazon fellow . I also had the opportunity to work with research teams at Google, NVIDIA , and Adobe during my Ph.D.

Previously, I received my Bachelor's from NIT Trichy, India in 2019 while also working closely with National University of Singapore.

Email / CV / Google Scholar / Github / LinkedIn

News

October, 2023 - 1 paper accepted at WACV 2024.
August, 2023 - Invited Talk at MedAI Group. Link for Slides, Video.
May, 2023 - Invited Talk at Amazon. Link for Slides.
April, 2023 - Defended my Ph.D.!! Link for Slides.
March, 2023 - 1 paper accepted at MIDL 2023.
February, 2023 - 1 paper accepted at CVPR 2023.
January, 2023 - 1 paper accepted at ICLR 2023.
October, 2022 - Won the Amazon Research Fellowship.
September, 2022 - Received Young Scientist Impact Award - Finalist at MICCAI 2022.
August, 2022 - 1 paper accepted at WACV 2023.
August, 2022 - Received NIH MICCAI Award 2022, which rewards early career scientists.
June, 2022 - 3 papers accepted at MICCAI 2022.
June, 2022 - Invited Talk at IEEE SPS Summer School on AI in Healthcare.
May, 2022 - Awarded Outstanding Automation Paper Finalist (top 3) at ICRA 2022.
March, 2022 - Presented a Tutorial at ISBI 2022 on medical image segmentation.
March, 2022 - 1 paper accepted at CVPR 2022.
January, 2022 - 1 paper accepted at ICRA 2022.
November, 2021 - 1 paper accepted in IEEE Transactions on Medical Imaging.
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 2020, which rewards first author students of the highest-quality MICCAI papers.
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.SP23, Spring 2023, Johns Hopkins University

Teaching Assistant: Deep Learning EN.520.638.01.SP22, Spring 2022, Johns Hopkins University

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

Research

Self-Supervised Denoising Transformer with Gaussian Process

WACV 2024

Rajeev Yasarla, Jeya Maria Jose , Vishwanath Sindagi, Vishal M. Patel

Paper

Disruptive Autoencoders: Leveraging Low-level features for 3D Medical Image Pre-training

Preprint 2023

Jeya Maria Jose , Yucheng Tang, Dong Yang, Ziyue Xu, Can Zhao, Wenqi Li, Vishal M. Patel, Bennett Landman, Daguang Xu, Yufan He and Vishwesh Nath

Paper | Weights | Pre-training Code

	ReBotNet: Fast Real-time Video Enhancement Preprint 2023 Jeya Maria Jose , Rahul Garg, Andeep Toor, Xin Tong, Weijuan Xi, Andreas Lugmayr, Vishal M. Patel and Anne Menini Paper \| Project
	CLIP Goes 3D: Leveraging Prompt Tuning for Language-Grounded 3D Recognition OpenSUN3D, ICCV 2023 Deepti Hegde, Jeya Maria Jose , and Vishal M. Patel *equal contribution Paper \| Code \| Project
	On-the-Fly Test-time Adaptation for Medical Image Segmentation MIDL 2023 Jeya Maria Jose , Pengfei Guo, Vibashan VS, and Vishal M. Patel Paper \| Code
	Ambiguous Medical Image Segmentation using Diffusion Models CVPR 2023 Aimon Rahman, Jeya Maria Jose, Ilker H, and Vishal M. Patel Paper \| Code \| Project
	Interactive Portrait Harmonization ICLR 2023 Jeya Maria Jose, He Zhang, Jianming Zhang, Yilin Wang, Zhe Lin , Jose Echevarria, Yinglan Ma, Zijun Wei, Kalyan Sunkavalli, and Vishal M. Patel Paper \| Code \| Project
	Fine-Context Shadow Detection using Shadow Removal WACV 2023 Jeya Maria Jose and Vishal M. Patel Paper
	TransWeather: Transformer-based Restoration of Images Degraded by Adverse Weather Conditions CVPR 2022 Jeya Maria Jose, Rajeev Yasarla and Vishal M. Patel Paper \| Code \| Project
	UNeXt: MLP-based Rapid Medical Image Segmentation Network MICCAI 2022 Jeya Maria Jose and Vishal M. Patel Paper \| Code \| Project
	Simultaneous Bone and Shadow Segmentation Network using Task Correspondence Consistency MICCAI 2022 Aimon Rahman, Jeya Maria Jose, Ilker H, and Vishal M. Patel Paper
	Orientation-guided Graph Convolutional Network for Bone Surface Segmentation MICCAI 2022 Aimon Rahman, Chaminda Bandara, Jeya Maria Jose, Ilker H, and Vishal M. Patel Paper
	Target and Task specific Source-Free Domain Adaptive Image Segmentation Preprint Vibashan VS, Jeya Maria Jose , and Vishal M. Patel *equal contribution Paper \| Code
	SPIN Road Mapper: Extracting Roads from Aerial Images via Spatial and Interaction Space Graph Reasoning for Autonomous Driving ICRA 2022 (Outstanding Automation Paper Finalist) 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 IEEE Transactions on Medical Imaging 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 (Oral) 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
	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

Services

Web Chair: AVSS 2021

Program Committe: DART Workshop, MICCAI 2022

Reviewer at:

Journals :

IEEE Transactions on Pattern Analysis and Machine Intelligence

IEEE Transactions on Medical Imaging

Elsevier Medical Image Analysis

IEEE Transactions on Circuits and Systems for Video Technology

IEEE Transactions on Geoscience and Remote Sensing

Springer International Journal on Computer Vision

Elsevier Pattern Recognition

Elsevier Computers in Biology and Medicine

Conferences :

CVPR

ICCV

ECCV

NeurIPS

ICLR

ICML

MICCAI

MIDL

WACV

ICIP

Workshops :

BrainLes, Medical Image Learning with Less Labels and Imperfect Data