Dr. Fredrik Heintz is an Associate Professor of Computer Science at Linköping University, Sweden. 
He leads the Stream Reasoning group within the Division of Artificial Intelligence and Integrated Systems (AIICS) in the Department of Computer Science (IDA). His research focus is artificial intelligence especially autonomous systems, stream reasoning and the intersection between knowledge representation and machine learning. 

He is the Director of the Graduate School for the Wallenberg AI, Autonomous Systems and Software Program (WASP) with more than 120 PhD students, the President of the Swedish AI Society (SAIS), and a member of the European Commission High-Level Expert Group on AI

He was the Local Arrangements Chair for IJCAI-ECAI-18 in Stockholm.

He is also very active in education activities both at the university level and in promoting computer science and computational thinking in primary and secondary education. Hewas responsible for the creation and design of the 5-year engineering program in computer science and software engineering (Civilingenjör Mjukvaruteknik).

He became a docent in January 2014. He completed his PhD in March 2009 and his supervisor was Patrick Doherty. He graduated from the Computer Science program in Linköping March 2000.

  • Dr. Fredrik Heintz  has  received three grants from the Pedagogy Development Group at LiTH, one for developing the dialoge seminar methodology for engineering education  (2014), one for researching Computational Thinking in Discrete Math (2013), and one for Contests as a pedgogical tool (2011).
  • Since 2014 I am a member of the board of Didacticum.

• Since 2013 I lead the Computer Science Education group at IDA.

• Since 2013 I lead the ICPC Analytics team at the ACM ICPC World Finals, previously I led the analytics team within the ICPC Live team.

• Since 2012 I teach the PhD course on Advanced Algorithmic Problem Solving.

• Since 2012 I am the chairman of PPG Mjukvaruteknik. I have lead the work with developing the new program Civilingenjör Mjukvaruteknik.

• Since 2012 I am a member of Programnämnden för data- och medieteknik (DM).

Since 2010 I am the president of the Swedish AI Society (SAIS) (I was the secretary 2000-2010).

• Since November 2009 I arrange Programming and Problem solving activities at IDA. We are currently running the IDA Championship in Programming and Algorithms. I also give the PhD course in Advanced Algorithmic Problem Solving.

• Since 2007 I am the contest director for the Nordic Collegiate Programming Contest, which is part of ACMs International Collegiate Programming Contest (I was also the contest director 2003-2004).

• Since 2002 I am the national contest director for the Swedish Championship in programming. I have been the local organizer in Linköping of the same contest since 2000. 2000-2012 I taught the course TDDD10 AI Programming (known as TDDA14 AI Programming 2000-2007).


Download my CV for detailed information.




Member of: Artificial Intelligence and Integrated Computer Systems (AIICS)

                    The Knowledge Processing Laboratory (KPLAB)




My main research interest is in stream-based reasoning grounded through sensing in cognitive robotics. I lead the Cognitive Robotics Group and am involved in several projects in AIICS, for example: Stream-based reasoning where for example develop the DyKnow knowledge processing middleware framework Model-based diagnosis where we develop the FlexDx reconfigurable diagnosis framework Execution monitoring where we extend DyKnow with support for execution monitoring through progression of temporal logical formulas and integrate it with TALplanner.

I am the principle investigator for the CENIIT project Stream-based reasoning grounded through sensing.


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Conor F. Hayes, Roxana Rădulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers (2022) A practical guide to multi-objective reinforcement learning and planning Autonomous Agents and Multi-Agent Systems , Vol. 36 Continue to DOI


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