Functions

• Research Scientist Sintef (Sustainable Communication Technologies)
• External Supervisor Simula Research Laboratory (High Performance Computing)
• Member of Institute of Electrical and Electronics Engineers (IEEE)
• Alumni Technical University of Berlin
• Alumni Academy of International Affairs NRW

Short Bio

Dr. Daniel Thilo Schroeder, residing in Oslo, is a Research Scientist specializing in big data analytics, complex networks and digital communication. He is a member of the Smart Data group at SINTEF, contributing to the development of sustainable platforms for processing extreme data and building high-quality, FAIR-compliant datasets that fortify the effectiveness of AI applications. During his postdoc at the Simula Research Laboratory, he engaged in pivotal work to expand the application of deep learning to unstructured data through the development of computational frameworks. Earning his PhD from the Technical University of Berlin, Dr. Schroeder has been involved in multiple projects centered around understanding and mitigating the rapid spread of online misinformation.

Professional Experience

2023 - now. Research Scientist Sintef.
2021 - 2023. Postdoctoral Fellow Simula Research Laboratory.
2021 - 2022. Research Assistant Oslo Metropolitan University.
2018 - 2021. Phd Student Simula Research Laboratory & Technical University of Berlin.
2016 - 2017. Student Assistant at the department for Complex and Distributed IT Systems.

Education

• B.S. in Computer Science, Technical University of Berlin, 2010 - 2015
• B.S. in Computer Science, Federal University of Rio Grande do Sul, 2013 - 2015
• M.S. in Computer Science, Technical University of Berlin, 2015 - 2017
• Ph.D in Engineering, Technical University of Berlin, 2018 - 2022
• Ph.D in Engineering, Simula Research Laboratory, 2018 - 2021

Research Expertise

• Computational Social Science.
• Complex Networks.
• Graph Neural Networks.
• Data Management.

Language Skills

• German (+)
• English (+)
• Portuguese (+-)
• Norwegian Bokmål (-)

Publications

2026

• Intelligent Systems, Vulnerable Minds: A Framework for Radicalization to Violence in the Age of AI
  

  Personality and Social Psychology Review
• The 5G COVID-19 Digital Wildfire: An evolving network of Twitter contacts to explore phase transition metaphors in viral misinformation
  

  PLOS ONE
• Automated Disinformation Campaigns Meet Agentic AI: A Practical Threat Model for Malicious AI Swarms
  

  arXiv preprint
• How malicious AI swarms can threaten democracy
  

  Science
• The Messenger (not the Medium) Is the Message? Uncovering Journalists’ Perceptions of Digital Disinformation in Conflict Countries
  

  Journalism Studies

2025

• Beyond Information: Online Participatory Culture and Information Disorder
  

  Companion Publication of the 2025 Conference on Computer-Supported Cooperative Work and Social Computing
• Monitoring Digital Wildfires: a Large-Scale Dataset of COVID-19 Conspiracy Tweets Created via Fast NLP Inference using the Graphcore IPU
  

  2025 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)
• Ensemble-Based Fish Species Recognition in Challenging Underwater Environments
  

  OCEANS 2025 Brest
• Hashtags, Hatetags and social media campaigns in Ethiopia’s Tigray conflict
  

  Information, Communication & Society
• How Malicious AI Swarms Can Threaten Democracy
  

  OSF Preprints
• “Aren’t we all journalists?” Citizen journalism, disinformation and the weaponization of social media in conflict torn Mali
  

  Journalism

2024

• iPuma: High-Performance Sequence Alignment on the Graphcore IPU
  

  ISC High Performance 2024 Research Paper Proceedings
• GraphMa: Towards new Models for Pipeline-Oriented Computation on Graphs
  

  Companion of the 15th ACM/SPEC International Conference on Performance Engineering

2023

• GECO: A Twitter Dataset of COVID-19 Misinformation and Conspiracy Theories Related to the Berlin Parliament and Washington Capitol Riots
  

  Norsk IKT-konferanse for forskning og utdanning
• Harmful Conspiracies in Temporal Interaction Networks: Understanding the Dynamics of Digital Wildfires through Phase Transitions
  

  arXiv preprint
• Social media in the Global South: A Network Dataset of the Malian Twittersphere
  

  Journal of Data Mining & Digital Humanities
• COCO: an annotated Twitter dataset of COVID‑19 conspiracy theories
  

  2023 Journal of Computational Social Science
• COVID-19 and 5G conspiracy theories: long term observation of a digital wildfire
  

  International Journal of Data Science and Analytics

2022

• Understanding the Evolution of Reddit in Temporal Networks induced by User Activity
  

  Complex Networks and their Applications 2022
• Graph Neural Network for Fake News Detection and Classification of Unlabelled Nodes at MediaEval 2022
  

  Multimedia Benchmark Workshop 2022
• Combining Tweets and Connections Graph for FakeNews Detection at MediaEval 2022
  

  Multimedia Benchmark Workshop 2022
• Efficient Minimum Weight Vertex Cover Heuristics Using Graph Neural Networks
  

  20th International Symposium on Experimental Algorithms (SEA 2022)
• A Streaming System for Large-scale Temporal Graph Mining of Reddit Data
  

  2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)
• Implementing Spatio-Temporal Graph Convolutional Networks on Graphcore IPUs
  

  2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)
• The connectivity network underlying the German’s Twittersphere: a testbed for investigating information spreading phenomena
  

  Multimedia Benchmark Workshop 2022
• Explaining news spreading phenomena in social networks
  

  Technische Universitaet Berlin (Germany)

2021

• FakeNews: Corona Virus and Conspiracies Multimedia Analysis Task at MediaEval 2021
  

  MediaEval 2021 Workshop
• WICO Text: A Labeled Dataset of Conspiracy Theory and 5G-Corona Misinformation Tweets
  

  Proceedings of the 2021 Workshop on Open Challenges in Online Social Networks
• WICO Graph: A Labeled Dataset of Twitter Subgraphs based on Conspiracy Theory and 5G-Corona Misinformation Tweets.
  

  International Conference on Agents and Artificial Intelligence (ICAART) 2021
• iPUG: Accelerating Breadth-First Graph Traversals Using Manycore Graphcore IPUs
  

  ISC High Performance 2021
• Don’t Trust Your Eyes: Image Manipulation in the Age of DeepFakes
  

  Frontiers in Communication
• A Framework for Interaction-based Propagation Analysis in Online Social Networks
  

  Complex Networks and their applications

2020

• FakeNews Corona Virus and 5G Conspiracy Task at MediaEval 2020
  

  MediaEval
• Resource efficient algorithms for message sampling in online social networks
  

  2020 Seventh International Conference on Social Networks Analysis, Management and Security (SNAMS)
• Evaluating Standard Classifiers for Detecting COVID-19 related Misinformation
  

  IEEE Workshop on Parallel and Distributed Processing for Computational Social Systems
• A System for High Performance Mining on GDELT Data
  

  IEEE Workshop on Parallel and Distributed Processing for Computational Social Systems

2019

• A Scalable System for Bundling Online Social Network Mining Research
  

  2020 Seventh International Conference on Social Networks Analysis, Management and Security (SNAMS)
• Graph-Based Feature Selection Filter Utilizing Maximal Cliques
  

  Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS)
• Fact: a framework for analysis and capture of twitter graphs
  

  2019 Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS)

Supervisions

• Towards predicting Harmful Conspiracies through Phase Transitions in Complex Interaction Networks
  

  Kaspara Skovli Gåsvær 

   (University of Oslo)
• Implementing Sequence Alignment Algorithms on Graphcore IPUs
  

  Max Xiaohang Zhao 

   (Technical University of Berlin)
• Accelerating Breadth First traversals using AI accelerators
  

  Luk Burchard 

   (Technical University of Berlin)
• Observing Reddit’s Interaction Network - A stream-based approach for large scale Network Analysis on Reddit
  

  Andreas Huber 

   (University of Oslo)
• Graph Clustering for Long Term Twitter Observations
  

  Aigars Tumanis 

   (University of Oslo)
• Using Graph Neural Networks to classify Distribution Graphs from Twitter
  

  Ferdinand Schaal 

   (Technical University of Denmark)
• Visualization of Large Graphs
  

  Emil August Torp Nilsen" 

   (University of Oslo)
• Cartography and evolution of the Reddit landscape using graph-based methods
  

  Nora Marcoux 

   (Oslo Metropolitan University)
• A Twitter Graph Capturing Framework
  

  Luk Burchard 

   (Technical University of Berlin)

Public Engagement

2026

April

• Norwegian Helsinki Committee Annual Meeting (April 23, 2026): From Cyborg Propaganda to Malicious AI Swarms: Cognitive Security and the New Architecture of Influence — Invited lecture at the annual meeting of Den norske Helsingforskomité (Norwegian Helsinki Committee), Oslo. Talk on AI-driven influence operations, synthetic consensus, and threats to democratic resilience; invited following the NRK op-ed on fake grassroots movements.

• Sikkerhetskonferansen 2026 (NSM) (April 22, 2026): From Cyborg Propaganda to Malicious AI Swarms: Cognitive security and the new architecture of influence — Talk at Norway’s National Security Conference on hybrid influence threats and defense strategies. [Details & Slides] [Video]

• CXOTalk (April 2026): How AI Swarms Weaponize Disinformation — Podcast discussion on how AI swarms manufacture synthetic consensus, target corporate reputation, and what organizations can do about them.

March

• Hello Future (Orange) (March 2026): Confronting the Illusory Consensus of AI Swarms: Strategies for Preserving Democratic Debate — Orange’s research magazine on strategies for countering AI swarm threats to democratic discourse.

• Nettavisen (March 2026): KI-svermer på internett: – Krevende og skummelt — Norwegian coverage on AI swarms threatening democracy; features interviews with Jonas Kunst and Daniel Schroeder.

• Slovenian TV (March 2026): The Invisible Side of AI: When Algorithms Become Strategists — TV interview on how AI systems can identify key influencers and target disinformation based on psychological profiles.

February

• Somewhere on Earth: The Global Tech Podcast (February 2026): Is the internet still free - and who decides? — Podcast episode exploring AI swarms and their impact on elections, free speech, and public trust.

• Radio Ecoshock (February 2026): AI Swarms: We Are Not Ready — Radio interview on AI swarms and their threat to democracy.

• CT24 (Czech Television) (February 2026): Roje AI mohou rozvrátit demokracie, varují výzkumníci — Czech public broadcaster coverage on how AI swarms could disrupt democracies.

• NRK (February 2026): Falske folkebevegelser truer demokratiet — Opinion piece on how fake grassroots movements powered by AI threaten democracy.

• Tagesschau (ARD) (February 2026): KI-Schwärme könnten die Demokratie gefährden — German public broadcaster coverage on how AI swarms could endanger democracy.

• WELT (February 2026): “Die Frage ist nicht, ob es sie gibt, sondern in welchem Ausmaß sie bereits operieren” — In-depth feature on AI swarms and their potential scale of operation.

• Der Spiegel (February 12, 2026): Künstliche Intelligenz: Experten warnen vor KI-Schwärmen, die unsere Demokratie bedrohen — Detailed feature initiated by Schroeder and Kunst, focusing on threats and countermeasures.

• SciTechDaily (February 4, 2026): The AI Threat You’ll Never See Coming Is Already Talking to You Online — Repackages UBC-sourced warnings on unseen online manipulation and influence on elections.

• Tages-Anzeiger (February 2, 2026): AI-Schwärme: Wie künstliche Intelligenz Wahlen manipuliert — Discusses how AI-driven opinion makers are more sophisticated than bots and endanger democracy; quotes Schroeder on Swiss vulnerabilities.

• The Jerusalem Post (February 1, 2026): Study warns AI bot swarms could undermine democracy — Summarizes warnings on swarms mimicking behavior to spread misinformation and threaten free thought/elections.

January

• StudyFinds.org (January 30, 2026): AI Armies That Never Sleep Are Faking Grassroots Movements, Threatening Democracy — Focuses on faking grassroots consensus.

• UBC Science (January 29, 2026): AI swarms could hijack democracy—without anyone noticing — Quotes Schroeder on “synthetic consensus” via iterative probing/amplification; features UBC co-author Kevin Leyton-Brown.

• MDR (ARD) (January 27, 2026): Fake-Account war gestern – jetzt bedrohen KI-Schwärme den öffentlichen Diskurs — Warns about KI swarms manipulating democratic opinion formation and distorting discourse, referencing Schroeder’s Science paper.

• The Power of Us (January 27, 2026): When AI Can Fake Majorities, Democracy Dies Quietly — Guest elements from Schroeder, Kunst, and Jay Van Bavel; references the full paper.

• Decrypt (January 26, 2026): AI ‘Swarms’ Could Escalate Online Misinformation and Manipulation, Researchers Warn — Includes Schroeder quotes on capabilities.

• Max Planck Institute for Security and Privacy (January 26, 2026): AI ‘swarms’ could quietly threaten democracy — Ties to co-author Meeyoung Cha; focuses on faking consensus without obvious bot-like patterns.

• Harvard Digital Data Design Institute (January 26, 2026): The New Influence War: How AI Could Hack Democracy — Discusses implications with input from co-author Amit Goldenberg.

• The Guardian (January 23, 2026): Experts warn of threat to democracy from ‘AI bot swarms’ infesting social media — Direct quotes from Schroeder on deployment ease and cross-platform operations.

• TechXplore (January 23, 2026): The next generation of disinformation: AI swarms can threaten democracy by manufacturing fake public consensus — Core summary of the paper’s thesis.

• Neue Zürcher Zeitung (NZZ) (January 23, 2026): KI-Agenten könnten demokratische Wahlen beeinflussen, mahnen Experten. Wirklich? — Analytical piece discussing the paper’s claims on AI agents influencing elections.

• Marcus on AI (Gary Marcus Substack) (January 23, 2026): AI bot swarms threaten to undermine democracy — Joint essay with Schroeder and Jonas R. Kunst, expanding on the Science paper.

• BI Norwegian Business School (January 23, 2026): AI swarms threaten democracy — Co-lead emphasis on shift from bots to “social organisms”; quotes Schroeder on urgent defenses.

• University of Konstanz (January 23, 2026): The next generation of disinformation — Highlights co-author David Garcia’s involvement.

• WIRED (January 2026): AI-Powered Disinformation Swarms Are Coming for Democracy — Covers the technological shift to adaptive swarms, referencing Schroeder as lead author.

• Live Science (late January 2026): Next-generation AI ‘swarms’ will invade social media by mimicking human behavior and harassing real users, researchers warn — Emphasizes invasion and harassment risks.

• EurekAlert! / AAAS (January 22, 2026): Malicious AI swarms pose emergent threats to democracy — Official press release summarizing threats and proposed “AI Influence Observatory.”

• City St George’s, University of London (January 22, 2026): AI “swarms” could fake public consensus and quietly distort democracy, Science Policy Forum warns — Emphasizes co-author Andrea Baronchelli’s role and imitation of social dynamics.

• SINTEF (January 22, 2026): Publication page and related announcements — Linking to the paper and interviews.