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Daniel de Leng

Biträdande universitetslektor

Jag är biträdande universitetslektor vid Avdelningen för människocentrerade system. Mina forskningsintressen kretsar kring tillämpad AI och autonoma system.

Kortfattat CV

(På engelska)

  • PhD Computer Science, Dec 2019, Linköping University, Sweden.
  • Lic Computer Science, Oct 2017, Linköping University, Sweden.
  • MSc Computer Science, Nov 2013, Utrecht University, the Netherlands.
  • BSc Computer Science, Jul 2011, Utrecht University, the Netherlands.
  • Saab Aeronautics' first Point of Contact for Artificial Intelligence until 2022.
  • Part of the AIOps ELLIIT Infrastructure Initiative.
  • Part of the AI Academy management team.

 

Publikationer

Licentiat- och doktorsavhandling

2024

Md Fahim Sikder, Resmi Ramachandranpillai, Daniel de Leng, Fredrik Heintz (2024) FairX: A comprehensive benchmarking tool for model analysis using fairness, utility, and explainability Proceedings of the 2nd Workshop on Fairness and Bias in AI, co-located with 27th European Conference on Artificial Intelligence (ECAI 2024), Artikel 16 (Konferensbidrag)
Daniel de Leng, Pieter Bonte (2024) Last Night in Sweden: A Vision for Resource-Intelligent Stream Reasoning PROCEEDINGS OF THE 18TH ACM INTERNATIONAL CONFERENCE ON DISTRIBUTED AND EVENT-BASED SYSTEMS, DEBS 2024, s. 103-109 (Konferensbidrag) Vidare till DOI
Daniel de Leng, Pieter Bonte (2024) Last Night in Sweden: A Vision for Resource-Intelligent Stream Reasoning Proceedings of the 18th ACM International Conference on Distributed and Event-based Systems (DEBS ’24) (Konferensbidrag)
Pieter Bonte, Jean-Paul Calbimonte, Daniel de Leng, Daniele Dell'Aglio, Emanuele Della Valle, Thomas Eiter, Federico Giannini, Fredrik Heintz, Konstantin Schekotihin, Danh Le-Phuoc, Alessandra Mileo, Patrik Schneider, Riccardo Tommasini, Jacopo Urbani, Giacomo Ziffer (2024) Grounding Stream Reasoning Research Transactions on Graph Data and Knowledge (TGDK), Vol. 2, s. 1-47, Artikel 2 (Artikel i tidskrift) Vidare till DOI

2023

Ella Olsson, Mikael Nilsson, Kristoffer Bergman, Daniel de Leng, Stefan Carlén, Emil Karlsson, Bo Granbom (2023) Urdarbrunnen: Towards an AI-enabled mission system for Combat Search and Rescue operations Proceedings of the 35th Annual Workshop of the Swedish Artificial Intelligence Society (SAIS 2023), s. 38-45 (Konferensbidrag) Vidare till DOI

Forskning

AI Academy

Om avdelningen

Kollegor vid HCS

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