At UCL I am Deputy Director of the Leverhulme Doctoral Training Programme for the Ecological Study of the Brain, a member of the Steering and Executive Board of the UCL Institute of Digital Health and a member of the UCL Academic Centre of Excellence for Cyber Security Research (ACE-CSR). I am also the Director of the UCL Master in Geospatial Analysis.
The first cohort of Ph.D. students of the cross-disciplinary Ecological Brain Doctoral Training Centre funded by Leverhulme Trust started in October 2018. The focus of the centre is the study of the brain and human behaviour in-the-wild. There will be another intake in October 2019. If you are interested please get in touch.
I will be giving a talk on “Identification (and Obfuscation) in the Smartphone Era” at the 2nd International Workshop on Personal Analytics and Privacy in conjunction with ECML PKDD 2018.
I joined the Editorial Board of ACM Computing Surveys.
I joined the Editorial Board of IEEE Pervasive Computing as Associate Editor in Chief.
I joined the Editorial Board of the ACM Transactions on the Internet of Things.
I am currently involved in the following upcoming scientific events. Please consider submitting your work to and attending these conferences and workshops:
- 17th ACM International Conference on Mobile Systems, Applications and Services (ACM MobiSys 2019) [Program Committee Member]
- 13th International AAAI Conference on Web and Social Media (AAAI ICWSM 2019) [Senior Program Committee Member]
- 24th ACM International Conference on Intelligent User Interfaces (ACM IUI 2019) [Program Committee Member]
- 24th ACM International Conference on Mobile Computing and Networking (ACM MobiCom 2018) [Program Committee Member]
- 2018 ACM International Conference on Pervasive and Ubiquitous Computing [Member of the Editorial Board of the associated ACM IMWUT Journal and Workshop co-Chair]
- 3rd ACM International Workshop on Mental Health and Wellbeing: Sensing and Intervention at ACM UbiComp’18 [Program Committee Member]
- 7th ACM International Workshop on Pervasive Urban Applications (PURBA’18) at ACM UbiComp’18 [Program Committee Member]
The focus of the work of my lab is on the design of next-generation intelligent systems based on computational models of human behaviour and social dynamics. I am interested in both theoretical and systems-oriented aspects. In other words, I enjoy investigating theoretical foundations and models, and then using them in a variety of applications, including the development of real-world systems.
Areas of interest include:
- Design and implementation of intelligent systems;
- Computational and mathematical models of human behaviour and social systems (using mobile data, sensor and Internet of Things data, social media and other user-generated content, etc.) and their applications;
- Ubiquitous computing and mobile systems;
- Applied machine learning;
- Data science&AI for social good;
Learning through Probing: a Decentralized Reinforcement Learning Architecture for Social Dilemmas
Nicolas Anastassacos and Mirco Musolesi
Submitted for Publication. Preprint available on arXiv: arXiv:1809.10007
Interpretable Machine Learning for Privacy-Preserving Pervasive Systems
Benjamin Baron and Mirco Musolesi
Submitted for Publication. Preprint available on arXiv: arXiv:1710.08464
Characterizing Animal Movement Patterns Across Different Scales and Habitats using Information Theory
Kehinde Ayodeji Owoeye, Mirco Musolesi and Stephen Hailes
Submitted for Publication. Preprint available on biorXiv: bioRxiv:311241
Intelligent Notification Systems: A Survey of the State of the Art and Research Challenges
Abhinav Mehrotra and Mirco Musolesi
Submitted for Publication. Preprint available on arXiv: arXiv:1711:10171
Using Unsupervised Deep Autoencoders to Automatically Extract Mobility Features for Predicting Depressive States
Abhinav Mehrotra and Mirco Musolesi
Accepted for Publication in Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT). To be presented in the Research Track of 2018 International Joint Conference on Pervasive and Ubiquitous Computing (ACM UbiComp’18). Singapore. October 2018. To Appear.
Analyzing and Predicting the Spatial Penetration of Airbnb in U.S. Cities
Giovanni Quattrone, Andrew Greatorex, Daniele Quercia, Licia Capra and Mirco Musolesi
In EPJ Data Science. Volume 7. Issue 31. Springer. September 2018.
Precise Time-matching in Chimpanzee Allogrooming does not Occur After a Short Delay
Steve Phelps, Wing Lon Ng, Mirco Musolesi and Yvan I. Russell
In PLOS ONE. Volume 13. Issue 9. e0201810. September 2018.
The Hidden Image of Mobile Apps: Geographic, Demographic, and Cultural Factors in Mobile Usage
Ella Peltonen, Eemil Lagerspetz, Jonatan Hamberg, Abhinav Mehrotra, Mirco Musolesi, Petteri Nurmi and Sasu Tarkoma
In Proceedings of the 20th International ACM Conference on Human-Computer Interaction with Mobile Devices and Services (ACM MobileHCI 2018). Barcelona, Spain. September 2018.
A Comparison of Spatial-based Targeted Disease Containment Strategies using Mobile Phone Data
Stefania Rubrichi, Zbigniew Smoreda and Mirco Musolesi
In EPJ Data Science. Volume 7. Issue 17. Springer. June 2018.
You are your Metadata: Identification and Obfuscation of Social Media Users using Metadata Information
Beatrice Perez, Mirco Musolesi and Gianluca Stringhini
In Proceedings of the 12th International AAAI Conference on Web and Social Media (ICWSM 2018). Palo Alto, CA, USA. June 2018.
Predicting the Temporal Activity Patterns of New Venues
Krittika D’Silva, Anastasios Noulas, Mirco Musolesi, Cecilia Mascolo and Max Sklar
In EPJ Data Science. Volume 7. Issue 13. Springer. May 2018.
Personal Informatics Tools Benefit from Combining Automatic and Manual Data Capture in the Long-Term
Nora Ptakauskaite, Anna Cox, Mirco Musolesi, Abhinav Mehrotra, James Cheshire and Chiara Garattini
In Proceedings of the ACM CHI Workshop on Next Steps Towards Long Term Self Tracking. Colocated with ACM CHI 2018. Montreal, Canada. April 2018.
Towards Deep Learning Models for Psychological State Prediction using Smartphone Data: Challenges and Opportunities
Gatis Mikelsons, Matthew Smith, Abhinav Mehrotra and Mirco Musolesi
In Proceedings of the NIPS Workshop on Machine Learning for Healthcare 2017 (ML4H’17). Colocated with NIPS’17. Long Beach, California, USA. December 2017.
Upcoming office hours:
Monday 22 October 1-2pm
Friday 26 October 3-5pm
Last updated: 21 October 2018.