Francisco M. Couto is currently an associate professor with habilitation at FCUL. He graduated (2000) and has a (2001) in Informatics and Computer Engineering Francisco M. Couto is currently an associate professor with habilitation at Universidade de Lisboa (Faculty of Sciences) and a researcher at LASIGE. He graduated (2000) and has a master (2001) in Informatics and Computer Engineering from IST. He concluded his doctorate (2006) in Informatics, specialization Bioinformatics, from the Universidade de Lisboa. He was an invited researcher at EBI, AFMB-CNRS, BioAlma during his doctoral studies. Until 2023, he published 2 books; was co-author of 10 chapters, 65 journal papers (49 Q1 Scimago), and 33 conference papers (10 core A and A*); and was the supervisor of 11 PhD theses and of 53 master theses. At that same date, he had more than 6 thousand citations with an h-index of 37 at Google Scholar. He received the Young Engineer Innovation Prize 2004 from the Portuguese Engineers Guild, and an honorable mention in 2017 and the prize in 2018 of the ULisboa/Caixa Geral de Depósitos (CGD) Scientific Prizes.

Springer Book Livro Gradiva

In 2019, he published a book entitled Data and Text Processing for Health and Life Sciences that provides a step-by-step introduction on how shell scripting can help solve many of the data and text processing tasks that Health and Life specialists face everyday with minimal software dependencies. An adaptation of the book in Portuguese entitled Introdução à Bioinformática Via Linha de Comando was also published in 2019. The book is particularly relevant to Health and Life specialists or students that want to easily learn how to process data and text, and which in return may facilitate and inspire them to acquire deeper bioinformatics skills in the future.

With a diverse research portfolio spanning bioinformatics, knowledge management, and information retrieval, he has contributed significantly to the advancement of various fields, including semantic similarity, ontology matching, relation extraction, and named entity recognition and linking, with a particular focus on biomedical applications. Among his most recent and significant achievements is the development of innovative models such as K-RET for incorporating biomedical ontology information into Large Language Models (LLMs), and NILINKER for addressing unlinkable entities in Named Entity Linking systems. His expertise also extends to the assembly of biological networks, where he emphasizes the importance of reliable interactions extracted from scientific literature using text mining approaches. Through his research, he seeks to enhance our understanding of complex biological systems, including the study of complex diseases such as autism, and facilitate the development of more accurate and personalized computational models.

Furthermore, he has participated in many challenges, such as BioCreative, BioASQ, SemEval, ACM KDD Cup, and OAEI, achieving top-performing submissions. Most recently, he joined the LitCoin NLP Challenge, a component of the NASA Tournament Lab (NTL) in collaboration with Unicage. This challenge aimed to deploy data-driven technology solutions to expedite scientific research in medicine and harness biomedical publications for a broad spectrum of researchers. His collaborative effort with Unicage resulted in being awarded the 7th Prize out of approximately 200 participating teams, earning a cash prize of 5,000 USD. This success underscored the fruitful synergy between academia (LASIGE) and industry (Unicage), showcasing the potential for knowledge transfer from his research domains to practical applications, benefiting diverse sectors.