Workshop 2022
EMbeDS Workshop 4 July 2022, 9:00 - 5 July 2022, 19:00
Our world is characterized by globalization, financialization, deepening inequalities and mounting environmental issues. It is also characterized by a growing availability of massive, diverse datasets, and of increasingly sophisticated statistical and computational tools to gather and analyze them. EMbeDS overarching goal is to bring Economics and Management in the era of Data Science, leveraging data and tools to bridge the gaps that still exist between complex models, their empirical validation, and their use in policy.
The EMbeDS 2022 workshop will celebrate the final year of activity of the Department of Excellence with presentations by our extended EMbeDS community and a variety of national and international scholars. Speakers will tackle a variety of topics including climate change and its impacts; sustainability; health care; methodological advances in modeling, computation and statistics; and societal issues linked to the use of massive data and AI.
There is no fee for participating, but please register HERE so that we can keep an accurate count of participants and contact you with updates and additional information as needed.
Please indicate on the registration form if you have any food restrictions/allergies (describing the dietary restrictions) and if you agree to make the recording of the event public. After registering, you will receive a link that will allow you to participate to the meeting online if you wish to do so.
A book of abstracts (in pdf) can be downloaded at the end of this page.
A detailed program of the event, which will be held in Aula Savi, Botanical Garden of Pisa, on July 4-5, 2022, is provided below (and in attachment at the end of this page):
4 JULY 2022
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Videos: Morning, Keynote lecture - password required
- Slides: here
09:00am gathering of participants (coffee and pastries available)
9:15am Welcome and short remarks by Francesca Chiaromonte
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Morning Sessions
I. 9:30am-11:00am Computational approaches for process-oriented data analysis, simulations of large agent-based models, and statistical model checking. Chair: Andrea Vandin.
Adelinde Uhrmacher, Rostock University, Germany. Valid agent-based models - requirements and implications. (in remote).
Andrea Burattin, DTU Technical University of Denmark. Process-oriented Data Science: a gentle overview on Process Mining.
Andrea Vandin, Sant’Anna School of Advanced Studies, Italy. Simulation models meet Process Mining: a novel approach to model validation and enhancement.
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11:00am-11:30pm Coffee break
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II. 11:30pm-01:30pm Economic theory and learning processes. Chair: Daniele Giachini
Jonathan Newton, Kyoto University, Japan. Asymmetric behavior and long run outcomes.
Filippo Massari, University of Bologna, Italy. Good biases bad biases.
Pietro Dindo, Cà Foscari University of Venice, Italy. Learning models from prices.
Giulia Livieri, Scuola Normale Superiore, Italy. Analysis of Bank Leverage Via Dynamical Systems and Deep Neural Networks .
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01:30pm-3:00pm Light lunch
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Afternoon Sessions
III. 03:00pm-05:00pm Joint panel session with the Summer School of the PhD AI & Society
Francesca Chiaromonte, Sant'Anna School of Advanced Studies, Italy and Penn State University , USA.
Rita Cucchiara, University of Modena and Reggio Emilia, Italy.
Fosca Giannotti, Scuola Normale Superiore Italy.
Michela Milano, University of Bologna , Italy.
Mariarosaria Taddeo, Oxford University , UK.
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05:00pm-5:30pm Coffee break
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IV. 5:30-6:30 Keynote lecture. Chair: Francesca Chiaromonte
Marzia Cremona, Université Laval, Canada. Local clustering and motif discovery of functional data: applications in “omics”, biomedical sciences and finance .
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6:30-8.00 Guided tour of the botanical garden
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5 July 2022
9:00am gathering of participants (coffee and pastries available)
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Morning Sessions
V. 9.30 am-11:00am Science Technology and Innovation. Chair: Andrea Mina
Gaétan de Rassenfosse, Ecole Polytechnique Fédérale de Lausanne, Switzerland. The commercialization of DoD-SBIR patents: A counterfactual analysis.
Martina Iori, Sant’Anna School of Advanced Studies, Italy; and Jacopo Di Iorio, Statistics Department, Penn State University, USA. Local economies and specialization trajectories: A dynamic analysis from a Complexity Economics perspective.
Giorgio Tripodi, Sant’Anna School of Advanced Studies. Quantifying knowledge spillovers from advances in negative emissions technologies
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11:00am-11:30pm Coffee break
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VI. 11:30pm-1:00pm Climate risk and economic dynamics. Chair: Francesco Lamperti
Antoine Mandel, Sorbonne and PSE, France. Modelling climate-related financial risks.
Maximilian Kotz, Potsdam Institute for Climate Impact Research (PIK), Germany. Macroeconomic climate damages - resolving the locality of climate impacts in time and space.
Matteo Coronese, Sant’Anna School of Advanced Studies, Italy. Who will carry the climate burden? Heterogeneous impacts of climate anomalies on income classes and sectors. (in remote)
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1:00pm-2:00pm Light lunch
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Afternoon Sessions
VII. 2.00 pm-3.00pm Panel: Fostering Data and Computation-driven Interdisciplinary Research. Chair: Andrea Mina
Jenni Evans, Penn State University, USA.
Francesca Ieva, Human Technopole and Politecnico di Milano, Italy.
Francesca Chiaromonte, Sant'Anna School of Advanced Studies, Italy and Penn State University , USA.
VIII. 3:00pm-4:30pm Statistical approaches for the analysis of large and structured data. Chair: Francesca Chiaromonte
Luca Insolia, Sant’Anna School of Advanced Studies, Italy. Simultaneous feature selection and outlier detection with optimality guarantees.
Tobia Boschi, IBM Research Dublin, Ireland. High-dimensional functional regression: an efficient method for feature selection and estimation.
Ephraim Hanks, Penn State University, USA. Understanding and mitigating spatial confounding in spatially-referenced health data. (in remote).
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4:30pm-5:00pm Coffee break
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IX: 5:00– 6:30 Causal inference and its applications in healthcare. Chair: Chiara Seghieri
Marcella Vigneri, London School of Hygiene and Tropical Medicine, UK. Hand hygiene policies, strategies and interventions across settings: A scoping review across domains to identify knowledge (in remote).
Falco Bargagli, Harvard University, USA. Causal Rule Ensemble: A general ensemble learning framework for interpretable subgroups identification with an application in discovering heterogeneous exposure effects in air pollution studies.
Bénédicte Colnet, Inria Paris-Saclay, France. How can we account for sampling bias in randomized controlled trials? (in remote)
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6:30pm Francesca Chiaromonte, EMbeDS Scientific Coordinator. Goodbyes.
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VIDEOS: If interested in watching the video recordings of the event, please write to embeds@santannapisa.it
