I am a PhD student in Wu-Lab, at Arizona State University, co-advised by Dr. Teresa Wu and Dr. Baoxin Li
Currently focused on developing novel deep learning models for biomarker discovery, using multi-modal data and tackling issue of small datasets.
Broadly my research interests lie in Computer Vision, Medical Imaging and Deep LearningSpecifically working on solving following research questions:
- Capturing Imaging signatures of Brain-Age in Alzheimer's Disease
- Diffusion model based image super-resolution to improve quantification in Amyloid PET
- Multi-modal AI to investigate mechanisms and prevention of Persistent Post-Traumatic Headache
These research projects are in joint collaboration with Mayo Clinic, Banner Alzheimer's Institute and Barrow Neurological Institute in Arizona respectively. My CV
Also the host of Jay Shah Podcast on YouTube where I invite AI engineers, researchers and practitioners to talk more their jounrney, insights from their experience and tips on getting started.
Research
Publications
Google Scholar profile-
Ordinal Classification with Distance Regularization for Robust Brain Age Prediction
Jay Shah, Md Mahfuzur R. Siddiquee, Yi Su, Teresa Wu, Baoxin Li
In Proceedings of the IEEE/CVF WACV 2024.
link arxiv pdf code -
Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-weighted Brain MR Images
Md Mahfuzur R. Siddiquee, Jay Shah, Teresa Wu, Catherine Chong, Todd Schwedt, Baoxin Li
In Proceedings of the IEEE/CVF WACV 2024.
link arxiv pdf code AnoFPDM: Anomaly Segmentation with Forward Process of Diffusion Models for Brain MRI
Yiming Che, Fazle Rafsani, Jay Shah, Md Mahfuzur R. Siddiquee, Teresa Wu
arxiv pdf codeInterpretable deep learning framework towards understanding molecular changes in human brains with Alzheimer’s disease: implication for microglia activation and sex differences in AD
Maitry Ronakbhai Trivedi, Amogh Joshi, Jay Shah, Benjamin Readhead, Melissa Wilson, Yi Su, Eric Reiman, Teresa Wu, Qi Wang
bioarxiv pdf-
Neuropsychiatric symptoms and commonly used biomarkers of Alzheimer’s disease: A literature review from a Machine Learning perspective
Jay Shah, Md Mahfuzur R. Siddiquee, Janina Krell-Roesch, Jeremy Syrjanen, Walter Kremers, Maria Vassilaki, Erica Forzani, Teresa Wu, Yonas Geda
Journal of Alzheimer's Disease, 2023
link pdf HealthyGAN: Learning from Unannotated Medical Images to Detect Anomalies Associated with Human Disease
Md Mahfuzur R. Siddiquee, Jay Shah, Teresa Wu, Catherine Chong, Todd Schwedt, Baoxin Li
Simulation and Synthesis in Medical Imaging (SASHIMI), 2022 [MICCAI workshop]
link arxiv pdf code-
Headache Classification and Automatic Biomarker Extraction from structural MRIs using Deep Learning
Md Mahfuzur R. Siddiquee, Jay Shah, Catherine Chong, Simona Nikolova, Gina Dumkrieger, Baoxin Li, Teresa Wu, Todd Schwedt
Brain Communications, 2022
link pdf -
Deep Residual Inception Encoder-Decoder Network for Amyloid PET Harmonization
Jay Shah, Fei Gao, Valentina Ghisays, Ji Luo, Yinghua Chen, Wendy Lee, Yuxiang Zhou, Tammie Benzinger, Eric Reiman, Kewei Chen, Yi Su, Teresa Wu
Alzheimer's & Dementia, the Journal of Alzheimer's Association, 2022
link pdf WO/2023/101959 code
Conference Abstracts
Capturing MRI Signatures of Brain Age as a Potential Biomarker to Predict Persistence of Post-traumatic Headache
Jay Shah, Md Mahfuzur R. Siddiquee, Catherine Chong, Todd Schwedt, Jing Li, Visar Berisha, Katherine Ross, Teresa Wu
American Academy of Neurology, Annual Meeting, 2024
linkApplying Generative Adversarial Network on Structural Brain MRI for Unsupervised Classification of Headache
Md Mahfuzur R. Siddiquee, Jay Shah, Todd Schwedt, Catherine Chong, Baoxin Li, Teresa Wu
American Academy of Neurology, Annual Meeting, 2024
linkPrediction of Headache Improvement Using Multimodal Machine Learning in Patients with Acute Post-traumatic Headache
Amogh Joshi, Md Mahfuzur R. Siddiquee, Jay Shah, Todd Schwedt, Catherine Chong, Baoxin Li, Teresa Wu
American Academy of Neurology, Annual Meeting, 2024
linkA multi-class deep learning model to estimate brain age while addressing systematic bias of regression to the mean
Jay Shah, Ji Luo, Javad Sohankar, Eric Reiman, Kewei Chen, Yi Su, Baoxin Li, Teresa Wu
Alzheimer's Association International Conference, 2023
link pdfA 2.5D residual U-Net for improved amyloid harmonization preserving spatial information
Jay Shah, Javad Sohankar, Ji Luo, Yinghua Chen, Shan Li, Hillary Protas, Kewei Chen, Eric Reiman, Baoxin Li, Teresa Wu, Yi Su
Alzheimer's Association International Conference, 2023
link pdfInterpretable deep learning framework towards understanding molecular changes associated with neuropathology in human brains with Alzheimer’s disease
Amogh Joshi, Jay Shah, Benjamin Readhead, Yi Su, Teresa Wu, Qi Wang
Alzheimer's Association International Conference, 2023
link pdf-
AI-powered medicine article full magazine
- Thrive magazine-summer 2024, Arizona State University
- College Enrollment, Jobs, Medical Research, AGI and Consciousness with Dr. Jay Shah link
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Capturing MRI Signatures of Brain Age as a Potential Biomarker to Predict Persistence of Post-traumatic Headache slides link
- Oral presentation at American Academy of Neurology Annual Meeting, 2024
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Invited speaker on PhD student Panel
- SUmmer Research Initiative (SURI) 2023, Arizona State University
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Invited Young Professionals (YP) speaker at CMD Workshop link
- IEEE IAS Annual Meeting, 2022
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Fulton Schools CS Doctoral student & researcher explores the quickly evolving world of AI and related smart tech advances on popular podcast link
- FullCircle, Arizona State University Newsletter
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Using AI to battle Alzheimer’s link asu news
- FullCircle, Arizona State University Newsletter
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Speaking at Emerging Research Topics in Engineering(ERTE) link
- IEEE Gujarat Section
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Landscape of Explainable AI, Interpreting Deep Learning predictions and my observations from hosting an ML Podcast link
- 4th OnCV&AI workshop arranged by the Nordling Lab, National Cheng Kung University in Taiwan
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From DA-IICT to Arizona State University and working with Nobel Laureate Frank Wilczek: Journey of Jay Shah link
- DA-IICT Blog
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Interview on growing a technical podcast link link
- IEEE Spectrum and IEEE TV
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Behind the scenes with a Machine Learning Expert : Jay Shah link
- Curryup Leadership Podcast
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Python Workshop 2020 Convolutional Neural Networks 2020 2021
- AI Club, Arizona State University