DSC SCHEDULE

09:30 – 9:45  Match Fixing Detection

Stefano Gemin & Domen Pozrl
Data Science Team Lead @ Sportradar & Data Scientist @ Sportradar

The Sportradar Universal Fraud Detection System monitors over 900,000 sport events per year, reporting suspicious betting activities to hundreds of sport federations across 30+ sports. To do this, over 5 billions betting transactions and 25 billions odds movements from 600+ betting operators are processed each year in real time by a ML model, with suspicious events being flagged for removal and integrity analysts leveraging prediction explanations for further analysis.

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09:45 – 10:00   Injury prediction in Soccer: Will it ever happen?

Arian Skoki
Research & Teaching Assistant @ Faculty of Engineering, University of Rijeka

Soccer, a dynamic sport combining skill and chance, poses a unique challenge for injury prediction. As technology advances, the prospect of leveraging machine learning to anticipate injuries gains momentum. However, the unpredictable nature of the game, coupled with individual variability and the complexity of injury mechanisms, raises questions about the feasibility of accurate predictions. This talk delves into the complexities of soccer injury dynamics, explores the current state of machine learning applications, and examines the hurdles hindering reliable injury forecasts, and confronts the problems associated with acquiring and preparing comprehensive datasets.

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10:00 – 10:15   Data-Driven Player Development: Nurturing Future Champions – Today

Marko Marjanovic
Chief Digital and Innovation Officer @ Artifit



Player development is a highly complex activity with numerous challenges, limited time for action and no room for error. In the quest for new perspectives, numerous scientific disciplines are involved, leading to the creation of enormous data sets that need to be collected, aggregated, and analyzed to serve as foundation for managing the process of selecting and training young footballers. How might data insights support coaches in developing future champions?

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10:15 – 10:30   Data-driven Match Analysis in Soccer

Henrik Biermann
Data Analyst @ Borussia Dortmund



While most data-driven analytics in soccer is still performed with qualitative video data, there exist two sources of soccer that recently gained popularity. Event data, comprising the player’s actions on the field in sport-specific terms, and position data, describing the movement of the players and the ball in two coordinates. As simple integration of these data sources can already lead to an improvement of usual workflows in soccer analytics (e.g., automatic retrieval of certain situations via event data), more complex (automatic) approaches are already developed and aim to offer a more substantial extension of the field up to the generation of new, unknown insights. In this talk, we discuss how data can improve the workflow of professional football analytics and shed light on the barriers that currently prevent the integration of more sophisticated AI algorithms in the sport.

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10:30 – 11:00   Panel discussion

Stefano Gemin & Domen Pozrl & Arian Skoki & Marko Marjanovic & Henrik Biermann
Data Science Team Lead @ Sportradar & Data Scientist @ Sportradar & Research & Teaching Assistant @ Faculty of Engineering, University of Rijeka & Chief Digital and Innovation Officer @ Artifit & Data Analyst @ Borussia Dortmund

15:00 – 15:15   Cyberpunk revolution

Max Talanov
Senior research associate @ Institute for artificial intelligence

The talk is dedicated to the set of technologies emerging at the moment including BCI, AI and neuromorphic technology that now are forming the foundation for a new generation breaking through approaches and applications. We see the paradigm shift in the understanding of how technology could influence and merge with humans and thus what is the human body. I’ll provide a vision of the future of the AI + humans perspectives that we call the Cyberpunk revolution.

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15:15 – 15:30   Fungal intelligence

Andrew Adamatzky
Professor @ UWE Bristol

The fungi is the largest, widely distributed and the oldest group of living organisms. The smallest fungi are microscopic single cells. The largest mycelium occupies over dozens of hectares and weighs several tons. Fungi possess almost all the senses as humans do. They sense light, chemicals, gases, gravity and electric fields. Fungi exhibit an electrical response to stimulation in a matter of seconds or minutes. We demonstrate that fungi process information in a manner similar to neurons. We represent fungi from an unusual perspective—as sensors, electronic neuromorphic devices and future computers. We propose fungal electronics, computing and intelligence as an alternative to currently adopted methodologies.

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15:30 – 15:45   Neuromorphic systems based on organic memristive devices

Victor Erokhin
Research Director @ Institute of Materials for Electronics and Magnetism, National Research Council (IMEM-CNR)

There are special requirements for the hardware realization of neuromorphic systems, namely:
Same elements must be used for memorizing and processing of the information;
It must allow parallel information processing;
It must have internal activity (cross-talk of elements, oscillation processes, effect of noise, etc.)
It must allow bio-realistic learning algorithms;
It must allow the formation of 3D systems with distributed connection of elements;
It must allow interfacing with nervous system.

We will consider the importance of each item and approaches for their practical realization.

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15:45 – 16:00   Rewiring Minds and Bodies

Jordi Vallverdú
Professor @ ICREA – UAB

Join us to explore the transformative impact of AI on Human-Robot Interaction (HRI) and Man-Machine Interfaces, with a focus on the intriguing concept of ‘rewiring bodies.’ Discover how AI-driven systems enhance interactions, empower robots to adapt to human preferences, and enable individuals to control machines through brain-computer interfaces and wearables. Dive into the forefront of HRI and interface technology, where AI is revolutionizing the way we understand, collaborate, and augment our physical and cognitive capabilities.

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16:00 – 16:15   NeuroAI Hardware Accelerators

Rastislav Struharik
Professor @ Faculty of Technical Sciences, University of Novi Sad

Current state-of-the-art AI systems, based on 2nd generation neural networks (Convolutional Neural Networks, Large Language Models, etc.), have proved to be highly useful in many application domains, however, their performance in terms of computational efficiency (speed and power consumption) makes them unsuitable for edge-based systems. The 3rd generation of neural networks, Spiking Neural Networks (SNNs), have been proposed to bridge the gap between the biological and artificial neural computing systems, using biologically plausible models of neurons to fully exploit the efficiency in the spatiotemporal signal coding and processing, and the corresponding power efficiency observed in the BNSs. Spiking neurons operate asynchronously, each neuron firing an output spike only when its state reaches a certain threshold. SNN information processing is event-driven, which makes a crucial difference between the 2nd and 3rd generation of ANNs. Although highly promising, current SNN technology has not reached maturity yet, lagging behind state-of-the-art 2nd generation ANN systems in classification accuracy. One way of moving forward is to develop more efficient SNN training algorithms, use more advanced spike information encoding schemes, etc. Another alternative, offering a mid-term solution, is to develop 2nd–3rd gen hybrid ANN/SNN systems, combining the advantages of both approaches. These hybrid systems could offer a comparable classification performance of current 2nd gen ANNs, while still being significantly more power efficient, due to the event-based processing, inherent to the 3rd gen SNN architectures. This talk will present existing results and future work on the development of hardware accelerators for 2nd and 3rd-generation ANN systems that is being conducted at the University of Novi Sad.

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16:15 – 16:30   Memristive Spiking Neural Networks

Natasa Samardžic
Associate Professor @ Faculty of Technical Sciences, University of Novi Sad

Neuromorphic computing, a computing approach directly inspired by human brain, shows significant potential in addressing the von Neuman bottleneck. Spiking neural networks (SNNs) represent a category of artificial neural networks which model behavior of biological neurons and synaptic connections are widely used in the domain of neuromorphic systems. Memristors (memory-resistors), as basic two-terminal circuit components offer unique properties including nonlinearity, multilevel resistance state, energy efficiency and nanoscale size. We will discuss the potential and opportunities of the implementation of memristors in spiking neural networks providing both synaptic plasticity and neuron spiking behavior.

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16:30 – 17:00   Panel discussion

Max Talanov & Andrew Adamatzky & Victor Erokhin & Jordi Vallverdu & Rastislav Struharik & Natasa Samardzic
Senior research associate @ Institute for artificial intelligence & Professor @ UWE Bristol & Research Director @ Institute of Materials for Electronics and Magnetism, National Research Council (IMEM-CNR) & Professor @ ICREA – UAB & Professor @ Faculty of Technical Sciences, University of Novi Sad & Associate Professor @ Faculty of Technical Sciences, University of Novi Sad