Browsing Chemical Engineering by Supervisor "Budman, Hector"
Now showing items 1-12 of 12
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Application of Deep Learning in Chemical Processes: Explainability, Monitoring and Observability
(University of Waterloo, 2022-01-04)The last decade has seen remarkable advances in speech, image, and language recognition tools that have been made available to the public through computer and mobile devices’ applications. Most of these significant ... -
Application of Flow Cytometry and Fluorescence Spectroscopy to Monitor and Predict the Fermentation Activity in a Vaccine Manufacturing Process
(University of Waterloo, 2019-01-07)Bordetella pertussis is a Gram-negative coccobacillus, pathogenic and aerobic bacterium responsible for causing whooping cough, which is an upper respiratory tract infection in humans. To prevent this disease whole cellular ... -
Classification Algorithms based on Generalized Polynomial Chaos
(University of Waterloo, 2016-01-22)Classification is one of the most important tasks in process system engineering. Since most of the classification algorithms are generally based on mathematical models, they inseparably involve the quantification and ... -
Deep Recurrent Neural Networks for Fault Detection and Classification
(University of Waterloo, 2018-12-20)Deep Learning is one of the fastest growing research topics in process systems engineering due to the ability of deep learning models to represent and predict non-linear behavior in many applications. However, the application ... -
Dynamic Latent Structured Data Analytics for Process Modeling and Monitoring
(University of Waterloo, 2023-10-11)With the advent of Industry 4.0, variable relations in modern industrial processes are increasingly complex due to their high dimensions and complex auto-correlations and cross-correlations. Multivariate statistical methods ... -
Empirical, Mechanistic and Hybrid Models for Mammalian Cell Cultures
(University of Waterloo, 2021-09-27)To reach the increasing demand for monoclonal antibodies the pharmaceutical industry has been looking into ways to optimize productivity. Monoclonal antibodies (mAb) are commonly synthesized in mammalian cell cultures. ... -
Identification of Dynamic Metabolic Flux Balance Models Based on Parametric Sensitivity Analysis
(University of Waterloo, 2016-06-15)A dynamic mathematical model that involves a set of physicochemical parameters can describe a dynamic system. Parametric sensitivity analysis studies the effect of changes in these parameters on model outputs of interest. ... -
Improving Productivity in Bioreactors through Control of Cell Heterogeneity
(University of Waterloo, 2022-12-22)Whooping cough, also referred to as pertussis, is a highly contagious bacterial respiratory tract disease. At Sanofi Pasteur, the fermentation step in the manufacturing of the vaccine for pertussis involves a sequence of ... -
Modeling and State Estimation of Bio-processes using Dynamic Flux Balances
(University of Waterloo, 2023-05-16)Due to the increasing demand for bio-pharmaceuticals, optimization of bio-processes' productivity and reduction of process variability have become critical goals for manufacturers. Mathematical models of the fermentation ... -
Robust Nonlinear Model Predictive Control of Biosystems described by Dynamic Metabolic Flux Models
(University of Waterloo, 2019-05-13)The accuracy of the model used for prediction in Nonlinear Model Predictive Controller (NMPC) is one of the main factors affecting the closed loop performance. Since it is impossible to formulate a perfect model for a real ... -
Run-to-Run Optimization of Biochemical Batch Processes in the Presence of Model-Plant Mismatch
(University of Waterloo, 2018-01-18)An increased demand for novel pharmaceuticals such as recombinant proteins with therapeutic potential has lead to significant advances in the operation of biotechnological processes. In general, biochemical processes are ... -
Systematic Approaches to Identification of Dynamic Flux Balance Models
(University of Waterloo, 2018-06-11)Mathematical modelling of biological systems is an essential tool for better understanding and for optimizing biological processes. Simulating the experiments before performing them is a time-saving strategy when seeking ...