Jay Shah
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Mail code: 8809Campus: Tempe
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Student Information
Graduate StudentComputer Science
Ira A Fulton Engineering
Ph.D. in Computer Science
Arizona State University - 2025
Masters in Computer Science
Arizona State University - 2020
Bachelors in Information and Communication Technology
Dhirubhai Ambani Institute of Information and Communication Technology - 2018
Research Assistant, Ph.D. student
Working with Dr. Baoxin Li and Dr. Teresa Wu on projects with a focus on using Deep Learning models for biomarker discovery for Alzheimer's disease and building Interpretable AI models for healthcare applications.
SciHub, Arizona State University
Collaborated with Frank Wilczek, Professor of Physics at MIT, ASU & Nobel Laureate (2004), & Nathan Newman, Professor and Lamonte H. Lawrence Chair in Solid State Science at ASU to study human color perception and how we can use Machine Learning to expand our senses.
Building tools for an Automatic Art Authentication system using image analysis, classification, detection, unmixing & estimation of paint pigments.
- Ordinal Classification with Distance Regularization for Robust Brain Age Prediction
Jay Shah, Md Mahfuzur Rahman Siddiquee, Yi Su, Teresa Wu, Baoxin Li, In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. 2024.
[link] - Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-weighted Brain MR Images
Md Mahfuzur Rahman Siddiquee, Jay Shah, Teresa Wu, Catherine Chong, Todd Schwedt, Baoxin Li, In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. 2024.
[link] - 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 L.S. Benzinger, Eric M. Reiman, Kewei Chen, Yi Su, Teresa Wu, Alzheimer's & Dementia, the Journal of Alzheimer's Association, 2022
[link], [pdf] - Enhancing Amyloid PET Quantification: MRI-Guided Super-Resolution Using Latent Diffusion Models
Jay Shah, Yiming Che, Javad Sohankar, Ji Luo, Baoxin Li, Yi Su, Teresa Wu, Life Journal, 2024
[link] - Neuropsychiatric symptoms and commonly used biomarkers of Alzheimer’s disease: A literature review from a Machine Learning perspective
Jay Shah, Md Mahfuzur Rahman Siddiquee, Janina Krell-Roesch, Jeremy A. Syrjanen, Walter K. Kremers, Maria Vassilaki, Erica Forzani, Teresa Wu, Yonas E. Geda, Journal of Alzheimer's Disease, 2023
[link] - Interpretable 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, Yi Su, Eric M. Reiman, Teresa Wu, Qi Wang
[link] - Headache Classification and Automatic Biomarker Extraction from structural MRIs using Deep Learning
Md Mahfuzur Rahman Siddiquee, Jay Shah, Catherine Chong, Simona Nikolova, Gina Dumkrieger, Baoxin Li, Teresa Wu, Todd J Schwedt, Brain Communications, 2022
[link] - HealthyGAN: Learning from Unannotated Medical Images to Detect Anomalies Associated with Human Disease
Md Mahfuzur Rahman Siddiquee, Jay Shah, Teresa Wu, Catherine Chong, Todd Schwedt, Baoxin Li, Simulation and Synthesis in Medical Imaging (SASHIMI), 2022 [MICCAI workshop]
[link], [pdf], [code] - Participant-specific interrogation of population-based data to predict cognitive decline from neuropsychiatric symptoms and neuroimaging biomarkers: A machine learning approach
Jay Shah, Jeremy A. Syrjanen, Janina Krell-Roesch, Walter K. Kremers, Prashanthi Vemuri, Maria Vassilaki, Ronald C. Petersen, Erica Forzani, Teresa Wu, Yonas E. Geda, American Academy of Neurology, Annual Meeting, 2023
[link] - MRI signatures of Brain Age in the Alzheimer’s Disease continuum
Jay Shah, Valentina Ghisays, Yinghua Chen, Ji Luo, Baoxin Li, Eric M. Reiman, Kewei Chen, Teresa Wu, Yi Su, Alzheimer's Association International Conference, 2022
[link], [pdf]
National Institutes of Health (NIH) Trainee Travel Award, December 2023
IEEE Impact Creator Award, January 2021
IEEE IAS Travel Grant Award, 2019, Baltimore, USA
CVPR, 2019 Travel Grant, Long Beach, California
IEEE IAS Travel Grant Award, 2018, Portland, USA
IEEE IAS Travel Grant Award, 2017, Cincinnati, USA
Poster 'Eco-Vending Machine' won the 1st prize at IEEE-IAS CMD International Robotic Contest - 2017
Personal Website: https://www.public.asu.edu/~jgshah1/
Subcommittee Chair, Conference Publication and Travel Program, IEEE
Research Assistant, Arizona State University, Tempe - May'20 - Present
Research Scientist Intern, Dolby Laboratories, San Francisco - May'24 to Aug'24
Research Scientist Intern, Amazon Science (Halo Heath CV), Seattle - May'22 to Aug'22
Research & Development Intern, Philips Research Labs, Cambridge - June'19 to Aug'19
Graduate Research Assistant, Arizona State University, Tempe - (9 months)
Machine Learning Challenge Curator, HackerRank, India - (6 months)
Research Assistant, Nanyang Technological University, Singapore - Summer 2017
Research Assistant, DA-IICT, India - Summer 2016
Subcommittee Chair, Conference Publication and Travel Program, IEEE
More about me: https://www.public.asu.edu/~jgshah1/