Conferences
Two Students: Enabling Uncertainty Quantification in Federated Learning Clients
Published in NeurIPS 2024 Workshop BDU
by C. Iglesias Jr, et al.
This paper is about novel Bayesian approaches for federated learning.
Download PaperCARG HUB: AI for bioreactors
CARG HUB: AI for bioreactors
This research is all about improving how we monitor bioprocesses in the biopharmaceutical industry, making it faster and less expensive. The project focuses on developing advanced tools called nonlinear Kalman estimators (NKEs) to tackle these issues. Specifically, it aims to solve three big challenges: estimating important process parameters in complex biological systems, automatically tuning these estimation tools for different production conditions, and making the estimators more adaptable and accurate for different types of processes.
Publications
Manuscripts
How Not to Make the Joint Extended Kalman Filter Fail with Unstructured Mechanistic Models
Published in Sensors
by Iglesias Jr, CF, Bolic, M.
Addresses the problems in joint estimation of states and parameters with an extended Kalman filter.
Download PaperManuscripts
rAAV Manufacturing: The Challenges of Soft Sensing during Upstream Processing
Published in Bioengineering
by Iglesias, CF, Ristovski, M, Bolic, M, Cuperlovic-Culf, M
This is a survey paper about machine learning models for rAAV manufacturing.
Download PaperManuscripts
Monitoring the Recombinant Adeno-Associated Virus Production using Extended Kalman Filter
Published in Processes
by Iglesias Jr, CF, Xu, X, Mehta, V, Akassou, M, Venereo-Sanchez, A, Belacel, N, Bolic, M
This paper monitors the rAAV production using the online viable cell density measurements and estimating the other state variables measured at a low frequency.
Download PaperConferences
Handling Massive Proportion of Missing Labels in Multivariate Long-Term Time Series Forecasting
Published in Journal of Physics: Conference Series
by Iglesias, J. C., Mehta, V., Venereo-Sanchez, A., Xu, X., Robitaille, J., Voyer, R., others
This paper handles situation where there are sparse labels for training machine learning forecast models for time series.
Download PaperResearchers
Principal Investigator
Academic Collaborators
| Researcher Name | University/Institute | Position |
|---|---|---|
| M. Cuperlovic-Culf | NRC, Canada | Senior Research Officer |
Industrial Partners
| Company Name | Location |
|---|---|
| National Research Council Canada (NRC) | Ottawa, Canada |