
Workshops at 11th IEEE Swiss Conference on Data Science (SDS2024)
July 4, 2024, by Reik Leiterer, data innovation alliance
The Swiss Conference on Data Science (SDS) is Switzerland’s premier event for applied data science. The conference brings together leaders and science and business experts to exchange ideas and drive innovation in products and services, with a focus on the Swiss market. The SDS2024 took place in Zurich on May 30-31 at The Circle Convention Centre, Zurich Airport. If you want to get an impression how it was, have a look on the SDS2024 Flashback Video!
The 2-day conference started with an interactive workshop day to provide in-depth, practical and application-oriented insights into the latest developments in the field of data science and Artificial Intelligence. Over 450 participants took advantage of these opportunities and were able to benefit from exciting and professionally prepared and conducted workshops. Two of the workshops were supported by the Innovation Booster Artificial Intelligence to identify challenges and discuss possible ideas for radical solutions.
Next-Gen Cleantech Solutions: Mining Insights from Media and Patent Data with Natural Language Processing (NLP) and Large Language Models (LLMs)
The first workshop addressed challenges and solutions in the cleantech sector and was organized and moderated by HSLU (Guang Lu), ETHZ (Susie Xi Rao), FHNW (Daniel Perruchoud) and Equintel GmbH (Janna Lipenkova). All slides, data and further information are provided here.
At a time when tackling environmental challenges is of paramount importance, the cleantech industry plays a central role in promoting sustainable solutions. However, technological innovation in the cleantech sector requires a deep understanding not only of the technologies, but also of the market requirements. The workshop addressed the challenge how this information, usually embedded in a large amount of patent and media data, could be analysed using Natural Language Processing (NLP) and the latest advancements in Large Language Models (LLMs).

The workshop started with a talk about Disentangling the Global Innovation Landscape by J. Lipenkova and expert techniques were presented for analysing patent and media data for cleantech innovation including NLP, LLMs, RAG, and LLMs-augmented recommender systems. These inputs were then applied in a hands-on session and transferred to specific use cases, where the participants were able to try out the presented LLM-powered cleantech question-answering and recommendation system.

They key challenges identified and discussed were:
i) How to identify use cases and workflows in the cleantech sector that can be supported with natural language processing, large language models and retrieval-augmented generation techniques?
ii) How to evaluate the business value of different technical variations and how to quantify the ROI of such systems?
Generative AI for Well-Being
The 2nd workshop deals with the potentials of the new technologies around generative AI to help people to fight stress and increase their well-being. This workshop was organized by BFH (Souhir Ben Souissi, Mascha Kurpicz-Briki, Yannis Schmutz, Tetiana Kravchenko, Christoph Golz).
Generative AI has reached broad attention in the media over the last months. Different new use cases have been identified to support people in their daily work and make their work more efficient. But what about the well-being of the individuals? Different studies have shown that there is a rise of stress, also in Switzerland. On the one side, technologies such as chatbots or coaching technologies can support mental health or therapy in the setting of blended therapy. On the other side, there is a huge potential of multimedia interventions for elderly people, patients or stressed workers.


In this interdisciplinary workshop with a mixture of talks and hands-on parts, the different directions possible were discussed and how these latest technologies can be applied for the well-being of humans. One example was, how language models could be leveraged for advanced conversational interactions in the digital health domains or more in general, how generative AI could be a suitable technology in mental health care. Current challenges include the sometimes-limited patients health literacy which could leads to less effective treatments. This could be addressed with digital assistants providing personalized information’s and thus may increase patients therapy adherence. The practical part was all about enhancing well-being through multimedia generative AI with a focus on image and sound generation.
The day was concluded with a networking Apero and the presentation of the Swiss Viz Awards.
