Usable Security Case Studies

Lecturer : 
Kristiina Karvonen
Event type: 
HIIT seminar
Event time: 
2010-12-13 13:15 to 14:00
Place: 
Computer Science Building, Room A328
Description: 

 Our next speaker for HIIT Otaniemi seminar series is Kristiina Karvonen from the "Usable Security, Privacy and Trust (USec)" group of the Helsinki Institute for Information Technology HIIT. Before her talk, she will also give a short overview on the research areas of the group.


All ICS@Aalto researchers are also warmly welcome to attend the seminar!

HIIT seminar Otaniemi, Monday December 13, 13:15
Location: Computer Science building, Room A328


Kristiina Karvonen
Usable Security, Privacy and Trust (USec) Group
Helsinki Institute for Information Technology HIIT

Title:
Usable Security Case Studies

Abstract:
Usable security is a field of study that aims to combine research in human computer interaction, security, privacy and trust. Areas of research include, for example, research on innovative security or privacy functionality and design, trust formation, field studies on the use of security or privacy technology, and usability evaluations of new or existing security or privacy features and technology. In my talk I will present an overview of the field and shortly present several case studies to give examples of research in this area.

Welcome!
-- 
Mehmet Gönen
Helsinki Institute for Information Technology HIIT
Aalto University, School of Science and Technology 
Department of Information and Computer Science

Clustering using the minimum description length principle

Lecturer : 
Panu Luosto
Event type: 
HIIT seminar
Event time: 
2010-12-10 10:15 to 11:00
Place: 
Kumpula Exactum C222
Description: 
Talk announcement:
HIIT Seminar Kumpula, Friday Dec 10, 10:15 a.m., Exactum C222

SPEAKER:
Panu Luosto
University of Helsinki

TITLE:
Clustering using the minimum description length principle

ABSTRACT:
Within a model class framework, the best model for data is according to
the minimum description length principle the one that leads to the most
efficient compression of the data in the worst case sense.  However,
many useful model classes have a property called infinite parametric
complexity, and in those cases an optimal solution cannot be defined in
a straightforward way.

This talk introduces one solution to the problem.  The resulting code
length functions are applied to two kinds of clustering applications.
In the first case, an unknown number of Gaussian clusters is searched
for in the presence of uniform background noise.  In the second
application, clustering with a richer variety of model classes is used
for one-dimensional density estimation.

BIO:
Panu Luosto is a PhD student under the supervision of Jyrki Kivinen in
the Department of Computer Science at the University of Helsinki.


Welcome!
--Matti Järvisalo

Mapping the Design Space for Ubimedia Services

Lecturer : 
Anu Kankainen
Event type: 
HIIT seminar
Event time: 
2010-12-01 14:30 to 15:30
Place: 
Computer Science Building, Room A328
Description: 

Our next speaker for HIIT Otaniemi seminar series is Anu Kankainen from the "Digital Content Communities (DCC)" group of the Helsinki Institute for Information Technology HIIT. Before her talk, she will also give a short overview on the research areas of the group.

All ICS@Aalto researchers are also warmly welcome to attend the seminar!

HIIT seminar Otaniemi, Wednesday December 1, 14:30
Location: Computer Science building, Room A328


Anu Kankainen
Digital Content Communities (DCC) Group
Helsinki Institute for Information Technology HIIT

Title:
Mapping the Design Space for Ubimedia Services

Abstract:
Docent Anu Kankainen, co-leader of DCC research group, will give a talk on what kind of role media services can have in everyday ubiquitous environments. DCC has done user research on people's everyday media practices in order to find opportunities for future ubimedia services. In her talk Anu will present examples of use situations for ubimedia. In general, media field is one of the most promising application areas for ICT. Media is in the era of digitalization. User stories will help us to understand the interplay of media and ICT in future.

Welcome!

-- 
Mehmet Gönen
Helsinki Institute for Information Technology HIIT
Aalto University, School of Science and Technology 
Department of Information and Computer Science

Reconstruction and evolution of gapless metabolic networks

Lecturer : 
Esa Pitkänen
Event type: 
HIIT seminar
Event time: 
2010-12-03 10:15 to 11:00
Place: 
Kumpula Exactum C222
Description: 

Talk announcement:
HIIT Seminar Kumpula, Friday Dec 3, 10:15 a.m., Exactum C222

SPEAKER:
Esa Pitkänen
University of Helsinki

TITLE:
Reconstruction and evolution of gapless metabolic networks

ABSTRACT:
Metabolism is the cellular subsystem responsible for generation of
energy from nutrients and production of building blocks for larger
macromolecules.  In this talk we will introduce gapless metabolic
networks as a model for biologically feasible metabolisms.  We will
concentrate on two prominent topics in metabolic modeling.  First, we
discuss algorithms for reconstructing gapless metabolic networks from
sequence data.  Reconstructed networks for observed species can then
be utilized to determine the evolutionary history of metabolic
networks by inferring gapless networks for ancestral species.  We will
also describe an on-going effort to apply these methods to large-scale
datasets.

BIO:
Esa Pitkänen is a PhD student at the Department of Computer Science,
University of Helsinki, in the Computational Systems Biology and
Bioinformatics group lead by Juho Rousu, and is currently working on
computational methods for metabolic modeling.


Welcome!
--Matti Järvisalo
 

Bayesian integration of multi-way, multi-species, and time-series metabolomic datasets

Lecturer : 
Ilkka Huopaniemi
Event type: 
HIIT seminar
Event time: 
2010-11-26 10:15 to 11:00
Place: 
Kumpula Exactum C222
Description: 
Talk announcement:
HIIT Seminar Kumpula, Friday Nov 26, 10:15 a.m., Exactum C222

SPEAKER:
Ilkka Huopaniemi
Aalto University

TITLE:
Bayesian integration of multi-way, multi-species, and time-series
metabolomic datasets


ABSTRACT:
Multi-way analysis of variance (ANOVA) - type methods are the default
tool for modelling the effects of multiple covariates (disease,
treatments, gender, time-series) in populations of (biomedical)
continues-valued measurements. I present a multivariate Bayesian
modelling framework for multi-way modelling, that can deal with the main
restriction of modern biomedical data: small sample-size and high
dimensionality. I then describe how we've extended this framework to
analyze data from novel biomedical multi-way experiment types: (i)
integrating multiple data sources, (ii) integrating data from multiple
species, and (iii) time-series experiment with mixed aging- and disease
progression effects.


BIO:
Ilkka Huopaniemi is a PhD student at the Department of Information and
Computer Science at Aalto University, in the Statistical Machine
Learning and Bioinformatics Group lead by Samuel Kaski. He received his
M.Sc. degree in 2006 from the Department of Technical Physics and
Mathematics of TKK, and did his Master's thesis in the Statistical
Physics group. He's research interests are multi-way experimental
designs, Bayesian methods, metabolomics, data integration, translational
modelling.

 

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