Nokia Foundation Grant for Ella Peltonen, Kumaripaba Athukorala & Matti Nelimarkka
Nokia foundations has been granting scholarships to support scientific development of information and telecommunications technologies for the last twenty years.
This year three researchers of the Computer Science department of University of Helsinki have been awarded the Nokia scholarship: Ella Peltonen, Matti Nelimarkka, and Kumaripaba Athukorala.
Award ceremony was held at Nokia Solution Experience Center on 24th November.
We congratulate Ella, Matti, and Kumaripaba.
The titles of their projects and abstracts are given below.
Ella Peltonen
Title: Iterative Data Analysis for Sensing Applications
Smartphones and other sensor devices can generate large amounts of data in a short time. Even if their computing capacity and battery lifetime can be limited, they usually have good communication capabilities, so that they can take advantage of remote services. Large-scale data analysis offers methodology, which can be used to improve functionality of the applications and extend the user activity. This creates a need for an iterative data analysis system, which offers streaming processing, data flow management, and machine learning algorithms suitable for complex sensing data.
PhD research of Ella Peltonen aims to develop principles and practices for an iterative data analysis algorithms and workflow. As a case study, we have presented a mobile application that measures context factors’ combined impact to energy consumption. This approach will be useful for different types of cases, where it is important to understand complex data sources in real time. In the future work, Ella will apply similar methodology to sensing human behavior patterns in collaboration with University College London, where she will spend five months in 2016.
Kumaripaba Athukorala
Title: Enhancing Exploratory Search with User Modeling
Search can be broadly divided into two types: lookup search, where the user has a specific search result in mind such as finding the exchange rate of a currency, and exploratory search, where the goal is to learn or investigate a less familiar topic or area.
Lookup searches are well supported by all the existing IR systems. However, exploratory search is found to be very challenging to the user, because users lack knowledge to formulate search queries and recognize relevant results, at the same time the user is uncertain about her own search goals. Due to this uncertainty in search goals, during the course of an exploratory search activity, users constantly change their information needs and thus expect more diverse results and better support from the search system. In spite of the importance and prevalence of exploratory search, the study of user behavior in such tasks and challenges they face have received much less attention.
Modeling user behavior in exploratory search is a hard problem to solve.