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.

41 entries « 3 of 9 »

2024

Jain, Charvi; Vahdati, Sahar; Gopan, Nandu; Sbalzarini, Ivo F.; Lehmann, Jens

Evaluating Large Language Model Literature Reviews in Interdisciplinary Science: A Systems Biology Perspective Proceedings Article

In: Badenes-Olmedo, Carlos; Novalija, Inna; Daga, Enrico; Stork, Lise; Pillai, Reshmi Gopalakrishna; Dierickx, Laurence; Kruit, Benno; Degeler, Victoria; Moreira, João; Zhang, Bohui; Alharbi, Reham; He, Yuan; Graciotti, Arianna; Tirado, Alba Catalina Morales; Presutti, Valentina; Motta, Enrico (Ed.): Joint Proceedings of Posters, Demos, Workshops, and Tutorials of the 24th International Conference on Knowledge Engineering and Knowledge Management (EKAW-PDWT 2024) co-located with 24th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2024), Amsterdam, Netherlands, November 26-28, 2024, CEUR-WS.org, 2024.

BibTeX | Links:

Lehmann, Jens; Meloni, Antonello; Motta, Enrico; Osborne, Francesco; Recupero, Diego Reforgiato; Salatino, Angelo Antonio; Vahdati, Sahar

Large Language Models for Scientific Question Answering: An Extensive Analysis of the SciQA Benchmark Proceedings Article

In: Meroño-Peñuela, Albert; Dimou, Anastasia; Troncy, Raphaël; Hartig, Olaf; Acosta, Maribel; Alam, Mehwish; Paulheim, Heiko; Lisena, Pasquale (Ed.): The Semantic Web - 21st International Conference, ESWC 2024, Hersonissos, Crete, Greece, May 26-30, 2024, Proceedings, Part I, pp. 199–217, Springer, 2024.

BibTeX | Links:

Meloni, Antonello; Recupero, Diego Reforgiato; Osborne, Francesco; Salatino, Angelo A.; Motta, Enrico; Vahdati, Sahar; Lehmann, Jens

Assessing Large Language Models for SPARQL Query Generation in Scientific Question Answering Proceedings Article

In: Alharbi, Reham; Berardinis, Jacopo; Groth, Paul; Meroño-Peñuela, Albert; Simperl, Elena; Tamma, Valentina (Ed.): Proceedings of the Special Session on Harmonising Generative AI and Semantic Web Technologies (HGAIS 2024) co-located with the 23rd International Semantic Web Conference (ISWC 2024), Baltimore, Maryland, November 13, 2024, CEUR-WS.org, 2024.

BibTeX | Links:

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:

41 entries « 3 of 9 »

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 « 3 of 9 »

2024

Jain, Charvi; Vahdati, Sahar; Gopan, Nandu; Sbalzarini, Ivo F.; Lehmann, Jens

Evaluating Large Language Model Literature Reviews in Interdisciplinary Science: A Systems Biology Perspective Proceedings Article

In: Badenes-Olmedo, Carlos; Novalija, Inna; Daga, Enrico; Stork, Lise; Pillai, Reshmi Gopalakrishna; Dierickx, Laurence; Kruit, Benno; Degeler, Victoria; Moreira, João; Zhang, Bohui; Alharbi, Reham; He, Yuan; Graciotti, Arianna; Tirado, Alba Catalina Morales; Presutti, Valentina; Motta, Enrico (Ed.): Joint Proceedings of Posters, Demos, Workshops, and Tutorials of the 24th International Conference on Knowledge Engineering and Knowledge Management (EKAW-PDWT 2024) co-located with 24th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2024), Amsterdam, Netherlands, November 26-28, 2024, CEUR-WS.org, 2024.

BibTeX | Links:

Lehmann, Jens; Meloni, Antonello; Motta, Enrico; Osborne, Francesco; Recupero, Diego Reforgiato; Salatino, Angelo Antonio; Vahdati, Sahar

Large Language Models for Scientific Question Answering: An Extensive Analysis of the SciQA Benchmark Proceedings Article

In: Meroño-Peñuela, Albert; Dimou, Anastasia; Troncy, Raphaël; Hartig, Olaf; Acosta, Maribel; Alam, Mehwish; Paulheim, Heiko; Lisena, Pasquale (Ed.): The Semantic Web - 21st International Conference, ESWC 2024, Hersonissos, Crete, Greece, May 26-30, 2024, Proceedings, Part I, pp. 199–217, Springer, 2024.

BibTeX | Links:

Meloni, Antonello; Recupero, Diego Reforgiato; Osborne, Francesco; Salatino, Angelo A.; Motta, Enrico; Vahdati, Sahar; Lehmann, Jens

Assessing Large Language Models for SPARQL Query Generation in Scientific Question Answering Proceedings Article

In: Alharbi, Reham; Berardinis, Jacopo; Groth, Paul; Meroño-Peñuela, Albert; Simperl, Elena; Tamma, Valentina (Ed.): Proceedings of the Special Session on Harmonising Generative AI and Semantic Web Technologies (HGAIS 2024) co-located with the 23rd International Semantic Web Conference (ISWC 2024), Baltimore, Maryland, November 13, 2024, CEUR-WS.org, 2024.

BibTeX | Links:

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:

41 entries « 3 of 9 »

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.

41 entries « 3 of 9 »

2024

Jain, Charvi; Vahdati, Sahar; Gopan, Nandu; Sbalzarini, Ivo F.; Lehmann, Jens

Evaluating Large Language Model Literature Reviews in Interdisciplinary Science: A Systems Biology Perspective Proceedings Article

In: Badenes-Olmedo, Carlos; Novalija, Inna; Daga, Enrico; Stork, Lise; Pillai, Reshmi Gopalakrishna; Dierickx, Laurence; Kruit, Benno; Degeler, Victoria; Moreira, João; Zhang, Bohui; Alharbi, Reham; He, Yuan; Graciotti, Arianna; Tirado, Alba Catalina Morales; Presutti, Valentina; Motta, Enrico (Ed.): Joint Proceedings of Posters, Demos, Workshops, and Tutorials of the 24th International Conference on Knowledge Engineering and Knowledge Management (EKAW-PDWT 2024) co-located with 24th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2024), Amsterdam, Netherlands, November 26-28, 2024, CEUR-WS.org, 2024.

BibTeX | Links:

Lehmann, Jens; Meloni, Antonello; Motta, Enrico; Osborne, Francesco; Recupero, Diego Reforgiato; Salatino, Angelo Antonio; Vahdati, Sahar

Large Language Models for Scientific Question Answering: An Extensive Analysis of the SciQA Benchmark Proceedings Article

In: Meroño-Peñuela, Albert; Dimou, Anastasia; Troncy, Raphaël; Hartig, Olaf; Acosta, Maribel; Alam, Mehwish; Paulheim, Heiko; Lisena, Pasquale (Ed.): The Semantic Web - 21st International Conference, ESWC 2024, Hersonissos, Crete, Greece, May 26-30, 2024, Proceedings, Part I, pp. 199–217, Springer, 2024.

BibTeX | Links:

Meloni, Antonello; Recupero, Diego Reforgiato; Osborne, Francesco; Salatino, Angelo A.; Motta, Enrico; Vahdati, Sahar; Lehmann, Jens

Assessing Large Language Models for SPARQL Query Generation in Scientific Question Answering Proceedings Article

In: Alharbi, Reham; Berardinis, Jacopo; Groth, Paul; Meroño-Peñuela, Albert; Simperl, Elena; Tamma, Valentina (Ed.): Proceedings of the Special Session on Harmonising Generative AI and Semantic Web Technologies (HGAIS 2024) co-located with the 23rd International Semantic Web Conference (ISWC 2024), Baltimore, Maryland, November 13, 2024, CEUR-WS.org, 2024.

BibTeX | Links:

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:

41 entries « 3 of 9 »

Recent Tweets

Go to Top