Complexity Science Hub

𝗪𝗮𝗻𝘁 𝘁𝗼 𝗷𝗼𝗶𝗻 𝘂𝘀 𝗳𝗼𝗿 𝘆𝗼𝘂𝗿 𝗣𝗵𝗗 𝗮𝗻𝗱 𝗱𝗶𝘃𝗲 𝗶𝗻𝘁𝗼 𝗖𝗼𝗺𝗽𝗹𝗲𝘅𝗶𝘁𝘆 𝗦𝗰𝗶𝗲𝗻𝗰𝗲? Applications for the 𝗚𝗿𝗮𝗱𝘂𝗮𝘁𝗲 𝗣𝗿𝗼𝗴𝗿𝗮𝗺 𝗶𝗻 𝗖𝗼𝗺𝗽𝗹𝗲𝘅𝗶𝘁𝘆 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 at the Complexity Science Hub are open until 15 October 2026.

❓ 𝗛𝗼𝘄 𝗱𝗼 𝘆𝗼𝘂 𝗸𝗻𝗼𝘄 if the program is right for you ❓

If you want to use science to help change the world and create real impact. If you're excited about digging into how complex systems really work. If you love combining large datasets with quantitative modeling and rigorous theory. If you're driven to tackle critical real-world challenges.

And, a little more technically: if you have a background in the natural or social sciences or mathematics, with a strong foundation in quantitative approaches.

If this sounds like you, we look forward to your application – and to welcoming the next generation of complexity scientists to CSH.

📅 Apply by 15 October 2026
👉 More information: https://csh.ac.at/education/graduate-program/

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The CSH Graduate Program in Complexity Science is an initiative under the umbrella of the CSH Digital Innovation School.

Graduate students at CSH will benefit from the collective expertise of our members, gaining valuable insights and mentorship as they build the foundation for successful academic and professional careers.

Members of the Complexity Science Hub are AIT Austrian Institute of Technology, University of Natural Resources and Life Sciences, Vienna (BOKU), Central European University, Interdisciplinary Transformation University (IT:U), Medical University of Vienna, Technische Universität Wien, Technische Universität Graz, Universität für Weiterbildung Krems, Vetmeduni, WU (Vienna University of Economics and Business) and Austrian Federal Economic Chamber.

👋 𝗪𝗲𝗹𝗰𝗼𝗺𝗲 👋 Eric Schnell, to the Complexity Science Hub as a Postdoctoral Researcher!

Eric joined the 𝗖𝗼𝗹𝗹𝗲𝗰𝘁𝗶𝘃𝗲 𝗠𝗶𝗻𝗱𝘀 group, led by Mirta Galesic and Henrik Olsson, to study how groups reach collective decisions when individuals have competing interests. He uses evolutionary game theory and mathematical modeling to look at cooperation across different scales of society.

He earned his PhD in Psychological and Behavioural Science from the London School of Economics, where he modeled the cultural evolution of large-scale human cooperation – how we moved from small hunter-gatherer groups to societies of millions.

📖 Eric's just published a new paper on how property rights and status competition shape wealth display, evil eye beliefs, and egalitarian norms: https://doi.org/10.1016/j.evolhumbehav.2026.106961

Welcome, Eric – it's a pleasure to have you on board! 🎉

🔗 More about Eric: https://csh.ac.at/eric-schnell/
🔗 More about Collective Minds at CSH: https://csh.ac.at/research/research-topic/collective-minds/

🎓 𝗖𝗼𝗻𝗴𝗿𝗮𝘁𝘂𝗹𝗮𝘁𝗶𝗼𝗻𝘀 Hannah Schuster, 𝗣𝗵𝗗! ⭐ 🏆 🥳

Hannah brilliantly defended her PhD thesis, “The Complexity of Crisis Situations: Data-Driven Approaches for Disaster Management,” on Friday.

Her research, conducted at the Complexity Science Hub and WU (Vienna University of Economics and Business), explored different use cases in crisis situations – and what data can tell us about them:

🏥 𝗖𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗮𝗰𝗰𝗲𝘀𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆: Network-based assessment of how road closures affect access to hospitals.

🌡️ 𝗛𝗲𝗮𝘁-𝗿𝗲𝗹𝗮𝘁𝗲𝗱 𝗵𝗲𝗮𝗹𝘁𝗵 𝗿𝗶𝘀𝗸𝘀: Identification of factors associated with heat-related mortality and development of the Heat Stress Index 👉 https://vis.csh.ac.at/heat-health-habitats/

🚨 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗱𝗲𝗺𝗮𝗻𝗱 𝗳𝗼𝗿𝗲𝗰𝗮𝘀𝘁𝗶𝗻𝗴: Assessment of the potential of weather warnings for forecasting crisis-related operational demand.

🔎 𝗖𝗿𝗼𝘀𝘀-𝗰𝗮𝘀𝗲 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀: Identification of recurring information domains and data-integration challenges across crisis-management applications.

🧩 𝗖𝗥𝗜𝗦𝗣 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗚𝗿𝗮𝗽𝗵: Using these insights to inform the development of a common knowledge representation for crisis management.

Hannah had a great team by her side throughout this journey: supervisor Axel Polleres (who shares more about what makes her work remarkable in his post: https://lnkd.in/p/d8XqsXgi) – as well as co-supervisors Johannes Wachs and Amin Anjomshoaa.

Hannah, 𝗛𝗨𝗚𝗘 𝗖𝗢𝗡𝗚𝗥𝗔𝗧𝗨𝗟𝗔𝗧𝗜𝗢𝗡𝗦 on this amazing milestone! We’ve loved having you as part of the CSH community and hope you’ll stay closely connected with us. Wishing you all the very best for whatever comes next! 🫶

🤔 𝗛𝗼𝘄 𝗱𝗼𝗲𝘀 𝗻𝗼𝘃𝗲𝗹𝘁𝘆 𝗲𝗺𝗲𝗿𝗴𝗲? Is it unpredictable, or are there patterns? And can we measure it? In their new 📚, 𝗧𝗵𝗲 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗡𝗲𝘄, published by Oxford University Press, CSH researcher Vito D. P. Servedio, together with CSH External Faculty members Vittorio Loreto and Francesca Tria, take a closer look at these questions.

“In our book, we investigate how first-time events – from everyday experiences to groundbreaking discoveries – can lead to subsequent breakthroughs,” explains Vito. “We ultimately propose a unified quantitative framework for understanding the dynamics of novelty and innovation in biological, technological and social systems.”

𝗧𝗵𝗲 𝗯𝗼𝗼𝗸 𝗶𝘀 𝗱𝗶𝘃𝗶𝗱𝗲𝗱 𝗶𝗻𝘁𝗼 𝘁𝗵𝗿𝗲𝗲 𝗺𝗮𝗶𝗻 𝗽𝗮𝗿𝘁𝘀:

📖 𝗣𝗮𝗿𝘁 𝟭 introduces tools for studying how new ideas emerge.
📖 𝗣𝗮𝗿𝘁 𝟮 explores classical and modern models that capture the development, interaction and competition of innovations within complex systems.
📖 𝗣𝗮𝗿𝘁 𝟯 presents empirical case studies that uncover hidden patterns in how novelty spreads.

Next week, the authors will present "The Science of the New" as part of Rome Future Week, in conversation with Anna Parisi: https://romefutureweek.it/event/la-scienza-del-nuovo/

📍 22 September 2026, 5:00 PM | Radisson Blu, Rome
👥 Vittorio Loreto (Sapienza Università di Roma, Sony CSL (Rome)), Vito D.P. Servedio (Complexity Science Hub) & Francesca Tria (Sapienza Università di Roma)

🔗 Book: https://academic.oup.com/book/62405

🌟 In this case, we can’t say it any other way: 𝗪𝗵𝗮𝘁 𝗮 𝗳𝗶𝗿𝘀𝘁 𝗲𝗱𝗶𝘁𝗶𝗼𝗻! Ljubica Nedelkoska really rocked our evening yesterday, sharing insights into AI and its impact on the labor market at the very first 𝗪𝗘𝗱𝗻𝗲𝘀𝗱𝗮𝘆 𝗦𝗔𝗟𝗢𝗡 at the Complexity Science Hub.

She started with three historical examples of technologies that disrupted the labor market – and what happened next:

📞 𝗧𝗲𝗹𝗲𝗽𝗵𝗼𝗻𝗲 𝗼𝗽𝗲𝗿𝗮𝘁𝗼𝗿𝘀
The entire occupation eventually disappeared. 𝗕𝘂𝘁: many of the women working as telephone operators were able to switch to other jobs relatively easily, including as secretaries or stenographers, because they already had many of the required skills.

👞 𝗕𝗼𝗼𝘁𝗺𝗮𝗸𝗲𝗿𝘀 𝗶𝗻 𝗩𝗶𝗰𝘁𝗼𝗿𝗶𝗮𝗻 𝗘𝗻𝗴𝗹𝗮𝗻𝗱
When sewing machines capable of working with leather emerged around 1850, the traditional bootmaking industry was transformed. By 1911, around 150,000 jobs had disappeared. 𝗕𝘂𝘁: roughly 140,000 new ones had emerged. Most workers who were already in the industry kept their jobs. But their sons often ended up in very different occupations, such as machine technicians, managers, or salespeople, as production expanded.

🌾 𝗙𝗮𝗿𝗺𝗲𝗿𝘀 𝗶𝗻 𝘁𝗵𝗲 𝗨𝗦
The invention of the combine harvester replaced several different occupations. Today, a modern combine can do the work of more than 400 people. 𝗕𝘂𝘁: it took roughly a century for the technology to reach that level of productivity.

𝗦𝗼 𝘄𝗵𝗮𝘁 𝗺𝗮𝗸𝗲𝘀 𝗔𝗜 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁?

For one, the pace 🏃‍♂️‍➡️ is much faster: it took just 3️⃣ years to go from AI as a writing assistant to autonomous AI agents, she emphasized. At the same time, AI is moving into a much wider range ↔️ of fields than any technology before it.

The 𝗴𝗼𝗼𝗱 𝗻𝗲𝘄𝘀, Ljubica pointed out, is that historically, new jobs have always emerged.

But that raises another question: 𝗪𝗵𝗲𝗿𝗲 𝗱𝗼 𝘁𝗵𝗼𝘀𝗲 𝗷𝗼𝗯𝘀 𝗲𝗺𝗲𝗿𝗴𝗲? – geographically and in terms of skills.

Ljubica ended with 3️⃣ questions policymakers should be thinking about:
🍰 𝗛𝗼𝘄 𝗱𝗼 𝘄𝗲 𝗴𝗿𝗼𝘄 𝘁𝗵𝗲 𝗽𝗶𝗲? To capture AI-led growth, the EU needs to start competing for it (for real).
🍰 𝗛𝗼𝘄 𝗱𝗼 𝘄𝗲 𝗱𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲 𝘁𝗵𝗲 𝗽𝗶𝗲? If the contribution of labor to production falls significantly, e.g., taxation would need to shift away from labor.
🍰 𝗛𝗼𝘄 𝗱𝗼 𝘄𝗲 𝗵𝗲𝗹𝗽 𝗽𝗲𝗼𝗽𝗹𝗲 𝗿𝗲𝗮𝗰𝗵 𝘁𝗵𝗲 𝗽𝗶𝗲? Can people in declining occupations make the transition to growing ones?

An incredibly interesting evening! Thanks to everyone who joined us, and especially to Aashima Dogra-Freitag for moderating the conversation!

🔗 Want to 𝗿𝗲𝗮𝗱 𝗺𝗼𝗿𝗲 – check out Ljubica’s piece in ? https://www.nature.com/articles/d41586-026-01877-y
🔗 Our 𝗻𝗲𝘅𝘁 𝗪𝗘𝗱𝗻𝗲𝘀𝗱𝗮𝘆 𝗦𝗔𝗟𝗢𝗡 will take place in October. Stay tuned and register here: https://csh.ac.at/events-news/events/

No. 3️⃣ Research Topic of the month: 𝗖𝗿𝗶𝗺𝗲 𝗶𝗻 𝘁𝗵𝗲 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗔𝗴𝗲 – looking behind the scenes with Bernhard Haslhofer! What is he working on right now that he can't stop thinking about? What is complexity, to him? When he is stuck – what does he do? And what does his typical workday look like?

In this rapid-fire interview, Bernhard shares a personal take: https://csh.ac.at/news/crime-in-the-digital-age-interview-with-bernhard-haslhofer/

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𝗔𝗯𝗼𝘂𝘁 𝘁𝗵𝗶𝘀 𝘀𝗲𝗿𝗶𝗲𝘀:

In June 2026, the Complexity Science Hub celebrated its 10th anniversary — and throughout our anniversary year, we're spotlighting one research topic every month. Curious about how we celebrated in June? For a deep dive into a decade of complexity science, read our 10-year publication here: https://csh.ac.at/news/its-the-complexity-stupid/

𝗙𝗿𝗼𝗺 𝘁𝗵𝗲 𝗡𝗲𝘄 𝗠𝗲𝘅𝗶𝗰𝗮𝗻 𝗱𝗲𝘀𝗲𝗿𝘁 🌵 𝘁𝗼 𝗮 𝟳𝟮-𝗵𝗼𝘂𝗿 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝘀𝗽𝗿𝗶𝗻𝘁 𝗶𝗻 𝗟𝗼𝗻𝗱𝗼𝗻 🇬🇧 — besides enjoying a well-deserved summer break, CSH PhD students were also pretty busy this summer, traveling to workshops and summer schools in different corners of the world. What better combination is there than 𝘀𝘂𝗺𝗺𝗲𝗿, 𝘀𝘂𝗻𝘀𝗵𝗶𝗻𝗲 – 𝗮𝗻𝗱 𝘀𝗰𝗶𝗲𝗻𝗰𝗲? ☀️🔬

Here are two glimpses from the road: 🧳

3️⃣ 𝗶𝗻𝘁𝗲𝗻𝘀𝗲 𝘄𝗲𝗲𝗸𝘀 𝗮𝘁 𝘁𝗵𝗲 𝗦𝗮𝗻𝘁𝗮 𝗙𝗲 𝗜𝗻𝘀𝘁𝗶𝘁𝘂𝘁𝗲 🏜️

The Complex Systems Summer School hosted by the Santa Fe Institute is something CSH PhD student Sophia Baum won't forget. In the mornings, SFI's incredible faculty gave lectures, while afternoons were spent on tutorials and self-organized research projects.

"Everything about this school felt intentional: how they ran the sessions, how they brought people together and how they initiated conversations that otherwise would not have happened. I walked in knowing only one other attendee and walked out knowing fifty more, from fields I never would have crossed paths with otherwise," says Sophia. In her downtime, she found herself exploring New Mexican nature and wildlife or taking in local festivals ‒ all part of a month well spent in the US. 🌄

7️⃣2️⃣ 𝗵𝗼𝘂𝗿𝘀, 𝗼𝗻𝗲 𝗽𝗿𝗲𝗽𝗿𝗶𝗻𝘁, 𝗹𝗶𝘁𝘁𝗹𝗲 𝘀𝗹𝗲𝗲𝗽 📝

– that's how CSH PhD student Alexandra Krasnokutskaya sums up her experience at the Complexity72h workshop in London, hosted by Northeastern University London and organized by Complexity Next Gen. True to the workshop's name, she and her CSH colleagues Jiaqi Liang and Carsten Källner took on the challenge of developing a scientific preprint within 72 hours.

"In this timeframe, your results are, of course, preliminary," says Alexandra, "but you get to know so many people from the world of complexity science – and potentially meet future collaborators. “As a first-year PhD student, I’m still learning how to develop a research idea into a manuscript, so working with more senior researchers and seeing how they approach this process was incredibly valuable."

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💬 🫵 If you'd like to share where your summer took you, or want to share your favorite summer schools, let us know in the comments!

🔗 𝗜𝗻𝘁𝗲𝗿𝗲𝘀𝘁𝗲𝗱 𝗶𝗻 𝗮 𝗣𝗵𝗗 𝗮𝘁 𝘁𝗵𝗲 𝗖𝗼𝗺𝗽𝗹𝗲𝘅𝗶𝘁𝘆 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗛𝘂𝗯? Check out our graduate program: https://csh.ac.at/education/graduate-program/
🔗 𝗜𝗻𝘁𝗲𝗿𝗲𝘀𝘁𝗲𝗱 𝗶𝗻 𝘀𝗽𝗲𝗻𝗱𝗶𝗻𝗴 𝘆𝗼𝘂𝗿 𝘀𝘂𝗺𝗺𝗲𝗿 𝗮𝘁 𝗖𝗦𝗛? Learn more about our CSH Summer Internship Program: https://csh.ac.at/education/internships/

𝗗𝗼 𝘆𝗼𝘂 𝗳𝗲𝗲𝗹 𝗰𝗼𝗺𝗳𝗼𝗿𝘁𝗮𝗯𝗹𝗲 𝘄𝗶𝘁𝗵 𝗸𝗲𝗲𝗽𝗶𝗻𝗴 𝗺𝗮𝗻𝘆 𝗽𝗼𝘀𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀 𝗼𝗽𝗲𝗻? In chess, humans and AI engines seem to have fundamentally different answers to this question.

♟️♞ ♜ In 1997, a computer beat a human at chess for the first time. Today, that's hardly news anymore. But how exactly do AI engines play chess? And how does their play differ from ours?

To find out, Complexity Science Hub researchers Vito D. P. Servedio and Eddie Lee, together with Adamo Cerioli from the University of Parma, analyzed roughly 2,400 chess games move by move (both games between humans and games between AI chess engines) and measured what they called the "strategic tension" – meaning, they quantified how many possibilities remain open after each move. The wider the range of possibilities still open at any given point, the greater the "strategic tension" players experience.

💡 Insight one: 𝗠𝗮𝗰𝗵𝗶𝗻𝗲𝘀 𝗸𝗲𝗲𝗽 𝘁𝗲𝗻𝘀𝗶𝗼𝗻 – 𝗮𝗻𝗱 𝗶𝗻 𝘁𝗵𝗲 𝗲𝗻𝗱, 𝗰𝗼𝗺𝗽𝗹𝗲𝘅𝗶𝘁𝘆 – 𝗵𝗶𝗴𝗵

"The best humans build tension higher than any engine does; but only the engines can hold it to the end," Vito explains. While human chess grandmasters typically simplify positions as the game progresses, AI engines keep more possibilities open for much longer – sustaining complexity across the board. Or in Vito’s own words: "We light the fire. Machines keep the whole board burning."

💡 Insight two: 𝗧𝗵𝗲 𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝘁𝗼 𝘀𝘂𝘀𝘁𝗮𝗶𝗻 𝘁𝗲𝗻𝘀𝗶𝗼𝗻 𝗶𝗻𝗰𝗿𝗲𝗮𝘀𝗲𝘀 𝘄𝗶𝘁𝗵 𝗽𝗹𝗮𝘆𝗶𝗻𝗴 𝘀𝘁𝗿𝗲𝗻𝗴𝘁𝗵

Stronger human players maintain complex positions longer than weaker players, and classical games – with more thinking time – show significantly higher cumulative tension than rapid or blitz games. A similar pattern appears in artificial intelligence when the search depth is increased.

𝗕𝗨𝗧 (‼️):
“Importantly, our study does not establish a causal link between how AI handles complexity and its superior playing strength,” says Vito. “We observe a difference in how humans and AI manage complex positions, but we cannot conclude from our data that one explains the other.”

💡Insight three: 𝗟𝗲𝘀𝘀𝗼𝗻𝘀 𝗳𝗼𝗿 𝗵𝗶𝗴𝗵-𝘀𝘁𝗮𝗸𝗲𝘀 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀?

“Many of the world’s hardest decisions – in diplomacy, military planning or financial markets – share one defining feature: they involve navigating a huge, ever-changing web of possibilities,” Vito says. Chess cannot capture the complexity of real-world decisions. Still, the findings raise a huge question: what happens when AI systems that handle complexity fundamentally differently enter high-stakes decision-making?

👉 The study has been published in APS Open Science (American Physical Society): https://doi.org/10.1103/63cv-52fj

🔗 Read the full story: https://csh.ac.at/news/ai-doesnt-just-play-better-chess-it-manages-complexity-differently/
🔗 Vito's blog post: https://lichess.org/@/yanez/blog/elite-chess-engines-sustain-higher-strategic-tension-than-humans-in-chess/lUDQDvXf

🎉 Join us in welcoming Michael Kiran Huber to the Complexity Science Hub as a PhD candidate!

He joins the 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝗘𝗰𝗼𝗻𝗼𝗺𝗶𝗲𝘀 group, led by Frank Neffke, studying how AI is reshaping the way skills and know-how get coordinated in the economy – with a focus on software development.

Michael holds a master's in Logic and Computation from TU Wien, specializing in algorithmics and graph theory.

He's no stranger to CSH: he first visited in March 2025, working with Eddie Lee on reconstructing organizational structures from firms' online reading activity.

𝗪𝗲𝗹𝗰𝗼𝗺𝗲, 𝗠𝗶𝗰𝗵𝗮𝗲𝗹! 👋

🔗 More about Michael: https://csh.ac.at/michael-huber/
🔗 More about Transforming Economies at CSH: https://csh.ac.at/research/research-topic/transforming-economies/