2010 - Fellow of the American Association for the Advancement of Science (AAAS)
2008 - IEEE Fellow For contributions to nonlinear process control and analysis for biological systems
Francis J. Doyle spends much of his time researching Artificial pancreas, Control theory, Model predictive control, Type 1 diabetes and Diabetes mellitus. His Artificial pancreas study combines topics from a wide range of disciplines, such as Meal, Clinical trial, Surgery and Continuous glucose monitoring. He has researched Control theory in several fields, including Control engineering and Process control.
Francis J. Doyle combines subjects such as Kalman filter, Multivariable calculus and System identification with his study of Model predictive control. The study incorporates disciplines such as Hypoglycemia and Basal insulin in addition to Type 1 diabetes. His Diabetes mellitus study incorporates themes from Internal medicine and Insulin.
Francis J. Doyle focuses on Control theory, Model predictive control, Artificial pancreas, Type 1 diabetes and Nonlinear system. His work carried out in the field of Control theory brings together such families of science as Control engineering and Process control. His Model predictive control study integrates concerns from other disciplines, such as Linear model, Robustness and Circadian rhythm.
His research integrates issues of Meal, Insulin delivery, Surgery and Insulin pump in his study of Artificial pancreas. His study in Type 1 diabetes is interdisciplinary in nature, drawing from both Hypoglycemia, Internal medicine and Insulin. His research links Mathematical optimization with Nonlinear system.
His primary areas of study are Artificial pancreas, Type 1 diabetes, Model predictive control, Internal medicine and Diabetes mellitus. His study on Artificial pancreas also encompasses disciplines like
His Model predictive control research includes themes of Control theory, Insulin sensitivity, Circadian clock, Circadian rhythm and Blood sugar regulation. The Limit cycle and Nonlinear system research Francis J. Doyle does as part of his general Control theory study is frequently linked to other disciplines of science, such as Weighting, therefore creating a link between diverse domains of science. His Diabetes mellitus research incorporates elements of Physical therapy, Surgery and MEDLINE.
The scientist’s investigation covers issues in Artificial pancreas, Type 1 diabetes, Hypoglycemia, Internal medicine and Model predictive control. He combines subjects such as Control theory, Clinical trial and Insulin, Glycemic with his study of Artificial pancreas. His study on Hypoglycemia is covered under Diabetes mellitus.
His Internal medicine study combines topics in areas such as Endocrinology, Methylation, Oncology, DNA methylation and Cardiology. His work carried out in the field of Model predictive control brings together such families of science as PID controller, Embedded system, Control theory and Bolus. The concepts of his Control theory study are interwoven with issues in Phase response curve, Interval and Phase synchronization.
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Robustness of cellular functions
Jörg Stelling;Uwe Sauer;Zoltan Szallasi;Francis J. Doyle.
Dynamic Flux Balance Analysis of Diauxic Growth in Escherichia coli
Radhakrishnan Mahadevan;Jeremy S. Edwards;Francis J. Doyle.
Biophysical Journal (2002)
International Consensus on Use of Continuous Glucose Monitoring
Thomas Danne;Revital Nimri;Tadej Battelino;Richard M. Bergenstal.
Diabetes Care (2017)
Clinical Targets for Continuous Glucose Monitoring Data Interpretation: Recommendations From the International Consensus on Time in Range
Tadej Battelino;Thomas Danne;Richard M. Bergenstal;Stephanie A. Amiel.
Diabetes Care (2019)
Intercellular Coupling Confers Robustness against Mutations in the SCN Circadian Clock Network
Andrew C. Liu;Andrew C. Liu;David K. Welsh;David K. Welsh;David K. Welsh;Caroline H. Ko;Caroline H. Ko;Hien G. Tran;Hien G. Tran.
Survey on iterative learning control, repetitive control, and run-to-run control
Youqing Wang;Furong Gao;Francis J. Doyle.
Journal of Process Control (2009)
A model-based algorithm for blood glucose control in Type I diabetic patients
R.S. Parker;F.J. Doyle;N.A. Peppas.
IEEE Transactions on Biomedical Engineering (1999)
Robust H∞ glucose control in diabetes using a physiological model
Robert S. Parker;Francis J. Doyle;Jennifer H. Ward;Nicholas A. Peppas.
Aiche Journal (2000)
Method and apparatus for glucose control and insulin dosing for diabetics
Francis J. Doyle;Lois Jovanovic.
Nonlinear model-based control using second-order Volterra models
Francis J. Doyle;Francis J. Doyle;Babatunde A. Ogunnaike;Ronald K. Pearson.
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