Three new researchers have recently joined LaSTUS lab, under the supervision of Prof. Horacio Saggion. We are delighted to have them on board, and that TALN continues to grow and innovate. Let's meet them:

Piotr Przybyła (pictured, left) is an NLP researcher focusing on text credibility assessment. Previously, he has worked as a postdoctoral researcher at the University of Manchester and Institute of Computer Science (Polish Academy of Sciences). He joins TALN thanks to the EU-funded Marie-Skłodowska Curie Postdoctoral Fellowship, aimed to increase researcher mobility across Europe. His 2-year research project, ERINIA, is aimed at improving our understanding on how NLP models detecting misinformation content (fake news, bots, propaganda, etc.) perform in an adversarial setting. 

Kemalcan Bora (pictured above) is doing a Ph.D. in the Department of Information and Communication Technologies at Universitat Pompeu Fabra. His field of research is recipe generation from food images under the Large-Scale Text Understanding Systems Lab at the Natural Language Processing (TALN) research group under the supervision of Professor Horacio Saggion. He holds a master's degree in management information systems from the University of Yıldırım Beyazıt, where his thesis was a comparative study of convolutional neural network features for detecting breast cancer. He also has 7 years of developer experience and has worked for some global companies such as AGCO, Wise, and Coca-Cola.

Nicolau Duran (pictured above) will work on a Industrial PhD[ca/es only link] project at the Large-Scale Text Understanding Systems Lab at the Natural Language Processing (TALN) research group with the company SIRIS Academic, which is a knowledge-intensive company that offers consultancy, analysis and evidence-based services to provide support, inform and improve the decision-making process for public R&D&I policies for domains of higher education, research and innovation. He did his bachelor's degree in Computer Science at Universitat Pompeu Fabra, and a master's degree in Language Technologies at UNED. The topics of research during his PhD are information extraction from scientific and technical documents, when no (or limited) labelled data is available, text simplification with heterogeneous documents, and how to provide data-driven evidence to policies for domains of higher education, research and innovation, regional development.

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