Meet the host
Glen Wright Colopy is a machine learning scientist who has worked in the healthcare, biomedical, and pharmaceutical industries since 2010. Glen joined industry full-time in 2018 after graduating from the Computational Health Informatics Lab (CHI) at the Oxford Institute of Biomedical Engineering (IBME).
He primarily works on time-series data modeling for automated monitoring and anomaly/outlier detection for large continuous data streams, such as
(i) patient vital signs (ex. heart rate, blood pressure, blood glucose),
(ii) medical device digital logs, and
(iii) clinical trial audit logs and pharmaceutical supply chains.
Glen’s research interests include Bayesian nonparametrics for personalized medical modeling and anomaly detection, the robust automation of statistical inference, and the experimental design of machine learning-based clinical trials. He is particularly interested in how critical reasoning can help people in the data sciences improve their scientific productivity.
Outside of work Glen active in several professional societies, including the American Statistical Association (ASA), the Institute of Engineering and Technology (IET), and the Institute of Electrical and Electronics Engineering (IEEE). Outside of nerd-work, Glen volunteers for his family’s non-profit, which organizes about 30 events per year to help other non-profits raise money for their charitable causes.
He am an Associate Editor of the Journal of Data Science and Program Chair-Elect for the ASA’s Section on Statistical Learning and Data Science.
Education
D.Phil. Engineering Science, University of Oxford, 2018
Thesis Title: Bayesian Gaussian Processes for Identifying the Deteriorating Patient
Advisers: David Clifton and Stephen Roberts
M.Sc. Applied Statistics, University of Oxford, 2012
Thesis Title: Market Makers and High Frequency Traders: Agents of Time and Space (A Multivariate Simulation Approach)
M.Sc. Operations Research, North Carolina State University, 2011
Thesis Title: An Application of Mixed Integer Linear Programing to Observed Medical Outcomes Partnership’s Safety Signal Detection
B.S. Mathematics and Economics, College of William and Mary, 2009
Publications & Patents
Glen’s research has been well received within the academic biomedical engineering community and in industry where it has been applied. His publications includes several invited journal articles, special journal issues, and conference paper awards.
Some of the work completed during his doctorate was patented by Oxford University.
Since leaving academia, Glen continues to actively collaborate with my colleagues at Oxford, NC State, and elsewhere, as time allows.
Outside of authoring, he is also a reviewer for several journals in biomedical engineering including the IEEE Journal of Biomedical and Health Informatics and Computers in Biology and Medicine Elsevier.
Publications
Colopy, G.W., Roberts, S.J., Clifton, D.A.: Gaussian Processes for Personalized Interpretable Volatility Metrics in the Step-down Ward, IEEE JBHI 23(3), 2019 p.949-959 [Paper Accepted for Special Issue on AI-Enabled Connected Health Informatics]
Zhu, T., Colopy, G. W., MacEwan, C., Neihaus, K., Yang, Y., Pugh, C. W., and Clifton, D. A.: Patient-Specific Physiological Monitoring and Prediction Using Structured Gaussian Processes, IEEE Access 7(1), 2019, p. 58094-58103
Kwong. M. T., Colopy, G. W., Weber, A. M., Ercole, A., Bergmann, J. H. M.: The efficacy and effectiveness of machine learning for mechanically ventilated patients in the intensive care unit: A systematic review, Bio-Design and Manufacturing 2019
Colopy, G.W., Roberts, S.J., Clifton, D.A.: Bayesian Optimisation of Personalised Models for Patient Vital-Sign Monitoring; IEEE JBHI 22(2), 2018, p. 301-310 [Invited Paper for Special Issue on Informatics for Personalized, Precision, and Preventative Healthcare]
T. Rieger, et al: Improving the Generation and Selection of Virtual Populations in Quantitative Systems Pharmacology Models, Progress in Biophysics and Molecular Biology, 2018.
Zhu, T., Colopy, G. W., Pugh, C. W., and Clifton, D. A., Identifying Patient-Specific Trajectories in Haemodialysis Using Bayesian Hierarchical Gaussian Processes, Procs IEEE BHI Conf, 2018 [Winner of Conference Paper Competition: 2nd Place.]
Whiting, S., Moreland, S., Costello, J., Colopy, G. W., McCann, C.: Recognising Cardiac Abnormalities in Wearable Device Photoplethysmography (PPG) with Deep Learning. KDD Workshop on Machine Learning for Medicine and Healthcare, 2018
Colopy, G.W., Zhu, T., Clifton, L., Roberts, S.J., Clifton, D.A.: Likelihood-based Artefact Detection in Continuously-Acquired Patient Vital Signs; Procs IEEE EMBC, 2017
Colopy, G.W., Pimentel, M.A.F., Roberts, S.J., Clifton, D.A.: Bayesian Optimisation of Gaussian Processes for Identifying the Deteriorating Patient; Procs IEEE BHI Conf, 2017
Colopy, G.W., Pimentel, M.A.F., Roberts, S.J., Clifton, D.A.: State-Space Approximations to Gaussian Processes for Patient Vital-Sign Monitoring in Computationally Constrained Environments; MEIBioEng AHT, 2016
Colopy, G.W., Pimentel, M.A.F., Roberts, S.J., Clifton, D.A.: Bayesian Gaussian Processes for Identifying the Deteriorating Patient; Procs IEEE EMBC, 2016
Clifton, D.A., Niehaus, K.E., Charlton, P., and Colopy, G.W.: Health Informatics for the Clinical Management of Patients Yearbook of Medical Informatics, International Medical Informatics Association
Clifford, Louis, Robbe, Ackroyde, Burns, Timbs, Colopy et. al.: SAMHD1 is mutated recurrently in chronic lymphocytic leukemia and is involved in response to DNA damage; Blood; 2013
Patents
D. A. Clifton, M. A. F. Pimentel, and G. W. Colopy, "System Monitor and Method of System Monitoring", GB 1613318.3, 2016
T. Zhu, D.A. Clifton, C. Pugh, and G. W. Colopy, “Bayesian System for Phenotyping Patients”, 2018