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ORCIDAhmed Metwally 0002
Person information
- affiliation: Google, Mountain View, CA, USA
- affiliation: Stanford University, CA, USA
- affiliation (PhD 2019): University of Illinois at Chicago, Department of Bioengineering, Chicago, IL, USA
- not to be confused with: Ahmed Metwally 0001
Other persons with the same name
- Ahmed Metwally 0001
![[0000-0002-1084-8078]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-1084-8078")
— Uber Technologies, Sunnyvale, CA, USA (and 3 more)
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2020 – today
- 2025
[j6]Heyjun Park, Ahmed A. Metwally, Alireza Delfarah, Yue Wu, Dalia Perelman, Caleb Mayer, Curtis McGinity, Majid Rodgar, Alessandra Celli, Tracey McLaughlin, Emmanuel Mignot, Michael Snyder:
High-resolution lifestyle profiling and metabolic subphenotypes of type 2 diabetes. npj Digit. Medicine 8(1) (2025)- [j5]María Fernanda Cabrera-Umpiérrez, Tayo Obafemi-Ajayi, Ahmed Metwally, Bobak J. Mortazavi:
Guest Editorial: Deep Medicine and AI for Health. IEEE J. Biomed. Health Informatics 29(2): 737-740 (2025) - [i11]Neil Mallinar, A. Ali Heydari, Xin Liu, Anthony Z. Faranesh, Brent Winslow, Nova Hammerquist, Benjamin Graef, Cathy Speed, Mark Malhotra, Shwetak N. Patel, Javier L. Prieto, Daniel McDuff, Ahmed A. Metwally:
A Scalable Framework for Evaluating Health Language Models. CoRR abs/2503.23339 (2025) - [i10]Ahmed A. Metwally, A. Ali Heydari, Daniel McDuff, Alexandru Solot, Zeinab Esmaeilpour, Anthony Z. Faranesh, Menglian Zhou, David B. Savage, Conor Heneghan, Shwetak N. Patel, Cathy Speed, Javier L. Prieto:
Insulin Resistance Prediction From Wearables and Routine Blood Biomarkers. CoRR abs/2505.03784 (2025) - [i9]Maxwell A. Xu, Girish Narayanswamy, Kumar Ayush, Dimitris Spathis, Shun Liao, Shyam A. Tailor, Ahmed Metwally, A. Ali Heydari, Yuwei Zhang, Jake Garrison, Samy Abdel-Ghaffar, Xuhai Xu, Ken Gu, Jacob E. Sunshine, Ming-Zher Poh, Yun Liu, Tim Althoff, Shrikanth Narayanan, Pushmeet Kohli, Mark Malhotra, Shwetak N. Patel, Yuzhe Yang, James M. Rehg, Xin Liu, Daniel McDuff:
LSM-2: Learning from Incomplete Wearable Sensor Data. CoRR abs/2506.05321 (2025) - [i8]Yuwei Zhang, Kumar Ayush, Siyuan Qiao, A. Ali Heydari, Girish Narayanswamy, Maxwell A. Xu, Ahmed A. Metwally, Shawn Xu, Jake Garrison, Xuhai Xu, Tim Althoff, Yun Liu, Pushmeet Kohli, Jiening Zhan, Mark Malhotra, Shwetak N. Patel, Cecilia Mascolo, Xin Liu, Daniel McDuff, Yuzhe Yang:
SensorLM: Learning the Language of Wearable Sensors. CoRR abs/2506.09108 (2025) - [i7]Cathy Speed, Ahmed A. Metwally:
The Human-AI Hybrid Delphi Model: A Structured Framework for Context-Rich, Expert Consensus in Complex Domains. CoRR abs/2508.09349 (2025) - [i6]A. Ali Heydari, Ken Gu, Vidya Srinivas, Hong Yu, Zhihan Zhang, Yuwei Zhang, Akshay Paruchuri, Qian He, Hamid Palangi, Nova Hammerquist, Ahmed A. Metwally, Brent Winslow, Yubin Kim, Kumar Ayush, Yuzhe Yang, Girish Narayanswamy, Maxwell A. Xu, Jake Garrison, Amy A. Lee, Jenny Vafeiadou, Benjamin Graef, Isaac R. Galatzer-Levy, Erik Schenck, Andrew Barakat, Javier Perez Matos, Jacqueline Shreibati, John Hernandez, Anthony Z. Faranesh, Javier L. Prieto, Conor Heneghan, Yun Liu, Jiening Zhan, Mark Malhotra, Shwetak N. Patel, Tim Althoff, Xin Liu, Daniel McDuff, Xuhai Xu:
The Anatomy of a Personal Health Agent. CoRR abs/2508.20148 (2025) - [i5]Ahmed A. Metwally, Heyjun Park, Yue Wu, Tracey McLaughlin, Michael P. Snyder:
Use of Continuous Glucose Monitoring with Machine Learning to Identify Metabolic Subphenotypes and Inform Precision Lifestyle Changes. CoRR abs/2511.03986 (2025) - 2024
- [c10]A. Ali Heydari, Naghmeh Rezaei, Javier L. Prieto, Shwetak N. Patel, Ahmed A. Metwally:
Lifestyle-Informed Personalized Blood Biomarker Prediction via Novel Representation Learning. BHI 2024: 1-8 - [i4]A. Ali Heydari, Naghmeh Rezaei, Javier L. Prieto, Shwetak N. Patel, Ahmed A. Metwally:
Lifestyle-Informed Personalized Blood Biomarker Prediction via Novel Representation Learning. CoRR abs/2407.07277 (2024) - 2022
- [j4]Ahmed A. Metwally, Tom Zhang, Si Wu, Ryan Kellogg, Wenyu Zhou, Kévin Contrepois, Hua Tang, Michael Snyder:
Robust identification of temporal biomarkers in longitudinal omics studies. Bioinform. 38(15): 3802-3811 (2022) - 2021
- [c9]Sally Mostafa, Isabel Hyo Jung Song, Ahmed A. Metwally, Nicolas Strauli, Nehemiah Sewde, Michel Friesenhahn, Maxime Usdin, Xiaoming Jia:
Predicting upper limb disability progression in primary progressive multiple sclerosis using machine learning and statistical methods. BIBM 2021: 1453-1457 - [c8]Ahmed A. Metwally, Ariel K. Leong, Aman Desai, Anvith Nagarjuna, Dalia Perelman, Michael Snyder:
Learning Personal Food Preferences via Food Logs Embedding. BIBM 2021: 2281-2286 - [i3]Ahmed A. Metwally, Ariel K. Leong, Aman Desai, Anvith Nagarjuna, Dalia Perelman, Michael Snyder:
Learning Personal Food Preferences via Food Logs Embedding. CoRR abs/2110.15498 (2021) - [i2]Derek Reiman, Ahmed Metwally, Jun Sun, Yang Dai:
Meta-Signer: Metagenomic Signature Identifier based onrank aggregation of features. F1000Research 10: 194 (2021) - 2020
- [j3]Derek Reiman, Ahmed A. Metwally, Jun Sun, Yang Dai:
PopPhy-CNN: A Phylogenetic Tree Embedded Architecture for Convolutional Neural Networks to Predict Host Phenotype From Metagenomic Data. IEEE J. Biomed. Health Informatics 24(10): 2993-3001 (2020)
2010 – 2019
- 2019
- [j2]Ahmed A. Metwally, Philip S. Yu, Derek Reiman, Yang Dai, Patricia W. Finn, David L. Perkins:
Utilizing longitudinal microbiome taxonomic profiles to predict food allergy via Long Short-Term Memory networks. PLoS Comput. Biol. 15(2) (2019) - [c7]Hani Aldirawi, Jie Yang, Ahmed A. Metwally:
Identifying Appropriate Probabilistic Models for Sparse Discrete Omics Data. BHI 2019: 1-4 - [c6]Mladen R. Rasic, Ahmed A. Metwally, Patricia W. Finn, David L. Perkins:
Taxonomic Classification at the Strain Level using a Species-of-Interest $\boldsymbol{k}$-mer Database. BHI 2019: 1-4 - [c5]Asem Alaa, Ayman M. Eldeib, Ahmed A. Metwally:
Protein Subcellular Localization Prediction Based on Internal Micro-similarities of Markov Chains. EMBC 2019: 1355-1358 - 2018
- [j1]Ahmed A. Metwally, Hani Aldirawi, Jie Yang:
A review on probabilistic models used in microbiome studies. Commun. Inf. Syst. 18(3): 173-191 (2018) - [c4]Asem Alaa, Ahmed A. Metwally:
Cloud-based solution for improving usability and interactivity of metagenomic ensemble taxonomic classification methods. BHI 2018: 198-201 - [i1]Jianguo Chen, Kenli Li, Kashif Bilal, Ahmed A. Metwally, Keqin Li, Philip S. Yu:
Parallel Protein Community Detection in Large-scale PPI Networks Based on Multi-source Learning. CoRR abs/1811.12160 (2018) - 2017
- [c3]Ahmed A. Metwally, Patricia W. Finn, Yang Dai, David L. Perkins:
Detection of Differential Abundance Intervals in Longitudinal Metagenomic Data Using Negative Binomial Smoothing Spline ANOVA. BCB 2017: 295-304 - [c2]Ahmed Metwally, Christian Ascoli, Kalista Andropolis, Ravi Ranjan, Yang Dai, Thomas Ferkol, Patricia W. Finn, David L. Perkins:
Microbiome Dynamics as Predictors of Lung Transplant Rejection. BCB 2017: 619 - [c1]Derek Reiman, Ahmed Metwally, Yang Dai:
Using convolutional neural networks to explore the microbiome. EMBC 2017: 4269-4272
Coauthor Index
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