Nature-Inspired Machine Learning (NIMI)

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.

30 entries « ‹ 1 of 6 › »

2023

Mohiuddin, Karishma; Alam, Mirza Ariful; Alam, Mirza Mohtashim; Welke, Pascal; Martin, Michael; Lehmann, Jens; Vahdati, Sahar

Retention is All You Need Proceedings Article

In: Frommholz, Ingo; Hopfgartner, Frank; Lee, Mark; Oakes, Michael; Lalmas, Mounia; Zhang, Min; Santos, Rodrygo L. T. (Ed.): Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023, pp. 4752–4758, ACM, 2023.

BibTeX | Links:

Song, Bowen; Xu, Chengjin; Amouzouvi, Kossi; Wang, Maocai; Lehmann, Jens; Vahdati, Sahar

Distinct Geometrical Representations for Temporal and Relational Structures in Knowledge Graphs Proceedings Article

In: Koutra, Danai; Plant, Claudia; Rodriguez, Manuel Gomez; Baralis, Elena; Bonchi, Francesco (Ed.): Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part III, pp. 601–616, Springer, 2023.

BibTeX | Links:

Mohiuddin, Karishma; Alam, Mirza Ariful; Alam, Mirza Mohtashim; Welke, Pascal; Martin, Michael; Lehmann, Jens; Vahdati, Sahar

Retention Is All You Need Journal Article

In: CoRR, vol. abs/2304.03103, 2023.

BibTeX | Links:

Language Models as Controlled Natural Language Semantic Parsers for Knowledge Graph Question Answering

Lehmann, Jens; Ferré, Sébastien; Vahdati, Sahar

Language Models as Controlled Natural Language Semantic Parsers for Knowledge Graph Question Answering Proceedings Article

In: Gal, Kobi; Nowé, Ann; Nalepa, Grzegorz J.; Fairstein, Roy; Radulescu, Roxana (Ed.): ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland - Including 12th Conference on Prestigious Applications of Intelligent Systems (PAIS 2023), pp. 1348–1356, IOS Press, 2023.

BibTeX | Links:

2022

Alam, Mirza Mohtashim; Rony, Md. Rashad Al Hasan; Nayyeri, Mojtaba; Mohiuddin, Karishma; Akter, M. S. T. Mahfuja; Vahdati, Sahar; Lehmann, Jens

Language Model Guided Knowledge Graph Embeddings Journal Article

In: IEEE Access, vol. 10, pp. 76008–76020, 2022.

BibTeX | Links:

30 entries « ‹ 1 of 6 › »

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.

30 entries « ‹ 1 of 6 › »

2023

Mohiuddin, Karishma; Alam, Mirza Ariful; Alam, Mirza Mohtashim; Welke, Pascal; Martin, Michael; Lehmann, Jens; Vahdati, Sahar

Retention is All You Need Proceedings Article

In: Frommholz, Ingo; Hopfgartner, Frank; Lee, Mark; Oakes, Michael; Lalmas, Mounia; Zhang, Min; Santos, Rodrygo L. T. (Ed.): Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023, pp. 4752–4758, ACM, 2023.

BibTeX | Links:

Song, Bowen; Xu, Chengjin; Amouzouvi, Kossi; Wang, Maocai; Lehmann, Jens; Vahdati, Sahar

Distinct Geometrical Representations for Temporal and Relational Structures in Knowledge Graphs Proceedings Article

In: Koutra, Danai; Plant, Claudia; Rodriguez, Manuel Gomez; Baralis, Elena; Bonchi, Francesco (Ed.): Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part III, pp. 601–616, Springer, 2023.

BibTeX | Links:

Mohiuddin, Karishma; Alam, Mirza Ariful; Alam, Mirza Mohtashim; Welke, Pascal; Martin, Michael; Lehmann, Jens; Vahdati, Sahar

Retention Is All You Need Journal Article

In: CoRR, vol. abs/2304.03103, 2023.

BibTeX | Links:

Language Models as Controlled Natural Language Semantic Parsers for Knowledge Graph Question Answering

Lehmann, Jens; Ferré, Sébastien; Vahdati, Sahar

Language Models as Controlled Natural Language Semantic Parsers for Knowledge Graph Question Answering Proceedings Article

In: Gal, Kobi; Nowé, Ann; Nalepa, Grzegorz J.; Fairstein, Roy; Radulescu, Roxana (Ed.): ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland - Including 12th Conference on Prestigious Applications of Intelligent Systems (PAIS 2023), pp. 1348–1356, IOS Press, 2023.

BibTeX | Links:

2022

Alam, Mirza Mohtashim; Rony, Md. Rashad Al Hasan; Nayyeri, Mojtaba; Mohiuddin, Karishma; Akter, M. S. T. Mahfuja; Vahdati, Sahar; Lehmann, Jens

Language Model Guided Knowledge Graph Embeddings Journal Article

In: IEEE Access, vol. 10, pp. 76008–76020, 2022.

BibTeX | Links:

30 entries « ‹ 1 of 6 › »

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.

30 entries « ‹ 1 of 6 › »

2023

Mohiuddin, Karishma; Alam, Mirza Ariful; Alam, Mirza Mohtashim; Welke, Pascal; Martin, Michael; Lehmann, Jens; Vahdati, Sahar

Retention is All You Need Proceedings Article

In: Frommholz, Ingo; Hopfgartner, Frank; Lee, Mark; Oakes, Michael; Lalmas, Mounia; Zhang, Min; Santos, Rodrygo L. T. (Ed.): Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023, pp. 4752–4758, ACM, 2023.

BibTeX | Links:

Song, Bowen; Xu, Chengjin; Amouzouvi, Kossi; Wang, Maocai; Lehmann, Jens; Vahdati, Sahar

Distinct Geometrical Representations for Temporal and Relational Structures in Knowledge Graphs Proceedings Article

In: Koutra, Danai; Plant, Claudia; Rodriguez, Manuel Gomez; Baralis, Elena; Bonchi, Francesco (Ed.): Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part III, pp. 601–616, Springer, 2023.

BibTeX | Links:

Mohiuddin, Karishma; Alam, Mirza Ariful; Alam, Mirza Mohtashim; Welke, Pascal; Martin, Michael; Lehmann, Jens; Vahdati, Sahar

Retention Is All You Need Journal Article

In: CoRR, vol. abs/2304.03103, 2023.

BibTeX | Links:

Language Models as Controlled Natural Language Semantic Parsers for Knowledge Graph Question Answering

Lehmann, Jens; Ferré, Sébastien; Vahdati, Sahar

Language Models as Controlled Natural Language Semantic Parsers for Knowledge Graph Question Answering Proceedings Article

In: Gal, Kobi; Nowé, Ann; Nalepa, Grzegorz J.; Fairstein, Roy; Radulescu, Roxana (Ed.): ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland - Including 12th Conference on Prestigious Applications of Intelligent Systems (PAIS 2023), pp. 1348–1356, IOS Press, 2023.

BibTeX | Links:

2022

Alam, Mirza Mohtashim; Rony, Md. Rashad Al Hasan; Nayyeri, Mojtaba; Mohiuddin, Karishma; Akter, M. S. T. Mahfuja; Vahdati, Sahar; Lehmann, Jens

Language Model Guided Knowledge Graph Embeddings Journal Article

In: IEEE Access, vol. 10, pp. 76008–76020, 2022.

BibTeX | Links:

30 entries « ‹ 1 of 6 › »

Publications

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.

30 entries « ‹ 1 of 6 › »

2023

Mohiuddin, Karishma; Alam, Mirza Ariful; Alam, Mirza Mohtashim; Welke, Pascal; Martin, Michael; Lehmann, Jens; Vahdati, Sahar

Retention is All You Need Proceedings Article

In: Frommholz, Ingo; Hopfgartner, Frank; Lee, Mark; Oakes, Michael; Lalmas, Mounia; Zhang, Min; Santos, Rodrygo L. T. (Ed.): Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023, pp. 4752–4758, ACM, 2023.

BibTeX | Links:

Song, Bowen; Xu, Chengjin; Amouzouvi, Kossi; Wang, Maocai; Lehmann, Jens; Vahdati, Sahar

Distinct Geometrical Representations for Temporal and Relational Structures in Knowledge Graphs Proceedings Article

In: Koutra, Danai; Plant, Claudia; Rodriguez, Manuel Gomez; Baralis, Elena; Bonchi, Francesco (Ed.): Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part III, pp. 601–616, Springer, 2023.

BibTeX | Links:

Mohiuddin, Karishma; Alam, Mirza Ariful; Alam, Mirza Mohtashim; Welke, Pascal; Martin, Michael; Lehmann, Jens; Vahdati, Sahar

Retention Is All You Need Journal Article

In: CoRR, vol. abs/2304.03103, 2023.

BibTeX | Links:

Language Models as Controlled Natural Language Semantic Parsers for Knowledge Graph Question Answering

Lehmann, Jens; Ferré, Sébastien; Vahdati, Sahar

Language Models as Controlled Natural Language Semantic Parsers for Knowledge Graph Question Answering Proceedings Article

In: Gal, Kobi; Nowé, Ann; Nalepa, Grzegorz J.; Fairstein, Roy; Radulescu, Roxana (Ed.): ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland - Including 12th Conference on Prestigious Applications of Intelligent Systems (PAIS 2023), pp. 1348–1356, IOS Press, 2023.

BibTeX | Links:

2022

Alam, Mirza Mohtashim; Rony, Md. Rashad Al Hasan; Nayyeri, Mojtaba; Mohiuddin, Karishma; Akter, M. S. T. Mahfuja; Vahdati, Sahar; Lehmann, Jens

Language Model Guided Knowledge Graph Embeddings Journal Article

In: IEEE Access, vol. 10, pp. 76008–76020, 2022.

BibTeX | Links:

30 entries « ‹ 1 of 6 › »

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