About Me

I am a Ph.D. student at the Faculty of Informatics of Università della Svizzera italiana (USI), Lugano, Switzerland, working under the supervision of Prof. Silvia Santini. I am a member of Mobile Computing and Sensing Systems (MCSS) research group from September 2017. I have joined the MCSS group in September 2016 for my Master's thesis on "Studying the Physiological Synchrony Between Teachers and Students During Lectures Using Mobile and Wearable Devices". In June 2017, I received my Master's degree in Informatics from USI. I obtained my Bachelor degree in Computer Science from City College, International Faculty of University of Sheffield, Thessaloniki, Greece, in June 2014.

Research

My research interests lie on ubiquitous and affective computing. In particular, I am interested in using data collected from sensors available in devices we use in our daily lives such as e.g., smartphones, smartwatches and sensory earbuds, to automatically and unobtrusively recognise human behavior. In the context of my Ph.D. thesis, I focus on design and development of robust mobile sensing systems, which are able to accurately detect people's behavior in real-world settings and act accordingly to support their work performance and well-being.

I have developed automatic methods for detection of artifacts in physiological signals collected using wearable devices in uncontrolled settings. In another project, I have used wearable devices to monitor the physiological signals, such as heart rate and electrodermal activity, of presenter and audience members during presentations of a conference. We have shown that presenters and audience's physiological signals synchrony reflects their agreement on self-reported engagement. Automatic quantification of users' agreement on engagement during a presentation can be useful for presenters to assess the effectiveness of their presentation to the audience and audience members, on the other hand, can understand which presentations they felt most engaged with.

Projects

Automatic Detection of Artifacts in Electrodermal Activity Data

Publications: [1]

Students' Engagement in Classroom

Publications: [6], [5] and [9]

Presenter and Audience's Engagement

Publications: [4] and [8]

Laughter Recognition

Publications: [3]

Cooking Activity Recognition

Publications: [2]

Social Media Usage and Mood

Publications: [7]

Publications

Please refer to my Google Scholar page here.

[1] S. Gashi, E. Di Lascio, B. Stancu, V. Das Swain, V. Mishra, M. Gjoreski, and S. Santini. 2020. Detection of Artifacts in Ambulatory Electrodermal Activity Data. In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (PACM IMWUT), Vol. 4, Issue 2, June 2020.

[2] S. Gashi, E. Di Lascio, S. Santini: Multi-class Multi-label Classification for Cooking Activity Recognition. To Appear in Smart Innovation, Systems and Technologies Series of Springer Books, Human Activity Recognition Challenge, June 2020.

[3] E. Di Lascio, S. Gashi and S. Santini: Laughter Recognition Using Non-invasive Wearable Devices. In: Proceedings of the 13th EAI International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), May 2019.

[4] S. Gashi, E. Di Lascio, S. Santini: Using Unobtrusive Wearable Sensors to Measure the Physiological Synchrony Between Presenters and Audience Members. In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (PACM IMWUT), Vol. 3, Issue 1, March 2019.

[5] E. Di Lascio, S. Gashi, S. Santini: Unobtrusive Assessment of Students’ Engagement During Lectures Using Electrodermal Activity Sensors. In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (PACM IMWUT), Vol. 2, Issue 3, September 2018.

[6] S. Gashi, E. Di Lascio, S. Santini: Using Students' Physiological Synchrony to Quantify the Classroom Emotional Climate. In: Adjunct Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2018). (Best Paper Award).

[7] H. Zhang, S. Gashi, H. Kimm, E. Hanci, and O. Matthews. Moodbook: An Application for Continuous Monitoring of Social Media Usage and Mood. In: Adjunct Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2018).

[8] S. Gashi. Unobtrusive Recognition of Socio-Affective Dynamics During Human Interactions Using Wearables and Smartphones. In: Adjunct Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2018).

[9] E. Di Lascio, S. Gashi, D. Krasic, S. Santini: In-classroom Self-tracking for Teachers and Students: Preliminary Findings from a Pilot Study. In: Adjunct Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2017).

Teaching

As a Ph.D. student at USI, I have been a teaching assistant for the following courses.

Course Instructor Programme Semester
S&DE Atelier: Visual Analytics Dr. Marco D'Ambros Master of Science in Software & Data Engineering Spring 2018/2019/2020
Data Design & Modeling Prof. Marco Brambilla Master of Science in Software & Data Engineering Fall 2018/2019