Ongoing projects
Based on the premise that it takes two to tango, the project aims to build a synergistic approach to human-machine decision making The international consortium behind TANGO will develop the theoretical basis and computational framework for hybrid decision support systems (HDSS) in which humans and machines are aligned in terms of values and goals, know […]
Partners
Ministry of Family Care and Demography | University of Trento | A 11 – Initiative for Economic and Social Rights | Share Foundation
Advanced deep learning solution that reduces the complexity and increases the speed and reliability of soil carbon monitoring and verification. Learning from various satellite inputs, meteorological data, and reference soil datasets. Global solution, ideal for food and beverage companies, landowners, and carbon credit initiators.
Partners
MALTAccelerate | Smart Cloud Farming
Participant real-time engagement monitoring during online classes or meetings. Secure, end to end encrypted solution, suitable for on-premise deployment. Solution will be extended to transcript generation and semantic search.
Partners
MALTAccelerate | Cinteraction
Development of a platform for automatic diagnosis of mammographic images. Developed Computer Vision solution tailored for mammogram analysis. Models trained and fine tuned on thousands of patients. Gives probabilities of lesion in breast tissue in mammograms.
Partners
Institute for Oncology and Radiology of Serbia | Ministry of Health
Amidst the mounting challenges posed by climate change, particularly escalating urban flooding events, the Institute for Artificial Intelligence R&D of Serbia (IVI) introduces the ARTIFACT project, focusing on the synergy of Artificial Intelligence (AI) and engineering for urban flood resilience. Recognizing the limitations of existing physics-based models, the ARTIFACT seeks to harness AI’s capabilities to […]
Partners
Technical University of Delft | IHE Delft | Technical University of Hamburg
Urban design faces challenges in engaging the public for Nature-based Solutions (NBS), hindering sustainable development. With the support of the Marie Skłodowska-Curie Actions programme, the PACT-NBS project aims to bridge this gap. By integrating public value frameworks into serious gaming tools, PACT-NBS facilitates the co-creation of NBS projects. It systematically establishes public value metrics, develops […]
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Accurate prediction of daily inflows into reservoirs is crucial for effective water resource management and planning. This project introduces an artificial intelligence framework designed specifically for predicting daily inflows in the Drina River basin. It integrates machine learning algorithms with hydrological data, including historical inflow patterns, meteorological variables, and reservoir levels. The framework employs a […]
Partners
IMP Automatika d.o.o. | Jaroslav Černi Water Institute
IVI is a partner in the EU project embrAIsme within the framework of the Interreg Europe program. The program has a duration of four years and started in April 2024. The consortium consists of a total of ten partner organizations from eight different European regions. Further information about the project, the partner organizations, the addressed […]
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River water quality is crucial for the environment, biodiversity and human health. To improve the decision making process and, in turn, enhance the river health, the Artificial Intelligence (AI) framework for water quality monitoring, prediction and alarming is proposed. This framework relies on the existing water quality and quantity measuring system capable of providing only […]
Partners
Faculty of Technical Sciences, University of Novi Sad
In collaboration with a startup from the USA, we are developing a generative AI-based platform for peptide design targeting specific proteins. In addition to the generative process, the platform includes candidate filtering using the state-of-the-art Alpha Fold 2 model to predict the binding affinities of designed peptides and the target protein.
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This project primarily focuses on verifying the accuracy of information in texts generated by generative language models within the biomedical field. The developed system aims to provide users with accurate, real-time responses to their queries supported by relevant sources. This project involves fine-tuning and prompting generative language models, lexical, semantic, and hybrid search, and metrics […]
Partners
Bayer AG
The aim of this pilot project, launched jointly with three large healthcare centers in Serbia – the University Clinical Centre of Serbia, the University Children’s Clinic Tiršova, and Zemun Hospital – and in cooperation with the innovative Japanese pharmaceutical company Takeda, is to reduce the complexity of Fabry disease diagnosis by employing modern AI techniques. […]
Partners
Takeda
Creating an AI platform for the drug supply prediction for 25 million users across 1752 location across Côte d’Ivoire. The platform has also been designed to perform and control the medicine supply chain in Côte d’Ivoire. The goal of this project is to contribute in improving the health system and the overall quality of life […]
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As part of this pilot project, an analysis of user emails was carried out in cooperation with Telekom company to enhance the quality of customer support and user satisfaction. After anonymization, the emails were processed using the topic modeling method, leveraging state-of-the-art language models for the Serbian language. The developed system enables fast and automatic […]
Partners
Telekom Srbija
This project is aimed to develop and evaluate deep learning models for predicting spinal curvature from 3D back surface scans as a radiation-free alternative to traditional X-ray methods. Two primary approaches were investigated: a Convolutional Neural Network using depth maps and a Point Cloud Transformer using 3D point clouds. The models were optimized and compared […]
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In collaboration with a startup from Japan, we are researching and developing a platform for the design of small molecules. The platform includes state-of-the-art AI models for predicting molecular properties based on small sets of experimental data, as well as generative molecule design to optimize the desired property.
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The objective of this project was to leverage transfer learning capabilities to develop a method enabling the training of a model to recognize Named Entities for which it has not been trained, with no or minimal supporting training examples. This method necessitates the input data transformation for the binary classification of tokens and employs a […]
Partners
Bayer AG
The project revolves around the development of new Natural Language Understanding (NLU) tools designed to help analyse free form medical texts in Serbian. These will be used to aid in the targeted screening of Fabry disease (FD) and Hunter syndrome (MPSII) in order to improve the diagnosis and treatment of FD and MPSII patients.
Partners
Takeda
Green program of cooperation between science and economy of The Science Fund of the Republic of Serbia
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The use of electronic noses in industry enables the monitoring and control of a wide range of manufacturing processes in an industry in a minimally invasive way. Its application in the food and beverage industry is particularly noteworthy, where it can be used for quality control of products and monitoring of certain biochemical processes. The […]
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With the help of our Chinese colleagues we have been able to create a 2.7 billion parameter NLU model able to translate between Serbian and 52 other languages. This is just a starting point and we hope to improve the model’s performance in the time to come, but you can try it out now if […]
Partners
Peng Cheng Laboratory
Based on the premise that it takes two to tango, the project aims to build a synergistic approach to human-machine decision making The international consortium behind TANGO will develop the theoretical basis and computational framework for hybrid decision support systems (HDSS) in which humans and machines are aligned in terms of values and goals, know […]
Read more
The increase of textual data volumes necessitates a swift progression in data science, particularly in Natural Language Processing (NLP). The UniDive action is centered on the task of preserving linguistic diversity, with a focus on understanding both the differences between languages and the nuances within them. UniDive reframes technology from a potential threat to an […]
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Past projects
This project aimed to determine the underlying causes of vaccine hesitancy regarding COVID-19 among young individuals in Serbia, thereby contributing to an increase in vaccination rates. The dataset employed in this research comprised tweets related to COVID-19 vaccination. By integrating sentiment analysis using advanced language models and topic modeling techniques, we identified several categories of […]
Partners
USAID | UNDP