Aldo A. Faisal

Affiliations: 
University of Cambridge, Cambridge, England, United Kingdom 
Area:
Computational Neuroscience, Channel noise, Axon, Action Potential, Time
Google:
"Aldo Faisal"
Mean distance: 13.58 (cluster 17)
 
SNBCP

Parents

Sign in to add mentor
Malcolm Burrows grad student 1998-2000 Cambridge
 (MPhil supervisor)
Simon Laughlin grad student 2000-2004 Cambridge
 (PhD supervisor)
Daniel M. Wolpert post-doc Cambridge

Children

Sign in to add trainee
Chaiyawan Auepanwiriyakul grad student Imperial College of London
Alex J Harston grad student
Mohammed Khwaja grad student Imperial College of London
Margarita Kotti grad student Department of Surgery and Cancer, Imperial College London
Luchen Li grad student
Romy Lorenz grad student Imperial College London
Garazi Arana Oiarbide grad student Imperial College London
Pablo Ortega grad student Imperial College of London
Benjamin Post grad student Imperial College London
Mahendran Subramanian grad student Imperial College London
Scott V. Taylor grad student Imperial College London
Sigourney Waibel grad student Imperial College London
Ariadne Whitby grad student Cambridge
Yufei Wu grad student
Ali Neishabouri grad student 2010- Imperial College London
Andreas A C Thomik grad student 2010- Imperial College London
Constantinos Gavriel grad student 2012- Imperial College London
Rajeshwari Iyer grad student 2012- Imperial College London
Alessandro Ticchi grad student 2012- Imperial College London
Amr Nimer grad student 2020- Imperial College London
Ekaterina Abramova grad student 2010-2013 Imperial College London
Anastasia Sylaidi grad student 2010-2015 Imperial College London
William Welby Abbott grad student 2011-2015 Imperial College London
Feryal Mehraban Pour Behbahani grad student 2011-2015 Imperial College London
Diana Bicazan grad student 2015-2018 Imperial College London
Charalambos Konnaris grad student 2015-2018 Imperial College London
Pavel Orlov post-doc
Ali Shafti post-doc
Giuseppe zito post-doc Imperial College London
Balasundaram Kadirvelu post-doc 2018- Imperial College London
Luke Dickens post-doc 2011-2012 Imperial College London
Shlomi Haar post-doc 2017-2020 Imperial College London

Collaborators

Sign in to add collaborator
Jeremy E. Niven collaborator Cambridge
John A. White collaborator Cambridge
Luc PJ Selen collaborator 2006- Cambridge
Dietrich Stout collaborator 2006-
BETA: Related publications

Publications

You can help our author matching system! If you notice any publications incorrectly attributed to this author, please sign in and mark matches as correct or incorrect.

Patel BV, Haar S, Handslip R, et al. (2021) Natural history, trajectory, and management of mechanically ventilated COVID-19 patients in the United Kingdom. Intensive Care Medicine
Haar S, Faisal AA. (2020) Brain Activity Reveals Multiple Motor-Learning Mechanisms in a Real-World Task. Frontiers in Human Neuroscience. 14: 354
Rito Lima I, Haar S, Di Grassi L, et al. (2020) Neurobehavioural signatures in race car driving: a case study. Scientific Reports. 10: 11537
Bachtiger P, Plymen CM, Pabari PA, et al. (2020) Artificial Intelligence, Data Sensors and Interconnectivity: Future Opportunities for Heart Failure. Cardiac Failure Review. 6: e11
Gottesman O, Johansson F, Komorowski M, et al. (2019) Guidelines for reinforcement learning in healthcare. Nature Medicine. 25: 16-18
Faisal AA, Harston JA, Auepanwiriyakul C, et al. (2019) The Embodied Semantic Fovea - real-time understanding of what and how we look at things in-the-wild Journal of Vision. 19
Harston JA, Abbott WW, Faisal A. (2019) How body movements in a task predict visual attention dynamically Journal of Vision. 19: 149b
Khwaja M, Vaid SS, Zannone S, et al. (2019) Modeling Personality vs. Modeling Personalidad: In-the-wild Mobile Data Analysis in Five Countries Suggests Cultural Impact on Personality Models Arxiv: Human-Computer Interaction. 3: 88
Parbhoo S, Gottesman O, Ross AS, et al. (2018) Improving counterfactual reasoning with kernelised dynamic mixing models. Plos One. 13: e0205839
Komorowski M, Celi LA, Badawi O, et al. (2018) The Artificial Intelligence Clinician learns optimal treatment strategies for sepsis in intensive care. Nature Medicine. 24: 1716-1720
See more...