Prof. Dr. Jens Lehmann

PhD Supervisor

Nature-Inspired Machine Learning (NIMI)

Principal Scientist, Amazon AGI (Artificial General Intelligence)

Honorary Professor at TU Dresden
Member of InfAI

Prof. Dr. Jens Lehmann is a Principal Scientist at Amazon where he works at the AGI (Artificial General Intelligence) organisation on advancing large language models, conversational AI and knowledge graphs. He also holds an honorary professorship at TU Dresden, was selected as a fellow of ELLIS and is a member of InfAI. His academic activities at TU Dresden and InfAI support the Smart Data Analytics research group. Previously, he was jointly appointed full professor at the University of Bonn and Fraunhofer IAIS leading approximately 40 researchers. In this role, he was a lead scientist at Fraunhofer IAIS and coordinated the Dresden branch of the institute. His research interests involve knowledge graphs, machine learning as well as question answering & dialogue systems. His main research goal is to investigate and build generally intelligent systems by combining knowledge- and data-driven approaches. Prof. Lehmann authored more than 200 articles in international journals and conferences winning 15 best paper awards and obtaining more than 25000 citations and h-index 60+. He is a supporter and contributor to community research projects, including DBpedia, DL-Learner and LinkedGeoData. Previously, he led the AKSW research group and completed his PhD with „summa cum laude“ at the University of Leipzig with visits to the University of Oxford.

41 entries « ‹ 2 of 9 › »

2024

Saberi-Movahed, Farid; Biswas, Bitasta; Tiwari, Prayag; Lehmann, Jens; Vahdati, Sahar

Deep Nonnegative Matrix Factorization with Joint Global and Local Structure Preservation Journal Article

In: Expert Syst. Appl., vol. 249, pp. 123645, 2024.

BibTeX | Links:

Lehmann, Jens; Bhandiwad, Dhananjay; Gattogi, Preetam; Vahdati, Sahar

Beyond Boundaries: A Human-like Approach for Question Answering over Structured and Unstructured Information Sources Journal Article

In: Trans. Assoc. Comput. Linguistics, vol. 12, pp. 786–802, 2024.

BibTeX | Links:

Tiwari, Prayag; Movahed, Farid Saberi; Karami, Saeed; Saberi-Movahed, Farshad; Lehmann, Jens; Vahdati, Sahar

A Self-Representation Learning Method for Unsupervised Feature Selection using Feature Space Basis Journal Article

In: Trans. Mach. Learn. Res., vol. 2024, 2024.

BibTeX | Links:

Amouzouvi, Kossi; Song, Bowen; Vahdati, Sahar; Lehmann, Jens

Knowledge GeoGebra: Leveraging Geometry of Relation Embeddings in Knowledge Graph Completion Proceedings Article

In: Calzolari, Nicoletta; Kan, Min-Yen; Hoste, Véronique; Lenci, Alessandro; Sakti, Sakriani; Xue, Nianwen (Ed.): Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC/COLING 2024, 20-25 May, 2024, Torino, Italy, pp. 9832–9842, ELRA and ICCL, 2024.

BibTeX | Links:

Safaei, Farhad; Nenadovic, Milos; Liessner, Roman; Theilen, Raphael; Wittenstein, Jakob; Lehmann, Jens; Vahdati, Sahar

X-Vent: ICU Ventilation with Explainable Model-Based Reinforcement Learning Proceedings Article

In: Endriss, Ulle; Melo, Francisco S.; Bach, Kerstin; Diz, Alberto José Bugar'ın; Alonso-Moral, Jose Maria; Barro, Senén; Heintz, Fredrik (Ed.): ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain - Including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024), pp. 4719–4726, IOS Press, 2024.

BibTeX | Links:

41 entries « ‹ 2 of 9 › »

PhD Supervisor

Nature-Inspired Machine Learning (NIMI)

2024

InfAI

NIMI / Scads.AI