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.

34 entries « 7 of 7 »

2020

Nayyeri, Mojtaba; Xu, Chengjin; Lehmann, Jens; Vahdati, Sahar

Motif Learning in Knowledge Graphs Using Trajectories Of Differential Equations Journal Article

In: CoRR, vol. abs/2010.06684, 2020.

BibTeX | Links:

2019

Ali, Mehdi; Vahdati, Sahar; Singh, Shruti; Dasgupta, Sourish; Lehmann, Jens

Improving Access to Science for Social Good Proceedings Article

In: Cellier, Peggy; Driessens, Kurt (Ed.): Machine Learning and Knowledge Discovery in Databases - International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part I, pp. 658–673, Springer, 2019.

BibTeX | Links:

Nayyeri, Mojtaba; Vahdati, Sahar; Lehmann, Jens; Yazdi, Hamed Shariat

Soft Marginal TransE for Scholarly Knowledge Graph Completion Journal Article

In: CoRR, vol. abs/1904.12211, 2019.

BibTeX | Links:

Nayyeri, Mojtaba; Zhou, Xiaotian; Vahdati, Sahar; Yazdi, Hamed Shariat; Lehmann, Jens

Adaptive Margin Ranking Loss for Knowledge Graph Embeddings via a Correntropy Objective Function Journal Article

In: CoRR, vol. abs/1907.05336, 2019.

BibTeX | Links:

34 entries « 7 of 7 »

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.

34 entries « 7 of 7 »

2020

Nayyeri, Mojtaba; Xu, Chengjin; Lehmann, Jens; Vahdati, Sahar

Motif Learning in Knowledge Graphs Using Trajectories Of Differential Equations Journal Article

In: CoRR, vol. abs/2010.06684, 2020.

BibTeX | Links:

2019

Ali, Mehdi; Vahdati, Sahar; Singh, Shruti; Dasgupta, Sourish; Lehmann, Jens

Improving Access to Science for Social Good Proceedings Article

In: Cellier, Peggy; Driessens, Kurt (Ed.): Machine Learning and Knowledge Discovery in Databases - International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part I, pp. 658–673, Springer, 2019.

BibTeX | Links:

Nayyeri, Mojtaba; Vahdati, Sahar; Lehmann, Jens; Yazdi, Hamed Shariat

Soft Marginal TransE for Scholarly Knowledge Graph Completion Journal Article

In: CoRR, vol. abs/1904.12211, 2019.

BibTeX | Links:

Nayyeri, Mojtaba; Zhou, Xiaotian; Vahdati, Sahar; Yazdi, Hamed Shariat; Lehmann, Jens

Adaptive Margin Ranking Loss for Knowledge Graph Embeddings via a Correntropy Objective Function Journal Article

In: CoRR, vol. abs/1907.05336, 2019.

BibTeX | Links:

34 entries « 7 of 7 »

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.

34 entries « 7 of 7 »

2020

Nayyeri, Mojtaba; Xu, Chengjin; Lehmann, Jens; Vahdati, Sahar

Motif Learning in Knowledge Graphs Using Trajectories Of Differential Equations Journal Article

In: CoRR, vol. abs/2010.06684, 2020.

BibTeX | Links:

2019

Ali, Mehdi; Vahdati, Sahar; Singh, Shruti; Dasgupta, Sourish; Lehmann, Jens

Improving Access to Science for Social Good Proceedings Article

In: Cellier, Peggy; Driessens, Kurt (Ed.): Machine Learning and Knowledge Discovery in Databases - International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part I, pp. 658–673, Springer, 2019.

BibTeX | Links:

Nayyeri, Mojtaba; Vahdati, Sahar; Lehmann, Jens; Yazdi, Hamed Shariat

Soft Marginal TransE for Scholarly Knowledge Graph Completion Journal Article

In: CoRR, vol. abs/1904.12211, 2019.

BibTeX | Links:

Nayyeri, Mojtaba; Zhou, Xiaotian; Vahdati, Sahar; Yazdi, Hamed Shariat; Lehmann, Jens

Adaptive Margin Ranking Loss for Knowledge Graph Embeddings via a Correntropy Objective Function Journal Article

In: CoRR, vol. abs/1907.05336, 2019.

BibTeX | Links:

34 entries « 7 of 7 »

Recent Tweets

Go to Top