Univ. Professor Sepp Hochreiter is a distinguished German computer scientist and a leading authority in artificial intelligence and machine learning. He currently serves as the head of the Institute for Machine Learning at Johannes Kepler University of Linz, a position he has held since 2018, following his leadership of the Institute of Bioinformatics from 2006 to 2018. Prior to his appointments in Linz, Hochreiter held research positions at the Technische Universität Berlin, the University of Colorado at Boulder, and the Technical University of Munich. His academic journey has been marked by visionary leadership, including his role as founding director of the Institute of Advanced Research in Artificial Intelligence and his position as head of the Linz Institute of Technology AI Lab since 2017.
Professor Hochreiter's most groundbreaking contribution to science is the development of the Long Short-Term Memory neural network architecture, which he first conceived in his 1991 diploma thesis with the seminal publication following in 1997. LSTM solved the critical problem of vanishing gradients in recurrent neural networks, enabling machines to learn from long sequences of data and forming the foundation for modern sequence learning. This pioneering work has become one of the most influential architectures in deep learning, powering applications from speech recognition and language translation to autonomous driving systems. His research has also significantly advanced meta-learning, reinforcement learning, and biclustering methods with applications in bioinformatics, including the development of FABIA for biclustering and FARMS for microarray analysis.
Beyond his technical contributions, Hochreiter has been instrumental in establishing Austria as a hub for artificial intelligence research through his leadership of the LIT AI Lab and the AUDI.JKU deep learning center, which focuses on applying machine learning to autonomous driving challenges. His work continues to shape the field as evidenced by his numerous accolades including the prestigious IEEE Neural Networks Pioneer Award, widely regarded as the highest honor in deep learning. As a Corresponding Member of the Division of Mathematics and Natural Sciences in Austria since 2024 and chair of the Critical Assessment of Massive Data Analysis conference, he remains deeply engaged in fostering scientific excellence and collaboration. Professor Hochreiter's current research continues to push the boundaries of deep learning with applications spanning autonomous systems, computer vision, and bioinformatics, ensuring his lasting impact on both theoretical and applied artificial intelligence.
