Fotografi av Daniel de Leng

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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