The 2025 edition of AI-Days will take place from January 27 to 29, 2025, in Geneva (January 27 and 28) and Lausanne (January 29). The AI-Days of the HES-SO Engineering and Architecture Department are organized by the Swiss AI Center for SMEs. The aim of the event is to provide a forum for discussing the practical use of new artificial intelligence technologies in the economic fabric.
Find more information and the registration on the official website:
The Swiss Robotics Day (SRD) is Switzerland’s most comprehensive exhibition on robotics for industry and research.
The SRD brings together industry, researchers, investors, engineers and students to exchange and share experiences, new ideas, and technologies. Matchmaking sessions facilitate collaborations and partnerships.
The SRD is a one-day event initiated by the Swiss National Centre of Competence in Research in (NCCR) Robotics – a flagship project with EPFL as leading house and ETH Zurich as co-leading house. The 2024 edition is organized by Innovation Booster Robotics, the University of Basel (Dept. of Biomedical Engineering) and EPFL. Of course we will be around as well, as AI and robots are somehow married 🙂
Check the program and register here – it’s worth it:
OpenStreetMap (OSM) is a valuable crowdsourced alternative to commercial and governmental geospatial data providers, with proven applications e.g. in the environment, tourism and emergency services. However, the lack of quality assessment tools hinders its wider adoption. This workshop aims to address the need for reliable and standardized data quality evaluation in OSM, with a focus on AI-based methods.
Current research prototypes such as ‘OSM Data Completeness’ and ‘ohsome quality analyst’ offer intrinsic solutions for data quality evaluation in specific regions based on user requirements. But there’s potential for improvement in usability and integration of extrinsic approaches.
The workshop will explore how these tools can be developed for production use and identify areas for further research. By discussing data quality evaluation solutions, the workshop aims to enable the establishment of an applied research and development agenda to better evaluate the suitability of OSM data.
The workshop will be held in German and English.
Registration and contact: Mail to stefan.keller@ost.ch
Speakers:
Dr. Hanspeter Bär – Innosuisse
Dr. Reik Leiterer – data innovation alliance
Dr. Giulia Aguzzi – Kistler Group
Dr. Lukas Lichtensteiger – ZHAW School of Engineering
Moderated by Dr. Maria Anselmi, Innosuisse
The RiskOn event on September 4 – 5, 2024 brings together experienced risk professionals with experts and talents from Switzerlands leading universities to co-create innovative solutions in the realm of risk management
Challenge 1: Use of new technologies for risk events classification and analysis
Financial institutions, as part of their risk frameworks, are required to capture, investigate/analyse and report on risk events. Given the volume of such events, their handling and analysis may be cumbersome and resource intensive.
Challenge 2: Fraud Risk Detection – How artificial intelligence can help?
Fraud risk is currently among the top risks in the financial sector. Big data and the rapid development of artificial intelligence has also contributing to that over the past few years. On the other hand, AI-methods can be efficiently used by banks for
early detection of fraud risk.
Challenge 3: How can AI be leveraged to enable CRO employees to work more efficiently?
With the rise in Artificial Intelligence solutions, there is the potential for improving/scaling/automating tasks performed by Chief Risk Officer (CRO) employees, when considering the associated risks, limitations and implementation cost.
Read more here:
Artificial Intelligence is advancing faster than we can fully comprehend. Its potential is immense, but so are the risks. Can we apply principles of democracy, decentralization, and transparency to unlock AI’s full potential while mitigating its risks? In this workshop, we will explore the intersection of DAOs, Blockchain, and Artificial Intelligence to identify suitable applications.
Find the full program on the official website!
There are many potential applications of AI in healthcare, particularly in the care of older people. This mainly refers to algorithm-based computing techniques that manage and analyze large data sets to make conclusions and predictions: from clinical decision support systems that can help detect delirium from medical records to wearable devices that can predict the risk of falls.
In this webinar, the needs and challenges of older people will be presented and defined and possible solutions based on artificial intelligence methods for specific application examples will be demonstrated.
Program
12h00-12h10: Presentation of Innovation Booster SILVER AGING
12h10-12h20: Presentation of Innovation Booster ARTIFICIAL INTELLIGENCE
12h20-12h30 : Dr. Vincent Grek – AI, medicine and sport for elderly people
12h30-12h40 : Daria Mühlethaler – Supporting the Care Givers with GenAI
12h40-12h50: Q&A
12h50-13h00 : Prof. Dr. Tobias Nef – AI and Digital Biomarkers for patients with Neurodegenerative diseases
13h00-13h10 : Dennis Eitner
13h10-13h20 : Q&A
13h20-13h30 : Wrap-up
Organized by IB Silver Aging and IB Artificial Intelligence
Due to rising social expectations and new laws on the responsible use of artificial intelligence (AI), it is becoming increasingly important for companies to ensure the trustworthiness and ethical acceptability of AI applications. However, instead of viewing these requirements merely as a challenge, they also offer companies the opportunity to innovate and differentiate themselves from the competition. The aim of this event is to jointly explore the business challenges in the area of responsible AI. It will also discuss how companies can proactively use these requirements to tap into new innovation opportunities and position themselves sustainably in the market.
Organized by GRdigital in cooperation with the Focus Topic Responsible AI and Expert Group Data Ethics, of the data innovation alliance
The Service à l’Innovation et à la Recherche (SIR) of the HES-SO is organizing a webinar on June 24, 2024 (12:00-13:00) to present two ideas supported by the Innosuisse Innovation Booster program. The funding opportunities in the frame of the Innovation Booster databooster and Artificial Intelligence, for which Nabil Abdennadher, professor at HEPIA, is the representative in French-speaking Switzerland, will be introduced and explained.
Organized by HES-SO, HEPIA and the data innovation alliance
The Workshop on Challenges in Data Management in Robotics aims to bring together robotics enthusiasts, researchers, and industry professionals to discuss and address the pressing issues surrounding data management in robotics applications. Through keynotes, case studies, and breakout groups, participants will gain valuable insights into tackling data-related challenges in robotics and explore potential solutions.
Organized by IB Robotics and IB Artificial Intelligence
Official Website and Registration
Agenda (subject to change!)
| 08:30 – 09:00: | Registration and Welcome Coffee |
| 09:00 – 09:30: | Opening Remarks by Swiss Cobotics Competence Center and Innovation Boosters Robotics and Artificial Intelligence. |
| 09:30 – 10:30: | Presentation of the challenges |
Challenge 1: Coworking and Learning |
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| Understanding human practices within the context of human-robot interaction is crucial for robots to adjust their behaviors appropriately. However, this presents several challenges. Not only do technical tasks and ethical considerations come into play, but also the fact that different individuals interact in unique ways, making the development of universally applicable algorithms extremely difficult. Furthermore, ensuring precise communication and task allocation in the human-robot workflow is essential, especially considering the proximity between humans and robots. | |
Challenge 2: Data Management |
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| Most robots work with both filtered and uncensored data, not only for robot training and learning tasks but also directly acquired in-process by physical sensors. Nowadays, tasks such as training may require a large amount of data. This can be challenging in terms of data overload, costs of data analytics integration, and robust data management practices. |
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| 10:30 – 10:45: | Coffee Break |
| 10:45 – 12:15: | Breakout groups |
| 12:15 – 13:45: | Networking Lunch |
| 13:45 – 14:45: | Presentation of the challenges |
Challenge 3: Responsibe Collaboration |
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| Both humans and machines occasionally fail at specific tasks, making it essential to consider failure scenarios in developing robust interaction frameworks. By understanding and leveraging failure data, we aim to improve the design, development, control, and robustness robots, ensuring more resilient and adaptive human-robot interactions. To achieve this, we will explore methods for identifying and capturing failure events, analyzing their causes, and utilizing this data to improve the reliability and performance of robotic systems. | |
Challenge 4: Self-improvement of Robots |
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| One aspect of robustness involves the capacity for a robot to enhance its knowledge and behavior autonomously. This means it should possess a degree of flexibility to adapt and apply abilities to new situations as needed. Achieving this context-driven, adaptive autonomy, which relies on common-sense knowledge and practical manipulation tasks, demands extensive programming and often involves on-platform data management & analytics. |
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| 14:45 – 15:00: | Coffee Break |
| 15:00 – 16:30: | Breakout groups |
| 16:30 – 17:00: | Conclusions: Sharing Discussions and Findings |
