PhD in DATA ANALYTICS AND DECISION SCIENCES - 34th cycle · 2020-04-17 · PhD in DATA ANALYTICS...

PhD in DATA ANALYTICS AND DECISION SCIENCES -

34th cycle

Number of scholarship offered 4

DepartmentDIPARTIMENTO DI ELETTRONICA, INFORMAZIONE EBIOINGEGNERIA

Description of the PhD Programme

La grande quantità di dati raccolta attraverso i nuovi media e la disponibilità a memorizzarli edelaborarli a un costo relativamente contenuto hanno dato una forte spinta al settore del dataanalytics, che negli ultimi anni ha visto una crescita esponenziale. Questo ha fatto nascere ilbisogno di esperti con conoscenze approfondite (ben oltre la laurea magistrale) in diversi settori,in grado di lavorare in un ambito altamente interdisciplinare, adattandosi ai rapidi cambiamenti delsettore. Questo dottorato nasce per formare figure di senior data scientist attraverso uno studioapprofondito delle discipline e la partecipazione a ricerche di punta nell¿ambito della data scienceintegrando conoscenze di diversi settori disciplinari. Queste figure dovranno essere in grado diacquisire conoscenza dei fenomeni in gioco, di modellarli e realizzarli adeguatamente, dianalizzare criticamente i risultati prodotti per eventualmente guidare un processo di trasferimentotecnologico che le analisi potrebbero suggerire. Il dottorato si articola in tre anni, il primo dedicatoai corsi proposti e i successivi al lavoro di tesi. I corsi sono progettati per fornire una solidapreparazione interdisciplinare nelle diverse aree di ricerca che fanno parte della data science. Unperiodo obbligatorio di studio all¿estero e la partecipazione a scuole dottorali, conferenzeinternazionali, consente agli studenti di sviluppare una rete di relazioni che ne facilita la crescitaprofessionale.

Stampato il 16/04/2018 1 / 1


34th cycle

Research Field: DATA ANALYTICS AND DECISION SCIENCES

Monthly net income of PhDscholarship (max 36 months)

€ 1300.0In case of a change of the welfare rates during the three-year period, the amount could be modified.

Context of the research activity

Motivation and objectives of the researchin this field

The PhD program in Data Analytics and DecisionSciences aims at breeding the next generation of datascientists who will tackle the challenges and theopportunities created by the increasingly larger availabilityof data, cheap storage, and computer power. Datascientists who can capture the most relevant aspects ofphenomena in play, develop adequate models, supervisethe development of analytic pipelines, critically analyzethe result, and support the technological transfer that theresults might enable.

Methods and techniques that will bedeveloped and used to carry out theresearch

The research aims at developing novel approaches fordata analytics and decision science including novelstatistical methods for complex data, new econometricsetups, methods of advanced machine learning, as wellas technological solutions to integrate massive amount ofdata from heterogeneous data sources.

Educational objectives

The research will be carried out in collaboration with theteam of applied statisticians, economists, computer andmanagement engineers from three departments, theDepartment of Management, Economics and IndustrialEngineering, the Department of Mathematics, and theDeparment of Electronics, Information andBioengineering. Within this lively and stimulatingacademic and research environment, the doctoral studentwill be educated to become a skilful researcher in DataScience.

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Job opportunities

The profile of Data Scientist and the technological andmethodological solutions proposed are of interest for abroad range of actors, including International institutions,policy makers, statistical and research centres, largecorporations that aim to analyse heterogeneous datacoming from various datasources.

Composition of the research group

7 Full Professors7 Associated Professors2 Assistant Professors4 PhD Students

Name of the research directors Any faculty member

Contacts

PhD CoordinatorProf. Pier Luca LanziEmail: [email protected]: +390223993472

Additional support - Financial aid per PhD student per year (gross amount)

Housing - Foreign Students

1st year 2nd year 3rd year1500.0 €

per student1000.0 €


per student

max number of financial aid available: 1, given in order of merit (onlyfor students with scholarship)..

Housing - Out-of-town residents(more than 80Km out of Milano) --

Additional information: educational activity, teaching assistantship, computer availability, desk availability,any other information

Teaching AssistanshipThere are various forms of financial aid for activities of support to the teaching practice. The PhDstudent is encouraged to take part in these activities, within the limits allowed by the regulations.

Educational Activities

2nd year: max 1370,00 euro per student•

3rd year: max 1370,00 euro per student•

Computer Availability

2 / 3

1st year: individual use•

2nd year: individual use•

3rd year: individual use •

Desk availability


2nd year: individual use •

3rd year: individual use•

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34th cycle

Research Field: DATA ANALYTICS FOR IMPACT MEASUREMENT AND ECONOMIC

INTERDEPENDENCIES IN COMPLEX ECOSYSTEMS





The research focuses on the study of scalable statisticaland economic models to support the evaluation of thesocio-economic impacts generated by different economicagents, and to analyse the interdependencies thatcharacterize current complex ecosystems. The researchincludes the development of advanced data analyticsmethods that integrate both accounting (e.g., IO and EEIOdata) and socio-environmental data to study i) theeconomic and environmental impacts arising fromexternal shocks (e.g. strategic investments, environmentaldisasters¿), ii) the evolution of the ecosystems (in termsof technological and environmental conditions), iii) thecomparison of different ecosystems.


The project will develop novel statistical methods forcomplex data (e.g., matrices, networks and object data)and new econometric setups to (i) provide an innovativeperspective on the use of IO and EEIO matrices, and (ii)to gauge the uncertainty in the estimation of economicand socio-environmental multiplier effects and inforecasting future configurations.


The research will be carried out in collaboration with theteam of applied statisticians, economists, computer andmanagement engineers working in the Center for AnalysisDecision and Society of Human Technopole. Within thislively and stimulating academic and research

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environment, the doctoral student will be educated tobecome a skilful researcher in Data Science.

Job opportunities

The profile of Data Scientist and the applicationsproposed in this project are of interest to a broad range ofactors, including international institutions and researchcentres aiming to monitor the evolution of the competitiveand economic contexts; large corporations aiming tomeasure their contribution to their local ecosystems;policy makers.



Name of the research directors Prof. Azzone, Prof. Pammolli, Prof. Secchi

Contacts

Giovanni Azzone, [email protected], 0223993981,http://www.dig.polimi.it/index.php?id=238&tx_wfqbe_pi1[id]=1

Fabio Pammolli, [email protected], 0223999251,https://scholar.google.com/citations?user=qft7FqwAAAAJ&hl=it

Piercesare Secchi, [email protected], 0223994592,https://www.mate.polimi.it/?view=pp&id=85&lg=en






per student




List of Institutions Cooperating in the Research

Human Technopole•

Educational Activities2 / 3








Desk Availability




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34th cycle

Research Field: DATA INTEGRATION AND ANALYSIS IN HETEROGENEOUS

ENVIRONMENTS





Over the past 20 years the view of the data-relatedproblems has changed dramatically, moving to a Web-dominated world in which many different sources ofhowever structured information must interoperate, ideallyin a way that gives users a fully integrated view of them.This research focuses on the problems that derive fromthis scenario, aiming to study and design the means toaccess and analyze data coming from several sources ofinformation and to deal with heterogeneity, uncertainty,possible low-quality data with a view over them that is asunified as possible. In doing so, the research will also takeinto account basic ethical principles like fairness, non-discrimination, transparency, data protection, diversity,endeavouring to inject them into each step of the dataanalysis lifecycle (source selection, data integration, andknowledge extraction), so as to incorporate ethicsthroughout the design of the technology.


The project aims at providing a middleware that supportsthe combination of data coming from the different sourcesby leveraging existing middleware previously oriented tosupport the Internet of things, tailoring ethically-awareintegration views on the basis of a view adaptation factorthat takes into account the ethical context.

Educational objectives The research will be carried out in collaboration with the

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team of applied statisticians, economists, computer andmanagement engineers working in the Center for AnalysisDecision and Society of Human Technopole. Within thislively and stimulating academic and researchenvironment, the doctoral student will be educated tobecome a skilful researcher in Data Science.

Job opportunities

The profile of Data Scientist and the technological andmethodological solutions proposed are of interest for abroad range of actors, including International institutions,policy makers, statistical and research centres, largecorporations that aim to analyse heterogeneous datacoming from disparate datasources.



Name of the research directors Prof. Tanca, Prof. Azzone, Prof. Secchi

Contacts

Prof. Letizia Tanca, [email protected], 0223993531, http://tanca.faculty.polimi.it/

Prof. Giovanni Azzone, [email protected],0223993981,http://www.dig.polimi.it/index.php?id=238&tx_wfqbe_pi1[id]=1

Prof. Piercesare Secchi, [email protected],0223994592,https://www.mate.polimi.it/?view=pp&id=85&lg=en






per student





Human Technopole•2 / 3









Desk availability




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34th cycle

Research Field: HEALTHCARE RESEARCH IN A REAL WORLD EVIDENCE SETTING





Healthcare research is concerned with the study of thehuge amount of data and information produced by theclinical and administrative datawarehouses arising fromhealthcare context. In this huge amount data lies animmense potential for statistical learning which aims tosupport and inform policy making. If properly exploited,managed and integrated, such data may leads to a greatinnovation in epidemiology, pharmacoeconomics, clinicaland healthcare research in general.


The research will develop novel statistical methods forintegrated and massive healthcare data as well as neweconometric setups to (i) provide new insightful methodsfor outcome research; (ii) measure effectiveness ofprocedure and protocols of healthcare paths; (iii) performHTA on Real Word based datawarehouses; (iv) assesshealthcare providers performances and quantify therelated costs in different scenario analysis; (v) makepharmacoepidemiological and pharmacoeconomicalanalyses. Expertise in programming languages forstatistics (R, SAS or similar) is recommended.


The research will be carried out in close collaboration withthe team of applied statisticians, economists, computerand management engineers working in the Center forAnalysis Decision and Society of the Human Technopole.Within this lively and stimulating academic and researchenvironment, the student will be educated to become a

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skilful researcher in data science.

Job opportunities

The profile of Data Scientist and the applicationsproposed in this project are of interest to of a broad rangeof actors, including (but not limited to): public and privateinstitutions dealing with healthcare, clinical andpharmaceutical data, as well as international institutionsand research centres aiming at assessing performancesof healthcare providers, and policy makers in charge withhealthcare governance.



Name of the research directors Prof. Pammolli, Prof. Paganoni, Prof. Masella

Contacts

Prof. Fabio Pammolli, [email protected], 0223999251,https://scholar.google.com/citations?user=qft7FqwAAAAJ&hl=it

Prof. Anna Maria Paganoni, [email protected], 0223994574,https://www.mate.polimi.it/?view=pp&id=65&lg=it#ann

Prof. Cristina Masella, [email protected], 0223994081






per student





Human Technopole (HT)1.

CHRP - Center for Healthcare Research and Pharmacoepidemiology2.

UCL - University College of London3.

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SOSE - Soluzioni per il Sistema Economico pubblico e privato4.




Teaching assistanshipThere are various forms of financial aid for activities of support to the teaching practice. The PhDstudent is encouraged to take part in these activities, within the limits allowed by the regulations.

Computer availability




Desk availability




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PhD in DATA ANALYTICS AND DECISION SCIENCES - 34th cycle · 2020-04-17 · PhD in DATA ANALYTICS...

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