NCSR Demokritos & Qualco foster Innovation through Education

 

 

NCSR Demokritos and Qualco, a leader in providing technology solutions and services that cover the full range of loan and credit management lifecycle, are pleased to announce their collaboration for the promotion of innovation, utilising Artificial Intelligence and Big Data management technologies to meet business challenges in the field of financial technology (Fintech).

NCSR Demokritos & Qualco launch the NCSR D – Qualco Fellowship programme which supports young researchers to delve into their research in the Fintech field using AI and Big Data, two of the research areas that the Institute of Informatics and Telecommunications is extremely active.

 

The NCSR D – Qualco Fellowship programme

 

NCSR Demokritos & Qualco currently offer three (3) fellowships to PhD (2) and Post Doc (1) researchers in two domains.

Domain 1

Utilising unstructured, semi-structured and fully structured data to empower fintech analysis

A wealth of information exploitable for fintech analysis is available in various levels of structure: from databases and data warehouses, to XML and HTML documents to free text, this wealth can be challenging to capture, classify and -in the end- utilise effectively. This domain undertakes research on methods that identify, extract and organise rich information from different sources with varying structure in their data, rendering them useful in fintech processes.

Suggested topics for Post Doc/PhD Research

  • Text analytics in blended semi-structured and structured (big) data for (dynamic) predictive modelling in the financial domain
    • Feature engineering
    • Deep embeddings
  • Unstructured natural language processing (NLP) and text mining as significant features for the identification of opportunities and risks in the financial domain, e.g.
    • Sentiment analysis
    • Argument mining

Domain 2

Tapping into natural language as an information source for fintech

In direct and indirect expression, humans produce a multitude of signals usable in processes such as customer support, sales, human resources, negotiation and other settings. This domain undertakes research on methods that employ natural language processing (NLP) and related disciplines to harness the knowledge transferred through explicit and implicit language signals, to support fintech products and services including decision support and real-time analytics.

Suggested topics for Post Doc/PhD Research

  • Conversation (multi-modal) sentiment analysis
  • Speech summarisation in Fintech context
  • Argument mining from textual conversations
  • Utilising NLP for intelligent, real-time, interactive analytics and pattern identification on Fintech data

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