selected scholarly activity
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conferences
- Latent Variable Models and Big Data in the Process Industries. IFAC-PapersOnLine. 520-524. 2015
- Application of multivariate analysis of metabolic models for predictability of cell culture performance and quality attributes; an industry prospective. Food Pharmaceutical and Bioengineering Division 2013 Core Programming Area at the 2013 Aiche Annual Meeting Global Challenges for Engineering A Sustainable Future. 531. 2013
- Latent Variable MPC for trajectory tracking in batch processes: Role of the model structure. Proceedings of the American Control Conference. 4779-+. 2009
- Latent Variable Batch Predictive Control. AIChE Annual Meeting, Conference Proceedings. 2008
- Dynamic contrast‐enhanced MRI diagnostics in oncology via principal component analysis. Journal of Chemometrics. 708-716. 2008
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journal articles
- Setting simultaneous specifications on multiple raw materials to ensure product quality and minimize risk. Chemometrics and Intelligent Laboratory Systems. 157:96-103. 2016
- Erratum to “Robust multivariable identification: Optimal experimental design with contraints” [J. Process Control 16 (2006) 581–600]. Journal of Process Control. 22:944-944. 2012
- Image-based endpoint carbon prediction for a basic oxygen furnace. Iron and Steel Technology. 8:79-84. 2011
- Scale-up of a Pharmaceutical Roller Compaction Process Using a Joint-Y Partial Least Squares Model. Industrial & Engineering Chemistry Research. 50:10696-10706. 2011
- Modeling and Optimization of a Tablet Manufacturing Line. Journal of Pharmaceutical Innovation. 6:170-180. 2011
- Latent Variable Model Predictive Control (LV-MPC) for trajectory tracking in batch processes. Journal of Process Control. 20:538-550. 2010
- A Framework for the Development of Design and Control Spaces. Journal of Pharmaceutical Innovation. 3:15-22. 2008
- A novel approach for EIT regularization via spatial and spectral principal component analysis. Physiological Measurement. 28:1001-1016. 2007
- Fusion of sensory and mechanical testing data to define measures of snack food texture. Food Quality and Preference. 18:890-900. 2007
- Soft Sensor for Snack Food Textural Properties Using On-Line Vibrational Measurements. Industrial & Engineering Chemistry Research. 46:864-870. 2007
- Robust multi-variable identification: Optimal experimental design with constraints. Journal of Process Control. 16:581-600. 2006