Vision


We see Artificial Intelligence as a main means for the development of a more inclusive society, enabling a better quality of life. The starting and end point of our research is human
values and the study of how to improve the life of human beings, individually and collectively, through technology. According to our vision,
intelligent machines should understand the world in the same way as humans and use this knowledge to help them in
their social relations and interactions with the world. At the same time, humans should help machines
in helping humans, thus creating a positive loop of mutual growth. We call our stance,
Computational Humanism.

The ultimate success of Computational Humanism would be to make it possible
for everybody to exploit, in their everyday life, the best expertise available in the world.
Each person would be augmented with the knowledge and skills of any other person in the planet.

ƧMAЯTRAMS
Our goal is to develop systems which
live in symbiosis with their reference person, perceive the world as it is
needed to satisfy their reference person goals, and support them in his/her decision making.

Additional material:
The future of AI: a few insights into the possible futures of Artificial Intelligence, Computational Humanism

Technology

The i-Log system

Smartphone Sensors

The i-Log mobile application has been designed to collect data from the smartphone's internal sensors (details). The user is always informed of the data collection process thanks to a notification (details).

User Feedback

Periodically the user is asked to validate the sensor data by replying to very simple questions describing what he/she is doing (details). Questions can be answered immediatly or in a later moment but up to a certain time period.

Privacy Aware

All the data are collected in compliance with the EU Privacy laws. From a technical point of view, all the collected data are linked with a random unique identifier (details) that does not allow to link the data with the user who generated it.

Android Devices

The i-Log mobile application has been designed for Android devices. An iOS version is in development.

Easy to use

i-Log is very easy to use. The user can even not interact with the application at all. It starts when the phone boots and terminates when the battery is too low.

Battery Efficient

It is well known that using the phone to collect data is a battery intensive task. We designed the algorithms implemented in i-Log to be energy efficient and to affect the phone usability minimally, allowing to reach a full day battery life.

Projects

The list of sub-projects of ƧMAЯTRAMS.

ƧMAЯTKNOWDIVE

Internal Knowdive group experiment

ƧMAЯTUNITN

Involving bachelor students from Unitn

ƧMAЯTTN

Involving the municipality of Trento

About

What is the story so far

  • October 2015

    Great minds think alike

    Our team starts to assemble to bring i-Log to sociological studies. So, a first idea of ƧMAЯTUnitn is proposed.

  • March 2016

    ƧMAЯTKNOWDIVE is first proposed to test the capabilities and robustness of i-Log.

  • October 2016

    ƧMAЯTKNOWDIVE

    ƧMAЯTKNOWDIVE starts and acts as a test bed for future projects. It makes us cut our teeth on 20 users and shows great promise!

  • November - December 2016

    ƧMAЯTUNITN First Trial

    The ƧMAЯTUNITN first trial starts with 72 students and will last for two weeks. Students provide us a huge amount of high quality data thanks to i-Log.

  • September - October 2017

    ƧMAЯTUNITN Second Trial

    The second trial of ƧMAЯTUNITN is expected to start with a larger sample of students and collecting their emotions with experience sampling.

  • December 2017

    ƧMAЯTTN comes to life

    ƧMAЯTTN will begin its first deployment in the municipality of Trento, involving up to 10.000 citizens.

Our Team

You need ƧMAЯT people for a ƧMAЯT project

Fausto Giunchiglia

Full Professor @ Unitn

April 2015 -
ƧMAЯTRAMS

Andrea Passerini

Associate Professor @ Unitn

April 2017 -
ƧMAЯTRAMS

Mattia Zeni

Ph. D. Student @ Unitn
(Solution Architect)
April 2015 -

ƧMAЯTRAMS

Enrico Bignotti

Ph. D. Student @ Unitn
(Philosopher)

April 2015 -
ƧMAЯTRAMS

Ivan Kayongo

Master Student @ Unitn
ƧMAЯTRAMS
(Developer)

April 2017 -

Liviu Bogdan

Master Student @ Unitn
ƧMAЯTRAMS
(Developer)

April 2017 -


Ivano Bison

Associate Professor @ Unitn
ƧMAЯTUNITN
April 2015 -

Elisa Gobbi

Ph. D. student in Sociology @ Unitn
ƧMAЯTUNITN
April 2015 -

Paolo Poppi

Municipality of Trento
ƧMAЯTTN

Publications

  • [1] M. Zeni, I., Zaihrayeu, and F. Giunchiglia, "Multi-device activity logging", In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 299-302, ACM, 2014. (Download)
  • [2] F. Giunchiglia, E. Bignotti, and M. Zeni, "Personal context modelling and annotation", In Pervasive Computing and Communications, 2017 IEEE International Conference on , 2017. (Download)
  • [3] F. Giunchiglia, E. Bignotti, and M. Zeni, "Human-Like Context Modelling for Robot Surveillance", In Semantic Computing (ICSC), 2017 IEEE 11th International Conference on, pp. 360-365, 2017. (Download)
  • [4] F. Giunchiglia, M. Zeni, E. Gobbi, E. Bignotti and I. Bison, "Mobile Social Media and Academic Performance", In the 9th International Conference on Social Informatics (SocInfo 2017), Springer, pp. 360-365, 2017. (Download)
  • [5] F. Giunchiglia, E. Bignotti, and M. Zeni, "Human-Like Context Sensing for Robot Surveillance", In Semantics for Engineering and Robotics, Special Issue of the International Journal of Semantic Computing (IJSC), Vol. 11, N. 03. Extended version of [3]. (Download)

Contact Us

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