Modeling and predicting human behavior in AmI environments
Key words: middleware, ubiquitous computing, distributed systems, event-based systems
Description: Smart applications anticipate typical human behavior. A key to effectively predict human behaviour and act proactively is the ability to create models of individual or group behaviour from a variety of data obtained from sensors and other low-level events.
While user profiles are being used extensively in ubiquitous computing applications, there are various shortcomings and limitations related to the expressiveness of the models, and to the dynamic construction and updating of the models. These models also lack support for context-dependent inference and prediction of most-likely future behaviour of a single individual or a group as a whole.
In this PhD project, the candidate will investigate techniques to model, mine, and learn routines in order to recognize human behavior and activities within a particular context or situation. The methodology shall be based on event-based evidence of interactions with smart systems and state-of-the-art complex event processing techniques to identify relevant patterns.
The goal of this research is to be able to predict and proactively anticipate the most likely future behaviour of an individual or a group as a whole. The research will be carried out in the area of e-health applications and ambient assistent living.
Applicants should have a MSc in computer science or similar and should be highly motivated to work in the field of software engineering and be familiar with the principles of event-based systems. Basic knowledge of middleware for distributed systems and AI algorithms for prediction and learning is strongly encouraged.
Latest application date: 2011-10-01
Financing: available
Type of Position: scholarship
Duration of the Project : 4 years
Research group: Department of Computer Science
Scientific Supervisors: Yolande Berbers, Professor at K.U.Leuven, and Davy Preuveneers, postdoctoral researcher at K.U.Leuven
http://distrinet.cs.kuleuven.be/people/showMember.do?memberID=u0006685
http://distrinet.cs.kuleuven.be/people/showMember.do?memberID=u0038519
Additional Information: K.U.Leuven, which is situated at about 20 kilometers from Brussels, is the oldest and largest university of the Low Countries. It is a highly ranked university doing top research. It has a long-standing tradition of hospitality towards students and scholars from abroad. At present, almost 4,000 international students (about 10% of the total number of students at K.U.Leuven) have found their home away from home in Leuven.
How to apply: see http://phd.kuleuven.be/set/voorstellen_departement?departement=50000525
Link:
Modeling and predicting human behavior in AmI environments
Key words: middleware, ubiquitous computing, distributed systems, event-based systems
Description: Smart applications anticipate typical human behavior. A key to effectively predict human behaviour and act proactively is the ability to create models of individual or group behaviour from a variety of data obtained from sensors and other low-level events.
While user profiles are being used extensively in ubiquitous computing applications, there are various shortcomings and limitations related to the expressiveness of the models, and to the dynamic construction and updating of the models. These models also lack support for context-dependent inference and prediction of most-likely future behaviour of a single individual or a group as a whole.
In this PhD project, the candidate will investigate techniques to model, mine, and learn routines in order to recognize human behavior and activities within a particular context or situation. The methodology shall be based on event-based evidence of interactions with smart systems and state-of-the-art complex event processing techniques to identify relevant patterns.
The goal of this research is to be able to predict and proactively anticipate the most likely future behaviour of an individual or a group as a whole. The research will be carried out in the area of e-health applications and ambient assistent living.
Applicants should have a MSc in computer science or similar and should be highly motivated to work in the field of software engineering and be familiar with the principles of event-based systems. Basic knowledge of middleware for distributed systems and AI algorithms for prediction and learning is strongly encouraged.
Latest application date: 2011-10-01
Financing: available
Type of Position: scholarship
Duration of the Project : 4 years
Research group: Department of Computer Science
Scientific Supervisors: Yolande Berbers, Professor at K.U.Leuven, and Davy Preuveneers, postdoctoral researcher at K.U.Leuven
http://distrinet.cs.kuleuven.be/people/showMember.do?memberID=u0006685
http://distrinet.cs.kuleuven.be/people/showMember.do?memberID=u0038519
Additional Information: K.U.Leuven, which is situated at about 20 kilometers from Brussels, is the oldest and largest university of the Low Countries. It is a highly ranked university doing top research. It has a long-standing tradition of hospitality towards students and scholars from abroad. At present, almost 4,000 international students (about 10% of the total number of students at K.U.Leuven) have found their home away from home in Leuven.
How to apply: see http://phd.kuleuven.be/set/voorstellen_departement?departement=50000525<
Country: Belgium
