Faraz Faghri

According to our database, Faraz Faghri authored at least 15 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

BiomedSQL: Text-to-SQL for Scientific Reasoning on Biomedical Knowledge Bases.

Mathew J. Koretsky, Maya Willey, Adi Asija, Owen Bianchi, Chelsea X. Alvarado, Tanay Nayak, Nicole Kuznetsov, Sungwon Kim, Mike A. Nalls, Daniel Khashabi, Faraz Faghri

CoRR, May, 2025

Lost in the Haystack: Smaller Needles are More Difficult for LLMs to Find.

Owen Bianchi, Mathew J. Koretsky, Maya Willey, Chelsea X. Alvarado, Tanay Nayak, Adi Asija, Nicole Kuznetsov, Mike A. Nalls, Faraz Faghri, Daniel Khashabi

CoRR, May, 2025

SECONDGRAM: Self-conditioned diffusion with gradient manipulation for longitudinal MRI imputation.

Brandon Theodorou, Anant Dadu, Mike A. Nalls, Faraz Faghri, Jimeng Sun

Patterns, 2025

2024

Federated learning for multi-omics: A performance evaluation in Parkinson's disease.

Benjamin P. Danek, Mary B. Makarious, Anant Dadu, Dan Vitale, Paul Suhwan Lee, Andrew B. Singleton, Mike A. Nalls, Jimeng Sun, Faraz Faghri

Patterns, March, 2024

Instruction Tuning Large Language Models to Understand Electronic Health Records.

Zhenbang Wu, Anant Dadu, Mike A. Nalls, Faraz Faghri, Jimeng Sun

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Multimodal Patient Representation Learning with Missing Modalities and Labels.

Zhenbang Wu, Anant Dadu, Nicholas J. Tustison, Brian B. Avants, Mike A. Nalls, Jimeng Sun, Faraz Faghri

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Application of Aligned-UMAP to longitudinal biomedical studies.

Anant Dadu, Vipul Satone, Rachneet Kaur, Mathew J. Koretsky, Hirotaka Iwaki, Yue A. Qi, Daniel M. Ramos, Brian B. Avants, Jacob Hesterman, Roger Gunn, Mark R. Cookson, Michael E. Ward, Andrew B. Singleton, Roy H. Campbell, Mike A. Nalls, Faraz Faghri

Patterns, June, 2023

2022

PhenoExam: gene set analyses through integration of different phenotype databases.

Alejandro Cisterna, Aurora González-Vidal, Daniel Ruiz, Jordi Ortiz, Alicia Gómez-Pascual, Zhongbo Chen, Mike A. Nalls, Faraz Faghri, John Hardy, Irene Díez, Paolo Maietta, Sara Álvarez, Mina Ryten, Juan A. Botía

BMC Bioinform., December, 2022

2021

Uncovering the complexities of biological structures with network-based learning: An application in SARS-CoV-2.

Faraz Faghri, Mike A. Nalls

Patterns, 2021

GenoML: Automated Machine Learning for Genomics.

Mary B. Makarious, Hampton L. Leonard, Dan Vitale, Hirotaka Iwaki, David Saffo, Lana Sargent, Anant Dadu, Eduardo Salmerón Castaño, John F. Carter, Melina Maleknia, Juan A. Botía, Cornelis Blauwendraat, Roy H. Campbell, Sayed Hadi Hashemi, Andrew B. Singleton, Mike A. Nalls, Faraz Faghri

CoRR, 2021

2019

Learning a long healthy aging

Faraz Faghri

PhD thesis, 2019

2018

Learning the progression and clinical subtypes of Alzheimer's disease from longitudinal clinical data.

Vipul Satone, Rachneet Kaur, Faraz Faghri, Mike A. Nalls, Andrew B. Singleton, Roy H. Campbell

CoRR, 2018

2017

Toward Scalable Machine Learning and Data Mining: the Bioinformatics Case.

Faraz Faghri, Sayed Hadi Hashemi, Mohammad Babaeizadeh, Mike A. Nalls, Saurabh Sinha, Roy H. Campbell

CoRR, 2017

Decentralized User-Centric Access Control using PubSub over Blockchain.

Sayed Hadi Hashemi, Faraz Faghri, Roy H. Campbell

CoRR, 2017

2016

World of Empowered IoT Users.

Sayed Hadi Hashemi, Faraz Faghri, Paul Rausch, Roy H. Campbell

Proceedings of the First IEEE International Conference on Internet-of-Things Design and Implementation, 2016