ERASMUS+ KA171: Workshop on advanced ICT for the agri-food industry
PhD students Sun Yun and Kong Chuiyu under the supervision of the host mentor, associate professor Marija Brkić Bakarić, and other members of the Lab for Data Engineering and Computational Linguistics of the Faculty of Informatics and Digital Technologies professor Maja Matetić, associate professor Vanja Slavuj, PhD student Dejan Ljubobratović, and head of the lab, associate professor Lucia Načinović Prskalo participated in a workshop on advanced ICT for the agri-food industry that tackled:
- AI and data-driven solutions for sustainable agriculture
- Computational models for agri-environmental data analysis
- Smart applications and ICT tools supporting food systems
The workshop enabled participants to explore cutting-edge technologies shaping the future of food production and supply chains.
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Erasmus+ KA171: Research and collaboration in action
Two PhD students from the China Agricultural University visited Lab for Data Engineering and Computational Linguistics of the Faculty of Informatics and Digital Technologies in the period from April 1 to May 31, 2025. Along with the lab members they coninued working on joint research studies and on technology development. Presentations of the conducted research will be organized at 10:00 am on May 22, 2025 in room No 357. The workshop is open to all interested parties.
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Erasmus+ KA171: Round table
Obranjen doktorski rad
U ponedjeljak, 28. travnja 2025. u 12 sati Ive Botunac je obranio doktorski rad SUSTAV ZA AUTOMATSKO TRGOVANJE DIONICAMA NA TRŽIŠTU KAPITALA
TEMELJEN NA DUBOKOM PODRŽANOM UČENJU. Rad je izrađen pod mentorstvom prof. dr. sc. Maje Matetić, a obranjen je pred povjerenstvom za ocjenu i obranu doktorskog rada u sastavu prof. dr. sc. Ivo Ipšić, prof. dr. sc. Sanja Seljan i izv. prof. dr. sc. Marija Brkić Bakarić. Čestitke Ivi i mentorici na izvanrednim postignućima!
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Erasmus+ KA171: PhD Students from China Agricultural University Visit FIDIT
As part of our ongoing commitment to international research collaboration and knowledge exchange, Lab for Data Engineering and Computational Linguistics of the Faculty of Informatics and Digital Technologies is pleased to host two visiting PhD students from China Agricultural University in the period from April 1 to May 31, 2025.
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ERASMUS+ KA171: New Insights from the project
In a recent joint study published in Aquaculture (ScienceDirect), we tackled a crucial yet often overlooked question: how do we measure stress in aquatic animals—particularly when they’re exposed to challenging conditions?
We performed a comprehensive review of existing stress-indicating methods in fish and shellfish, distinguishing between two categories:
- Contact indicators, such as measuring cortisol levels in blood or tissues—accurate but invasive and sometimes harmful.
- Non-contact indicators, like monitoring behavior, changes in water chemistry, or using imaging and telemetry—a gentler approach, better suited for animal welfare.
We propose a new classification system to organize these metrics by how invasive they are and how reliably they signal stress.
Key Findings
- Traditional contact methods (e.g., blood cortisol) remain reliable but stressful and often impractical for large-scale use.
- Emerging non-contact techniques—behavioral monitoring, remote imaging, and water-based indicators—show promise for welfare-friendly stress detection.
- The proposed taxonomy helps aquaculturists balance accuracy with animal wellbeing, guiding them toward the most appropriate stress-measurement strategy for specific situations.
The study is available here.
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