The Medieval Culture of Food – a Case Study of Hippophagy in Medieval Hungary
In this interview László Bartosiewicz, Emeritus Professor of Osteoarchaeology at Stockholm University, discusses his recent research, undertaken with Erika Gál, on hippophagy, the eating of horse meat, in medieval Hungary. He considers their various sources of information and how they compare the archaeological occurrence of horse bones and any cutting marks on those bones, to known, but sometimes ambiguous references in written sources to hippophagy. This analysis demonstrates that people in the Carpathian basin ate horse meat, as well as keeping horses for many other purposes. He also shows how the horse bones were used to make skates, runners for sledges and even weights for fishing nets.László discusses the cultural implications of hippophagy in terms of social status, ethnic background and geographic location. He notes that while the Christian church did not out-right ban eating horse meat, it actively discouraged it, possibly because hippophagy may have been linked to earlier, non-Christian, religions and their celebrations. He notes that in this way, the foods that people eat help to define them as ‘one of us’ or ‘the other’ in terms of social acceptability.This podcast is part of a series of interviews covering central Europe in the medieval period for MECERN and CEU Department of Historical Studies.
11 Sept 2026
Teaching Analytics in the Age of AI - Seneca Miller
Puzzle Pieces: AI, Analytics and the First Real JobToo many data professionals are letting AI do their thinking. The result is broken pipelines, misaligned projects, and careers that stall at the first real challenge. Learning to use AI as a data analyst effectively, without surrendering the strategic judgement that makes the output valuable, is the capability that separates analysts who advance from those who plateau. In the first conversation of this series, we look at where AI genuinely accelerates analytics work, where it quietly leads you down the wrong methodological path and why adaptability is the most important attribute any new analytics graduate can develop. Host Eduardo Ariño de la Rubia is joined by Seneca Miller, a Data Analytics Scientist at eMedia Monitor in Vienna. She is a 2025 graduate of CEU’s Master of Science in Business Analytics programme and winner of the cohort’s Best Capstone Award. THINGS WE SPOKE ABOUT- Transitioning from marketing into analytics as a working professional- Being a company’s first data hire with full project ownership- How AI accelerated growth while creating knowledge blind spots- When to step back from AI and rely on your own judgement- What the MSBA should teach more and less of in the future GUEST DETAILSSeneca Miller is a Data Analytics Scientist at eMedia Monitor, a media monitoring company based in Vienna. A 2025 graduate of CEU’s Master of Science in Business Analytics programme, she won the cohort’s Best Capstone Award and joined eMedia Monitor as their first dedicated analytics hire. Reporting directly to the CEO, she designs and delivers data projects from the ground up, from NLP pipelines to topic classification models. QUOTES- “I can look at my project and say this from start to finish was what I did.” - Seneca Miller- “People will outsource their thinking to AI. And that’s where people get in trouble.” - Seneca Miller- “You might have linear growth, but this transforms everything to exponential growth.” - Seneca Miller- “If I didn’t have this course, I would just have a bunch of puzzle pieces still sitting there that I’d still be trying to put together myself.” - Seneca Miller- “It’s not the technical aspect of the work anymore that if you can write code, if you can put together a pipeline, it’s do you understand the business needs the business context, what that business wants, because every business incentivizes different things.” - Seneca Miller KEYWORDS #DataAnalytics #AnalyticsCareer #AITools #DataScience #MsbaProgram
31 Aug 2026
Teaching Analytics in the Age of AI - Ulrich Wohak
Signal Inflation: When Everyone Aces the Test But Nobody Learned AnythingToday our conversation explores why AI did not break academic assessment but made it impossible to verify, introduces the idea of signal inflation in technical fields and argues that sovereignty over decision-making is the one skill students must never outsource to a machine. We also reflect on how the MSBA curriculum at CEU will need to evolve and what a good relationship with AI looks like in research. Our host Eduardo Ariño de la Rubia is joined by Ulrich Wohak, a postdoctoral researcher in the Department of Economics at Central European University, where he teaches coding and data visualisation in the MSBA programme. He holds two MSc degrees from the Barcelona School of Economics and Vienna University of Economics and Business and previously worked as a competition economist for the British government. THINGS WE SPOKE ABOUT- From chef to competition economist: Ulrich's unlikely path into academia- Why AI empowers students but undermines academic assessment- Ulrich's AI stack and how he uses it in research- Maintaining sovereignty over decision-making in an AI world- Signal inflation, curriculum evolution, and the future of the MSBA GUEST DETAILSUlrich Wohak is a postdoctoral researcher in the Department of Economics at Central European University, where he also teaches coding and data visualisation in the MSBA programme. He holds two MSc degrees from the Barcelona School of Economics and Vienna University of Economics and Business, and previously worked as a competition economist for the British government. His current research, conducted alongside CEU colleagues, focuses on how AI is reshaping the labour market. QUOTES- "AI is such a cool product for students to engage more deeply with the material and to understand things maybe from a different angle. You know, it's a great learning tool, but it's also ripe for exploitation." - Ulrich Wohak- "I think one should be very aware of what one outsources to AI. And I think there are some things that one should not give up sovereignty over." - Ulrich Wohak- "I think students expect to learn very big ideas that deliver big results. But often I think what we're teaching is very small ideas that deliver big results." - Ulrich Wohak- "It's a signal inflation, if you want, rather than a signal erosion." - Ulrich Wohak- "I want to encourage them to use AI to empower themselves, not to outsource their thinking capacity." - Ulrich Wohak KEYWORDS #TeachingAnalytics #DataScience #AIEducation #AcademicIntegrity #HigherEducation
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