ACM SIGCHI Summer School on Computational Interaction

Alberto Monge Rofarello will participate to the 3rd ACM SIGCHI Summer School on Computational Interaction. The summer school will be held on Lake Lucerne in Switzerland, organized by ETH Zurich, from the 12th to the 17th of June 2017.

The goal of the summer school is to teach PhD students and researchers the foundations of computational tools in the context of user interface design and their application in interactive systems. In particular, the summer school will be organized around the common themes of optimization and machine learning. The first theme aims at solving interaction and user interface design problems by deriving interface configurations which satisfy constraints and maximize performance criteria. The latter theme, instead, introduces a principled and robust approach to designing a transformation from input to useful action.

The summer school will consist in a mix of theoretical lectures and pratical sessions, and it will close with a full-day hackaton.


Congratulations to Luigi De Russis, who has been selected as a member of the ACM Future of Computing Academy (FCA).

ACM FCA will lead the way in helping ACM develop new models of participation, collaboration, and career support. The Academy will advise on the problems ACM should tackle, how ACM should adapt to the needs of future generations as well as on how the computing field should evolve and where computing can help address challenging global issues.

Luigi will join an inaugural class of early career computing professionals, to shape the academy's governance structure and agenda. Moreover, he will attend the ACM celebration of 50 years of Turing Awards on June 23 - 24 at San Francisco.


CHI 2017 Logo

The e-Lite research group will participate to the ACM Conference on Human Factors in Computing Systems (CHI), one of the most important conference in the field of human-computer interaction. The 2017 edition will take place in Denver, Colorado, USA, from the 6th to the 11th of May.

Luigi De Russis and Alberto Monge Roffarello will present two late-breaking works on Monday and Tuesday (May 8-9) about notification preferences and end-user programming in the IoT.

Presentation of the thesis

The development of Internet of Things systems implies an increasing number of devices that interact with each user, every day and in every place. A growing need of programming, personalizing, and customizing the joint behavior of such devices by non-programmers is currently handled by rule-based programming platforms, such as IFTTT (if-this-then-that). Recent studies show that such platforms force the user to work at a "low-level" (i.e., at the device level), while end-users would prefer to work at a slightly more abstract level, where rules are more general and understandable.

The thesis of Fabio Ballati, discussed on March 2017, explores this field and proposes a methodology for automatically mapping low-level rules (e.g., extracted from IFTTT) onto a more abstract representation (high-level rules). The obtained translation process is fully automatic and relies on a dataset of IFTTT public rules.

The thesis analyses the rules present in the dataset with the aim of extracting the equivalent rules in the high-level representation, by producing a corresponding categorization of abstract IoT devices and services (i.e., by grouping objects for functionality, mainly). Then, a suitable algorithm was designed and implemented to perform the automatic mapping between the two representations, starting from the 200,000 low-level rules available in the dataset.

Finally, the thesis covered the validation of both the proposed mapping and the high-level representation. For validating the mapping procedure, the number of saved rules, per user, was computed: users in the dataset could compose 15%-33% less rules with the high-level representation, and still obtain the desired behavior for their IoT services. For validating the high-level representation, instead, a user study with 8 participants was carried out. The study asked participants for composing some rules in both the representations, starting from the description of some scenarios. As a result, participants largely prefer composing rules in the more abstract representation.


Poster used for presentation

The paper "Estimate user meaningful places through low-energy mobile sensing" presented by Teodoro Montanaro in the IEEE International Conference on Systems, Man, and Cybernetics 2016 was recently published in the IEEE Xplore Digital library.

Due to the increasing spread of location-aware applications, developers interest in user location estimation has grown in recent years. As users spend the majority of their time in few meaningful places (i.e., groups of near locations that can be considered as a unique place, such as home, school or the workplace), a new energy efficient method to estimate user presence in a meaningful place was presented in the published paper.

Specifically, instead of using commonly used but energy hungry methods such as GPS and network positioning techniques, the proposed method applies a Machine Learning algorithm based on Decision Trees, to predict the user presence in a meaningful place by collecting and analyzing: a) user activity, b) information from received notifications (receipt time, generating service, sender-receiver relationship), and c) device status (battery level and ringtone mode). The results demonstrate that, using 20 days of training data and testing the system with data coming from 14 persons, the accuracy (percentage of correct predictions) is 89.40% (standard deviation: 8.27%) with a precision of 89.04% and a recall of 89.40%. Furthermore, the paper analyzes the importance of each considered feature, by comparing the prediction accuracy obtained with different combinations of features.

On January 10, 2017, Howell Istance presented his Ph.D. thesis in a Viva session at the University of Loughborough (UK). The thesis title is "An investigation into gaze-based interaction techniques for people with motor impairments" and presents several research results, across a span of nearly 20 years, of investigation and experimentation in user interfaces bases on eye tracking, especially for persons with disabilities. Fulvio Corno was a member of the evaluation committee, together with prof. Penny StandenStanden and prof. Christopher Hinde (chair). The thesis was supervised by prof. Peter Howarth.