Materials Map

Discover the materials research landscape. Find experts, partners, networks.

  • About
  • Privacy Policy
  • Legal Notice
  • Contact

The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

×

Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

To Graph

1.080 Topics available

To Map

977 Locations available

693.932 PEOPLE
693.932 People People

693.932 People

Show results for 693.932 people that are selected by your search filters.

←

Page 1 of 27758

→
←

Page 1 of 0

→
PeopleLocationsStatistics
Naji, M.
  • 2
  • 13
  • 3
  • 2025
Motta, Antonella
  • 8
  • 52
  • 159
  • 2025
Aletan, Dirar
  • 1
  • 1
  • 0
  • 2025
Mohamed, Tarek
  • 1
  • 7
  • 2
  • 2025
Ertürk, Emre
  • 2
  • 3
  • 0
  • 2025
Taccardi, Nicola
  • 9
  • 81
  • 75
  • 2025
Kononenko, Denys
  • 1
  • 8
  • 2
  • 2025
Petrov, R. H.Madrid
  • 46
  • 125
  • 1k
  • 2025
Alshaaer, MazenBrussels
  • 17
  • 31
  • 172
  • 2025
Bih, L.
  • 15
  • 44
  • 145
  • 2025
Casati, R.
  • 31
  • 86
  • 661
  • 2025
Muller, Hermance
  • 1
  • 11
  • 0
  • 2025
Kočí, JanPrague
  • 28
  • 34
  • 209
  • 2025
Šuljagić, Marija
  • 10
  • 33
  • 43
  • 2025
Kalteremidou, Kalliopi-ArtemiBrussels
  • 14
  • 22
  • 158
  • 2025
Azam, Siraj
  • 1
  • 3
  • 2
  • 2025
Ospanova, Alyiya
  • 1
  • 6
  • 0
  • 2025
Blanpain, Bart
  • 568
  • 653
  • 13k
  • 2025
Ali, M. A.
  • 7
  • 75
  • 187
  • 2025
Popa, V.
  • 5
  • 12
  • 45
  • 2025
Rančić, M.
  • 2
  • 13
  • 0
  • 2025
Ollier, Nadège
  • 28
  • 75
  • 239
  • 2025
Azevedo, Nuno Monteiro
  • 4
  • 8
  • 25
  • 2025
Landes, Michael
  • 1
  • 9
  • 2
  • 2025
Rignanese, Gian-Marco
  • 15
  • 98
  • 805
  • 2025

Polikarpova, Nadia

  • Google
  • 1
  • 6
  • 41

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2020Program synthesis by type-guided abstraction refinement41citations

Places of action

Chart of shared publication
James, Michael
1 / 4 shared
Guo, Zheng
1 / 4 shared
Jhala, Ranjit
1 / 1 shared
Wang, Ziteng
1 / 2 shared
Zhou, Jiaxiao
1 / 1 shared
Justo, David
1 / 1 shared
Chart of publication period
2020

Co-Authors (by relevance)

  • James, Michael
  • Guo, Zheng
  • Jhala, Ranjit
  • Wang, Ziteng
  • Zhou, Jiaxiao
  • Justo, David
OrganizationsLocationPeople

article

Program synthesis by type-guided abstraction refinement

  • James, Michael
  • Guo, Zheng
  • Jhala, Ranjit
  • Wang, Ziteng
  • Polikarpova, Nadia
  • Zhou, Jiaxiao
  • Justo, David
Abstract

<jats:p>We consider the problem of type-directed component-based synthesis where, given a set of (typed) components and a query<jats:italic>type</jats:italic>, the goal is to synthesize a<jats:italic>term</jats:italic>that inhabits the query. Classical approaches based on proof search in intuitionistic logics do not scale up to the standard libraries of modern languages, which span hundreds or thousands of components. Recent graph reachability based methods proposed for Java do scale, but only apply to monomorphic data and components: polymorphic data and components infinitely explode the size of the graph that must be searched, rendering synthesis intractable. We introduce<jats:italic>type-guided abstraction refinement</jats:italic>(TYGAR), a new approach for scalable type-directed synthesis over polymorphic datatypes and components. Our key insight is that we can overcome the explosion by building a graph over<jats:italic>abstract types</jats:italic>which represent a potentially unbounded set of concrete types. We show how to use graph reachability to search for candidate terms over abstract types, and introduce a new algorithm that uses<jats:italic>proofs of untypeability</jats:italic>of ill-typed candidates to iteratively<jats:italic>refine</jats:italic>the abstraction until a well-typed result is found.</jats:p><jats:p>We have implemented TYGAR in H+, a tool that takes as input a set of Haskell libraries and a query type, and returns a Haskell term that uses functions from the provided libraries to implement the query type. Our support for polymorphism allows H+ to work with higher-order functions and type classes, and enables more precise queries due to parametricity. We have evaluated H+ on 44 queries using a set of popular Haskell libraries with a total of 291 components. H+ returns an interesting solution within the first five results for 32 out of 44 queries. Our results show that TYGAR allows H+ to rapidly return well-typed terms, with the median time to first solution of just 1.4 seconds. Moreover, we observe that gains from iterative refinement over exhaustive enumeration are more pronounced on harder queries.</jats:p>

Topics
  • impedance spectroscopy