Jay Shah
I’m a Machine Learning Engineer III at PathAI, developing AI-powered pathology solutions to improve patient outcomes. Previously, I completed my Ph.D. in Computer Science from Wu-Lab at Arizona State University, co-advised by Dr. Teresa Wu and Dr. Baoxin Li
Broadly, my research interests span Generative AI, Deep Learning and Medical ImagingDuring my Ph.D., I worked on AI-driven early detection of brain disorders (Alzheimer's Disease & Headaches). Specifically:
- Capturing brain-aging signatures in Alzheimer's Disease & Headache disorders
- Medical image super-resolution using to enhance quantitative accuracy
- Medical imaging quantization
These research projects were in joint collaboration with Mayo Clinic, Banner Alzheimer's Institute and Barrow Neurological Institute in Arizona. My CV
Also the host of Jay Shah Podcast on YouTube where I interview AI engineers, researchers, and practitioners to share their journey, insights, and advice for newcomers to the field.
Research
Publications
Google Scholar for latest updates-
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 -
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 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 -
Leveraging multi-modal foundation model image encoders to enhance brain MRI-based headache classification
Fazle Rafsani, Devam Sheth, Yiming Che, Jay Shah, Md Mahfuzur R. Siddiquee, Catherine Chong, Simona Nikolova, Katherine Ross, Gina Dumkrieger, Baoxin Li, Teresa Wu, Todd Schwedt
Scientific Reports, 2025
link pdf -
Enhancing Amyloid PET Quantification: MRI-Guided Super-Resolution Using Latent Diffusion Models
Jay Shah, Yiming Che, Javad Sohankar, Baoxin Li, Yi Su, Teresa Wu
Life Journal, 2024
link preprint 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
link arxiv pdf code -
DinoAtten3D: Slice-Level Attention Aggregation of DinoV2 for 3D Brain MRI Anomaly Classification
Fazle Rafsani, Jay Shah, Catherine Chong, Todd Schwedt, Teresa Wu
ICCV, 2025
arxiv 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 -
Interpretable deep learning framework for understanding molecular changes in human brains with Alzheimer’s disease: implications for microglia activation and sex differences
Maitry Ronakbhai Trivedi, Amogh Joshi, Jay Shah, Benjamin Readhead, Melissa Wilson, Yi Su, Eric Reiman, Teresa Wu, Qi Wang
link bioarxiv pdf -
Predicting cognitive decline from neuropsychiatric symptoms and Alzheimer’s disease biomarkers: A machine learning approach to a population-based data
Jay Shah, Janina Krell-Roesch, Erica Forzani, David Knopman, Cliff Jack, Ronald Petersen, Yiming Che, Teresa Wu, Yonas Geda
Journal of Alzheimer's Disease, 2024
link 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 -
Physical activity and the outcome of cognitive trajectory: a machine learning approach
Bettina Barisch-Fritz, Jay Shah, Jelena Krafft, Yonas Geda, Teresa Wu, Alexander Woll, Janina Krell-Roesch
European Reviews of Aging and Physical Activity, 2024
link pdf code
Other publications...
Conference Abstracts
Using Large-scale Contrastive Language-Image Pre-training to Maximize Brain MRI-Based Headache Classification
Fazle Rafsani, Devam Sheth, Yiming Che, Jay Shah, Md Mahfuzur R. Siddiquee, Catherine Chong, Simona Nikolva, Gina Dumkrieger, Baoxin Li, Teresa Wu, Todd Schwedt
American Academy of Neurology, Annual Meeting, 2025
linkCapturing 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 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 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 pdfEnd-to-End 3D CycleGAN Model for Amyloid PETHarmonization
Xuanzhao Dong, Yalin Wang, Jay Shah, Valentina Ghisays, Ji Luo, Yinghua Chen, Wendy Lee, Baoxin Li, Kewei Chen, Eric M. Reiman, Teresa Wu, Yi Su
Alzheimer’s Association International Conference, 2024
link pdfClassification and Biomarker Discovery of Persistent Post-traumatic Headache (PPTH) Using Deep Learning on Structural Brain MRI Data
Md Mahfuzur R. Siddiquee, Jay Shah, Todd Schwedt, Catherine Chong, Simona Nikolova, Gina Dumkrieger, Katherine Ross, Visar Berisha, Jing Li, Teresa Wu
OR/MS/Analytics in the Diagnosis and Treatment of Neurological Diseases, INFORMS Annual Meeting, 2022
linkParticipant-specific interrogation of population-based data to predict cognitive decline from neuropsychiatric symptoms and neuroimaging biomarkers: A machine learning approach
Jay Shah, Jeremy Syrjanen, Janina Krell-Roesch, Walter Kremers, Prashanthi Vemuri, Maria Vassilaki, Ronald Petersen, Erica Forzani, Teresa Wu, Yonas Geda
American Academy of Neurology, Annual Meeting, 2023
link pdfMRI signatures of Brain Age in the Alzheimer’s Disease continuum
Jay Shah, Valentina Ghisays, Yinghua Chen, Ji Luo, Baoxin Li, Eric Reiman, Kewei Chen, Teresa Wu, Yi Su
Alzheimer's Association International Conference, 2022
link pdfTransfer Learning based Deep Encoder Decoder Network for Amyloid PET Harmonization with Small Datasets
Jay Shah, Kewei Chen, Eric Reiman, Baoxin Li, Teresa Wu, Yi Su
Alzheimer's Association International Conference, 2022
link pdfClassification of Post-Traumatic Headache (PTH) using Deep Learning on Structural Brain MRI data
Md Mahfuzur R. Siddiquee, Jay Shah, Todd Schwedt, Catherine Chong, Simona Nikolova, Gina Dumkrieger, Katherine Ross, Visar Berisha, Jing Li, Teresa Wu
American Headache Society 64th Annual Scientific Meeting, 2022
link pdfMigraine Classification using Deep Learning on Structural Brain MRI data
Md Mahfuzur R. Siddiquee, Jay Shah, Todd Schwedt, Catherine Chong, Simona Nikolova, Gina Dumkrieger, Katherine Ross, Visar Berisha, Jing Li, Teresa Wu
American Headache Society 64th Annual Scientific Meeting, 2022
link pdfInterpreting Deep Learning Model Predictions using Shapley Values
Jay Shah, Catherine Chong, Todd Schwedt, Visar Berisha, Jing Li, Katherine Ross, Gina Dumkrieger, Jianwei Zhang, Nathan Gaw, Simona Nikolova, Teresa Wu
INFORMS Annual Meeting, 2021
pdfDeep Residual Inception Encoder-Decoder Network for Amyloid PET Harmonization
Jay Shah, Valentina Ghisays, Ji Luo, Yinghua Chen, Wendy Lee, Baoxin Li, Tammie Benzinger, Eric Reiman, Kewei Chen, Yi Su, Teresa Wu
Alzheimer’s Association International Conference, 2021
link pdf
Other abstracts...
Patents
User-guided context-aware music recommendations
Inventors: Jay Shah, Shanti Stewart, Gauri Jagatap, Gouthaman KV, Andrea Fanelli
Dolby Laboratories, 2024Deep Residual Inception Encoder-Decoder Network for Amyloid PET Harmonization
Inventors: Fei Gao, Yi Su, Jay Shah, Teresa Wu
US20240285244A1 WO2023101959A1 pdf
Work Experience
Machine Learning Engineer III
PathAI, Boston
08.2025 - Present
Research Assistant, Ph.D. Student
Arizona State University, Tempe
05.2020 - 07.2025
Ph.D. Research Intern
Dolby Laboratories, San Francisco [Machine Perception and Reasoning]
05.2024 - 08.2024
Research Scientist Intern
Amazon, Seattle [Health Halo Computer Vision]
05.2022 - 08.2022
Graduate Teaching Assistant
Arizona State University, Tempe
10.2019 -05.2020
Research Intern - Computer Vision
Philips Research Labs, Cambridge
06.2019 -08.2019
Graduate Research Assistant
Arizona State University, Tempe
11.2018 -06.2019
Machine Learning Engineer Intern
HackerRank, Bengaluru
01.2018 -05.2018
Visiting Research Assistant
Nanyang Technological University, Singapore
05.2017 -08.2017
News and Highlights
- I will be joining PathAI as a Machine Learning Engineer III
- Successfully defended my Ph.D. thesis on "Novel Deep Learning techniques for Early Detection of Neurological Disorders" slides thesis
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Invited lecture on "Novel Deep Learning techniques for Early Detection of Neurological Disorders"
- Stephen and Denise Adams Center for Parkinson's Disease, Yale University
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Invited talk on "AI for Early Detection of Alzheimer’s Disease" link
- AI Club, DAIICT
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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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Invited speaker at Emerging Research Topics in Engineering(ERTE) link
- IEEE Gujarat Section
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Invited talk on "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
- Best 100 Machine Learning Podcasts, Million Podcasts link
- Best 100 Research Podcasts, Million Podcasts link
- A hand-curated list of the best AI Podcasts, AI Depot link
- 8 of the best machine learning podcasts to listen to in 2022, Qwak MLOps link
- 5 Best Machine Learning & AI Podcasts, Unite[dot]AI, Futurist series link
- 20 best Machine Learning Podcasts of 2021, Welp Magazine link