May 31, 2021 | News | Workshop
Migration and Mobility Research in the Digital Era (MIMODE 2021)
The recent availability of massive amounts of digital data have profoundly revolutionized research on migration and mobility, enabling scientists to quantitatively study individual and collective mobility patterns at different granularities as generated by human activities in their daily life. Harnessing such digital data offers many new opportunities to study migration and mobility and fill in the gaps left by traditional data. At the same time, such innovative data sources also come with several limitations, biases, and challenges, which have led to diverging research methodologies and frameworks, requiring even greater effort in their operationalization and communication to stakeholders and policy makers.
The aim of this satellite session is to bring together researchers from different fields and practitioners from around the world to facilitate a conversation on the use of innovative digital data sources, new methodologies, empirical findings, and critical challenges of studying migration and mobility in the digital era.
Topics of interest include, but are not limited to:
- New data sources for mobility and migration research, challenges and opportunities
- Internal and international migration, short- and long-term mobility
- Modeling and predicting human mobility patterns
- Machine learning and AI methods for studying mobility
- Longitudinal analyses and empirical studies of mobility and migration
- Socio-economic and environmental drivers of migration
- Integration and segregation of migrant populations
- Measuring the impact of natural disasters, conflicts, climate change, and the COVID-19 pandemic on migration
- Access to mobility data, open science, and privacy concerns
- Evaluation and development of migration policy
Call for Abstracts
We welcome submissions of abstracts on ongoing or published work that fit the topics of the event. The submissions must be a single PDF-file of maximum 2 pages in English including the title, list of authors and affiliations, abstract text (maximum 500 words), descriptive figure or table (optional), and references (optional). The abstracts can be in any format or style as long as they do not exceed the page and word limits. Alternatively, authors can use the abstract template of the main conference (click here to view our optional formatting template).
Abstracts must be submitted electronically by July 17, 2021, through the Easychair platform at the following link: easychair.org/conferences
All submissions will be evaluated by the Program Committee on the basis of quality and fit to the satellite theme.
Oral presentations will be allocated 12 minutes, followed by 5 minutes of Q&A. Please note that the presenting author must register to the main conference as announced on CCS2021 website.
July 17, 2021 — Deadline for abstract submissions (midnight CET)
July 30, 2021 — Notification of abstract acceptance for oral presentation
October 27, 2021 — MIMODE 2021 satellite
Registration & Venue
MIMODE 2021 is a satellite of the Conference on Complex Systems CCS2021, and will take place in Lyon (and online) on October 27, 2021.
Satellite participants (with or without abstract submission) will have to register following the procedure described in the CCS2021 conference website: ccs2021.univ-lyon1.fr/#REGISTRATION
Presenting authors can indicate their availability to travel to Lyon in October 2021 in the submission platform. We will consider researchers’ needs and organize our satellite event accordingly as we approach the date of the event. More details will follow soon.
The conference venue will be the Lyon Convention Centre named Cité | Centre de Congrès | Lyon and located in
50 quai Charles De Gaulle
69463 Lyon Cedex 06
To know more about the venue, please visit the conference website: ccs2021.univ-lyon1.fr/#CONVENTION-CENTER
© courtesy of Joshua Blumenstock
Joshua Blumenstock is an Associate Professor at the U.C. Berkeley School of Information, the Director of the Data-Intensive Development Lab, and the faculty co-Director of the Center for Effective Global Action. His research lies at the intersection of machine learning and empirical economics, and focuses on developing new computational approaches to better understand the causes and consequences of global poverty.
Joshua has a Ph.D. in Information Science and a M.A. in Economics from U.C. Berkeley, and Bachelor’s degrees in Computer Science and Physics from Wesleyan University. He is a recipient of an NSF CAREER award, the Intel Faculty Early Career Honor, a Gates Millennium Grand Challenge award, a Google Faculty Research Award, and the U.C. Berkeley Chancellor's Award for Public Service. His work has appeared in a variety of publications including Science and Nature, as well as top economics journals (e.g., the American Economic Review) and computer science conferences (e.g., ICML, KDD, AAAI, WWW, CHI).
© courtesy of Vanessa Frias-Martinez
Vanessa Frias-Martinez is an associate professor in the iSchool and UMIACS, and an affiliate associate professor in the Department of Computer Science at the University of Maryland (UMD) where she also leads the Urban Computing Lab. Frias-Martinez's research areas are data-driven behavioral modeling and spatio-temporal data mining. Her research focuses on the use of large-scale ubiquitous data to model the interplay between human mobility patterns, social networks and the built environment. Specifically, Frias-Martinez develops methodologies to model and predict human behaviors in different contexts as well as tools to aid decision makers in areas such as poverty, natural disasters or urban planning. Before coming to UMD, she spent five years at Telefonica Research developing algorithms to analyze mobile digital traces. Frias-Martinez is the recipient of a National Science Foundation (NSF) CAREER Award and a La Caixa Fellowship. She received her PhD in Computer Science from Columbia University.
© courtesy of Andy Tatem
Andy Tatem is Professor of spatial demography and epidemiology at the University of Southampton and is the Director of WorldPop (www.worldpop.org), leading a group of 30 researchers and data scientists. He is interested in how populations, their characteristics and their dynamics can be mapped at high resolution across low and middle-income countries. His research has led to pioneering approaches to the use and integration of satellite, survey, cell phone and census data to map the distributions and movement patterns of vulnerable populations for disease, disaster and development applications. He runs international collaborations with national governments, UN agencies and data providers, and leads multiple research and operational projects funded by the Bill and Melinda Gates Foundation, Wellcome Trust, World Bank, GAVI, Clinton Health Access Initiative and others.
- Albert Ali Salah, University of Utrecht
- Alessandro Sorichetta, University of Southampton
- Alexander Kustov, Princeton University
- Alina Sîrbu, University of Pisa
- Andrea Milan, IOM’s Global Migration Data Analysis Centre
- Andrea Miranda-Gonzalez, UC Berkeley
- Archana Roy, International Institute for Population Sciences (IIPS)
- Arkadiusz Wiśniowski, University of Manchester
- Aude Bernard, University of Queensland
- Bruno Lepri, Fondazione Bruno Kessler
- Carlos Arcila, USAL
- Chiara Boldrini, IIT-CNR
- Elin Charles-Edwards, University of Queensland
- Emanuele Del Fava, Max Planck Institute for Demographic Research
- Emilio Zagheni, Max Planck Institute for Demographic Research
- Emmanuel Olamijuwon, University of the Witwatersrand
- Floriana Gargiulo, GEMASS - CNRS and University of Paris Sorbonne
- Francesco Rampazzo, University of Oxford
- Francisco Rowe, University of Liverpool
- Giulio Rossetti, KDD Lab ISTI-CNR
- Guy Stecklov, University of British Columbia
- Hannah Postel, Princeton University
- Ingmar Weber, Qatar Computing Research Institute
- Jakub Bijak, University of Southampton
- John Palmer, Pompeu Fabra University
- José-Javier Ramasco, Institute for Cross-Disciplinary Physics and Complex Systems
- Kailash Chandra Das, International Institute for Population Sciences (IIPS)
- Katherine Hoffmann Pham, New York University
- Kiran Garimella, MIT
- Laura Alessandretti, Technical University of Denmark
- Laura Pollacci, University of Pisa
- Leo Ferres, Universidad del Desarrollo & Telefónica R&D
- Luca Pappalardo, ISTI-CNR
- Marc Barhelemy, Institute of Theoretical Physics
- Mark Ellis, University of Washington
- Michael Szell, IT University of Copenhagen
- Michele Tizzoni, ISI Foundation
- Miranda Jessica Lubbers, Autonomous University of Barcelona
- Niklas Sievers, IOM Global Migration Data Analysis Centre (GMDAC)
- Noemi Derzsy, AT&T Labs
- Qiang Fu, University of British Columbia
- Raffaele Vacca, University of Florida
- Ram B Bhagat, International Institute for Population Sciences
- Rajesh Sharma, University of Tartu
- Siiri Silm, University of Tartu
- Sk Karim, International Institute for Population Sciences
- Sophie Muetzel, University of Lucerne
- Victoria Prieto-Rosas, University of the Republic
- Yao Robert Djogbenou, University of Montreal
- Yuan Hsiao, University of Washington
Daniela Perrotta, Research Scientist, Laboratory of Digital and Computational Demography, MPIDR.
Daniela completed her PhD in Complex Systems for Life Sciences at the University of Turin with a fellowship at the Lab. of Digital and Computational Epidemiology at the ISI Foundation in Italy. Her research focuses on harnessing innovative data-collection schemes and computational methods for modeling human mobility and disease spread, including leading a collaborative effort to collect and evaluate health behavioural data during the COVID-19 pandemic leveraging large-scale Facebook surveys.
© Samin Aref
Samin Aref, Research Scientist, Laboratory of Digital and Computational Demography, MPIDR.
Samin has worked on modeling and analyzing the migration of researchers using large-scale bibliometric data with geographical focus on Mexico, Russia, the United Kingdom, and Germany. Samin holds a PhD in Computer Science from the University of Auckland and has been Research Area Chair of Migration and Mobility at the MPIDR.
© Jisu Kim
Jisu Kim, Research Scientist, Laboratory of Digital and Computational Demography, MPIDR.
Jisu holds a PhD in Data Science from Scuola Normale Superiore in Italy. She has worked on exploring and establishing novel methods to improve relevant statistics of international migration using social media data. Her research focuses on the intersection of migration sciences, economics of migration, complex social networks, statistical models and data-driven algorithms.
Contact the Organizers