A5036653219- Advanced Multi-Objective Optimization Algorithms
- Metaheuristic Optimization Algorithms Research
- Anomaly Detection Techniques and Applications
- Context-Aware Activity Recognition Systems
- Evolutionary Algorithms and Applications
- RNA Research and Splicing
- Manufacturing Process and Optimization
- Human Mobility and Location-Based Analysis
- RNA modifications and cancer
- Probabilistic and Robust Engineering Design
- Molecular Biology Techniques and Applications
- Optimal Experimental Design Methods
- Gait Recognition and Analysis
Jožef Stefan Institute
2019-2024
Jožef Stefan International Postgraduate School
2022-2024
Cardiovascular disease (CVD) remains the leading cause of death worldwide and, despite continuous advances, better diagnostic and prognostic tools, as well therapy, are needed. The human transcriptome, which is set all RNA produced in a cell, much more complex than previously thought lack dialogue between researchers industrials consensus on guidelines to generate data make it harder compare reproduce results. This European Cooperation Science Technology (COST) Action aims accelerate...
The SHL recognition challenge 2020 was an open competition in activity where the participants were tasked with recognizing eight different modes of locomotion and transportation smartphone sensors. main challenges that training data recorded by a person than validation test data, location unknown to participants. We, team "Third time's charm", tackled first attempting identify persons clustering, then performed cluster/person-specific feature selection build separate classifier for each...
From 2018 to 2021, the Sussex-Huawei Locomotion-Transportation Recognition Challenge presented different scenarios in which participants were tasked with recognizing eight modes of locomotion and transportation using sensor data from smartphones. In 2019, main challenge was one location recognize activities sensors another location, while following year, person other persons. We use these two as a framework analyze effectiveness components machine-learning pipeline for activity recognition....
Exploratory landscape analysis (ELA) is a popular method for the understanding of complex, often black-box optimization problems. It tries to approximate and describe surfaces formed by fitness other characteristic values associated with problem solutions on top multi-dimensional solution spaces. Sampling initial step ELA pipeline. strategy selecting limited number solutions, i.e., points in space, which function(s) are evaluated. Consequently, approximated its properties drawn from these...