- Position:
- Researcher
PhD student
- Department:
- Department of Information Engineering and Process Control (DIEPC)
- Room:
- NB 647
- eMail:
- Home page:
- https://www.uiam.sk/~mojto
- Phone:
- +421 259 325 349
- ORCID iD:
- 0000-0002-6114-2710
- WoS ResearcherID:
- AAZ-3608-2020
- Google Scholar:
- sjBbi0AAAAAJ
- Availability:
-
Personal Information
Scientific Interest
- Data treatment, detection of outliers, and systematic errors
- Hotelling's T2 distance, minimum covariance determinant, k-means clustering
- More information: paper (CACE 2021)
- Design of inferential (soft) sensors using data-driven methods:
- Ordinary Least Squares (OLS)
- Principal Component Analysis (PCA)
- Partial Least Squares (PLS)
- Least Absolute Shrinkage and Selection Operator (LASSO)
- Subset Selection (SS)
- More information: article, poster, video
- Detection of systematic errors and outliers within an industrial dataset:
- Visual gross error detection
- Hotelling's T-squared distance
- Minimum Covariance Determinant (MCD)
- k-means clustering
- Industrial applications:
- Fluid Catalytic Cracking (FCC) Unit - Slovnaft
- Vacuum Gasoil Hydrogenation (VGH) Unit - Slovnaft
- Advanced control of industrial distillation columns
Education
- Doctoral Studies (1.9.2019–now)
- Thesis topic: Plant-wide Optimization and Predictive Control in an Oil Refinery
- Supervisor: doc. Ing. Radoslav Paulen, PhD.
- Programme: Process Control
- Master's Degree (01.09.2017–27.05.2019)
- Thesis topic: Advanced Process Control of a Depropanizer Column
- Supervisor: prof. Ing. Miroslav Fikar, DrSc.
- Programme: Automation and Information Engineering in Chemistry and Food Industry
- Bachelor's Degree (01.09.2014–11.07.2017)
- Thesis topic: Simulation of Azeotropic Distillation
- Supervisor: doc. Ing. Pavol Steltenpohl, PhD.
- Programme: Chemical Engineering
Martin Mojto
Martin Mojto