Honorable mention as one of the three finalist papers for the INCOM Best Paper Award 2018 for the contribution ** A data-driven districting to improve emergency medical service systems** presented by E. Lanzarone (IMATI-Milan) and authored by F. Regis-Hernandez (previous post-doc at IMATI-Milan), E. Lanzarone (IMATI-Milan), V. Bélanger and A. Ruiz.

IFAC INCOM 2018 Conference, Bergamo, June 2018.

Wednesday 13/6/2018 at 2:30 p.m. **Prof**. **Stefano Favaro**

Protection against disclosure is a legal and ethical obligation for statistical agencies releasing microdata files for public use. Given a cross classification of sample records by categorical key variables, any decision about release is supported by measures of disclosure risk, the most common being the number τ of sample uniques cells that are also population uniques. In this paper we depart from the dominant literature that infers τ by modeling association among key variables, and we consider modeling directly sample records. We develop a novel nonparametric Bayesian approach under the minimal assumption of a generalized Dirichlet prior for the random partition induced by the cross-classified sample records. This allows to derive an explicit, and simple, expression for the posterior distribution of τ, as well as a large sample Binomial approximation of it. Such a closed-form results, combined with an estimator for prior parameters designed in such a way to recognizes a primary role of small cells, make inference on τ exact, of easy implementation, computationally efficient and scalable to massive datasets. The proposed approach is tested on benchmark data from the U.S. 2000 census for the state of California, showing the same good performance of recent semiparametric Bayesian models for key variables.

Presso: Sala Pentagonale II Piano Via Bassini 12 20133 Milano

Tuesday, 5 June 2018,

* 3 p.m. (sharp),**Dr. Giorgio Saracco**, Università degli Studi di Pavia

at the conference room of IMATI-CNR in Pavia, will give a lecture titled:

The Cheeger problem and an application to the (constant) Prescribed Mean Curvature problem

* 4 p.m. (sharp)**Dr. Stefano Almi,** TUM Monaco

will give a lecture titled:

Energy release rate and stress intensity factors in planar elasticity in presence of smooth cracks

as part of the Applied Mathematics Seminar (IMATI-CNR e Dipartimento di Matematica, Pavia).

Thursday, 7 June 2018, 3 p.m. (sharp),

**Dr. Robert Lasarzik**, WIAS Berlino

at the conference room of IMATI-CNR in Pavia, will give a lecture titled:

Generalized solution concepts to the Ericksen-Leslie equations modeling liquid crystal flow

as part of the Applied Mathematics Seminar (IMATI-CNR e Dipartimento di Matematica, Pavia).

At the end a refreshment will be organized.

Giovedì, 31 Maggio 2018

Aula B, via Alfonso Corti 12, Milano, Italy

15:00-16:00

**Non-homogeneous Inference Using Dynamic Bayesian Networks: Minimising the Impact of Dredging on Seagrass Ecosystems**

Il Dott. Wu è uno dei due relatori, insieme alla Prof.ssa Kerrie Mengersen (QUT), della scuola estiva ABS18 (Applied Bayesian Statistics) su

BAYESIAN STATISTICAL MODELLING AND ANALYSIS IN SPORT che si terrà la prossima settimana a Como e per cui sono ancora

disponibili alcuni posti: http://www.mi.imati.cnr.it/conferences/abs18/index.html

It is challenging to predict the dynamic response of a complex system to stressors due to interdependencies and interactions between multiple system components under uncertainty. Potentially, the behaviour of the system itself can change over time as a result of exogeneous inputs and/or changes to the system state. For instance, an ecosystem that has already been subjected to stress may respond differently to further stresses, such as a reduced ability to resist and recover. Such changing dynamics are characteristic of non-homogeneous complex systems.

Dynamic Bayesian Networks (DBNs) provide an approach for predictive, whole-of-systems modelling of complex systems under uncertainty. Here, we discuss an approach to non-homogeneous inference with DBNs. The method enables dynamic updates of DBN parameters and inference of posterior marginal probabilities by propagating the effect of observations forwards in time. It also enables approximate inference for forwards-backwards inference. The approach is demonstrated on evaluating dredging impacts on seagrass ecosystems, with discussion on broader application to other domains.

Tuesday, 29 May 2018, 3 p.m. (sharp),

**prof. Massimo Fornasier,** TUM Monaco

at the conference room of IMATI-CNR in Pavia, will give a lecture titled:

Consistency of probability measure quantization by means of power repulsion-attraction potentials

as part of the Applied Mathematics Seminar (IMATI-CNR e Dipartimento di Matematica, Pavia).

At the end a refreshment will be organized.

Friday, 25 May 2018, 10.30 a.m.,

**Dr. Raphaelle Chaine**,

at the conference Leonardo room of IMATI-CNR in Genova, will give a lecture titled:

**Quasi-uniform triangulations for virtual sculpture**

Tuesday, 22 May 2018, 3 p.m. (sharp),

**Dr. Antonio De Rosa**, Courant Institute

at the conference room of IMATI-CNR in Pavia, will give a lecture titled:

Sharp regularity for weak notions of surfaces

as part of the Applied Mathematics Seminar (IMATI-CNR e Dipartimento di Matematica, Pavia).

At the end a refreshment will be organized.