LAMSADE: the last 5 yearstsoukias/papers/lamsade/... · 2017-11-26 · SWOT Conclusions Examples of science Axiomatisation of bibliometric indices Handbook of Computational Social

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Facts and ThoughtsSWOT

Conclusions

LAMSADE: the last 5 years

Alexis Tsoukiàs

HCERES, 23/10/2017

Alexis Tsoukiàs LAMSADE: the last 5 years

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Conclusions

Outline

1 Facts and Thoughts

2 SWOT

3 Conclusions


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Conclusions

Decision Sciences and Technologies

We do research for:Improving how people and devices “decide” as well asimproving how to help people and devices to “decide”.

Data, Information and KnowledgeAlgorithms and AgentsModels, Languages, TheoriesPractices


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Conclusions

Who are we?

2011: 43 researchers,30 PhD, 5 staff2016: 56 researchers,40 PhD, 5 staff13 nationalities, 18considering the PhDs40%women,40% international


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Conclusions

Who are we?

2011: 43 researchers,30 PhD, 5 staff2016: 56 researchers,40 PhD, 5 staff13 nationalities, 18considering the PhDs40%women,40% international


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Conclusions

Organisation


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Conclusions

LAMSADE in Dauphine

Data SciencesGame Theory

Economics and DecisionPeace StudiesLAMSADE

Policy AnalyticsManagement Science

DRM

IRISSO

LEDA

CEREMADE


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Conclusions

LAMSADE in Dauphine




DRM

IRISSO

LEDA

CEREMADE


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Conclusions

LAMSADE in Dauphine




DRM

IRISSO

LEDA

CEREMADE


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Conclusions

LAMSADE in Dauphine




DRM

IRISSO

LEDA

CEREMADE


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Conclusions

LAMSADE in Dauphine




DRM

IRISSO

LEDA

CEREMADE


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Conclusions

Science

3 papers/person/yearImproved QualityNice resultsCommunity leadersAttractiveness


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Conclusions

Science

3 papers/person/yearImproved QualityNice resultsCommunity leadersAttractiveness


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Conclusions

Examples of science

Axiomatisation of bibliometric indicesHandbook of Computational Social ChoiceFormal framework for super-polynomial approximationImproving the quality of Lovász theta functionsNew methods for “preferred solutions” in multi-objectiveoptimisationReducing costs of data integrationImproved machine learning algorithmsmonograph/book on process analytics, new models andcomplexity analysis for service selection and compositionproblem


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Conclusions

PhDs

established rules forallocationsinternationalrecrutementreturned to an average10 per year3,9 years averageduration


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Conclusions

PhDs

established rules forallocationsinternationalrecrutementreturned to an average10 per year3,9 years averageduration


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Conclusions

PhD funding and jobs


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Conclusions

Funding

Good financial resultsAutonomous creativemanagementWorrying trendGood science is notawardingGood selling andlobbying is awarding


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Conclusions

Funding

Good financial resultsAutonomous creativemanagementWorrying trendGood science is notawardingGood selling andlobbying is awarding


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Conclusions

Fund raising

Our PartnersRENAULT, Orange,SNCF, DCNS, Sagem ...Decision Brain, Coheris,Meta-Conseil, Agilab,Treize 37 ...Lyon Hospitals, Courdes Comptes, Conseild’État, CGEDD, IHEDN,HAS, INERIS, IRSN,IRSTEA ...


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Conclusions

Fund raising

Our PartnersRENAULT, Orange,SNCF, DCNS, Sagem ...Decision Brain, Coheris,Meta-Conseil, Agilab,Treize 37 ...Lyon Hospitals, Courdes Comptes, Conseild’État, CGEDD, IHEDN,HAS, INERIS, IRSN,IRSTEA ...


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Conclusions

Training

Doctoral SchoolMIDO: 2 research programs in Decision Sciences andIntelligent Systems and 3 Professional programs inComputer Science/Analytics/BusinessMSO: 2 Professional programs in Management ofInformation Systems and Peace StudiesLSO: Computer Science for all ...


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Conclusions

So what?

Strengths

Weaknesses

Attractiveness

Internal Differences

Clear Identity

Low risk taking

Clear Rules

Visibility and autonomy

Community Leadership

of projects

Good ScienceInterdisciplinarityInternationalisationReputation

Opportunities ThreatsDecision/Data/A.I. Job careersEuropean Training Private Research CompetitorsInterdisciplinary challenges PSL and Computer SciencePSL PIA2/PIA3 Research Funding


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Conclusions

So what?

Strengths WeaknessesAttractiveness Internal DifferencesClear Identity Low risk takingClear Rules Visibility and autonomyCommunity Leadership of projectsGood ScienceInterdisciplinarityInternationalisationReputation

Opportunities ThreatsDecision/Data/A.I. Job careersEuropean Training Private Research CompetitorsInterdisciplinary challenges PSL and Computer SciencePSL PIA2/PIA3 Research Funding


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Conclusions

So what?

Strengths WeaknessesAttractiveness Internal DifferencesClear Identity Low risk takingClear Rules Visibility and autonomyCommunity Leadership of projectsGood ScienceInterdisciplinarityInternationalisationReputationOpportunities

Threats

Decision/Data/A.I.

Job careers

European Training

Private Research Competitors

Interdisciplinary challenges

PSL and Computer Science

PSL PIA2/PIA3

Research Funding


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Conclusions

So what?

Strengths WeaknessesAttractiveness Internal DifferencesClear Identity Low risk takingClear Rules Visibility and autonomyCommunity Leadership of projectsGood ScienceInterdisciplinarityInternationalisationReputationOpportunities ThreatsDecision/Data/A.I. Job careersEuropean Training Private Research CompetitorsInterdisciplinary challenges PSL and Computer SciencePSL PIA2/PIA3 Research Funding


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Conclusions

Remarquable Facts

2014: 40 years of LAMSADE2015: 3rd area of LAMSADE; Data Sciences2016: EURO awards and AAMAS Best paper award2017: Bronze and Silver CNRS MedalsInterdisciplinarityIncreased visibility


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Conclusions

Conclusions

We are doing fair ...We can do much better ...But the system is not sustainable ...


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Conclusions

Thanks

to Eric Jaquet-LagrèzeFounding member, pioneer and friend (1947 - 2017)


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Conclusions

Thanks

to Eric Jaquet-LagrèzeFounding member, pioneer and friend (1947 - 2017)


Documents

LAMSADE: the last 5 yearstsoukias/papers/lamsade/... · 2017-11-26 · SWOT Conclusions Examples of science Axiomatisation of bibliometric indices Handbook of Computational Social