Fernando Manuel Marques Batista

Fernando Manuel Marques Batista is an Associate Professor at ISCTE – University Institute of Lisbon, Department of Information Science and Technology, and an integrated researcher at INESC-ID Lisbon. He serves as the Executive Coordinator of the Human Language Technologies (HLT) Scientific Area at INESC-ID and is a member of its Scientific Council. He previously held leadership roles including President of the Pedagogical Council of ISCTE-IUL (2017–2019) and member of its Standing Committee (2015–2017).

Research Interests:

• Natural Language Processing
• Machine Learning
• Text and Speech Processing
• Sentiment and Emotion Analysis
• Hate Speech Detection
• Social Media Analytics
• Automatic Speech Recognition and Transcription

His recent publications reflect a strong focus on applying NLP and machine learning to social media, with particular emphasis on hate speech detection, sentiment analysis, and user behavior modeling. He has also contributed significantly to speech processing, including punctuation restoration and prosody modeling, and to digital humanities through medieval text analysis. His work spans both technical innovation and real-world applications in tourism, finance, and public discourse.

Scientific Recognition:

• Senior Member of IEEE (since 2016)
• Member of ISCA (International Speech Communication Association)

Fernando Batista actively advises numerous PhD and Master’s students, supervising research in areas such as generative AI, hate speech detection, sentiment analysis, and economic forecasting. He has coordinated research projects like SPEDIAL and AppRecommender and is involved in organizing major conferences including PROPOR, EAMT, IPMU, and the Lisbon Machine Learning Summer School (LxMLS), where he has served in editorial and technical roles.

Research Labs and Teams:
He is a key member of the HLT@INESC-ID research group, contributing to its leadership and scientific direction. This group focuses on human language technologies, including speech processing, natural language understanding, and multilingual systems.