The Women’s Network is an informal network for all women working at CeTI, regardless of their scientific career level. It serves the purpose of networking, professional exchange and the development of ideas and should be largely self-directed. Ideas for the advancement of women in particular and approaches to removing career obstacles that come from the network can be submitted to the CeTI Programme Office, Career Development & Equal Opportunity, and the Womens’ Network Director.

Upcoming events

Artificial intelligence in cybersecurity increases system efficiency and precision to detect potential threats in manufacturing systems. Manufacturers expanding their horizons to different regions generate vast amounts of data to generate insights and use analytics to improve their product offerings. The global cybersecurity artificial intelligence market is expected to grow at a CAGR of 35.0% over the forecast period, reaching a market size of USD 31.2 billion by 2024. The artificial intelligence in cybersecurity market is primarily driven by the increase in data fraud and cyberattacks globally. The growing popularity of cyber technology makes smart manufacturing systems vulnerable to cyber risks. This creates the most pressing need for specific systems and procedures that can detect, predict and analyze such threats and protect factories from cyberattacks. Artificial intelligence is providing solutions to threats on a large scale, thus various industry players are focusing on the use of artificial intelligence for cybersecurity, thereby driving the growth of the global market. Security is a broad concept, and there are many different levels of “security” contexts in the industry. Artificial intelligence and machine learning techniques are applied and developed in this field. AI and security — in many ways — were made for each other, and modern machine learning approaches seem to fill the void left by previous rule-based data security systems. The purpose of this talk is to introduce industrial AI and highlight current trends and applications in the intersection of industrial AI and security. In addition to focusing on current applications (real world examples), we also showcase some of our contributions and discuss upcoming applications. Potential future applications are designed to spark ideas about some of the directions that AI technology is taking, for example, the use of machine learning techniques for bandwidth allocation to enhance latency performance in tactile internet.

Dr. Farah Jemili works as a Ph.D. at the University of Sousse, ISITCom, Mars Research Laboratory in Tunisia.

The lecture will take place in Barkhausen Bau (BAR I15) or virtually via Zoom:

Meeting ID: 688 2122 8788; Passcode: kH$s5G&9

Past events

Ubiquitous and context-aware sensors are increasing in number and aim at providing comfort and better life quality. They are spatially distributed and their computation capacity are still under-exploited. “Spatial Services” are a new generation of services exploiting IoT and spatially distributed data. They result from collective and decentralised interactions of multiple computing entities. They rely on coordination models providing built-in features leveraging bio-inspired patterns. Spatial services provide innovation capabilities for the software industry, connected objects manufacturers and edge computing industry.

This talk discusses first-order and higher-order emergence, the corresponding bio-inspired mechanisms or patterns, and how from this inspiration we can build actual reliable self-composing spatial services. To transfer these patterns into artificial systems and reliable services that build themselves on-demand, we base our work on a chemical-based coordination model, equipped with the above bio-inspired mechanisms and with additional learning / logic capabilities. Our solution provides a communication platform for the multi-agent systems working on behalf of these devices.

We illustrate the talk with examples and applications we developed in diverse areas such as: (1) first- and second-order emergence into swarm robotics; (2) self-composition of services on demand for a humanitarian aid scenario; (3) dynamic construction of contracts among producers and consumers of energy in smart electricity grids; (4) dynamic setting and verification of safety policies in a chemical warehouse; (5) dynamically following runners in a sport’s event.

Prof. Giovanna Di Marzo Serugendo received her Ph.D. in Software Engineering from the Swiss Federal Institute of Technology in Lausanne (EPFL) in 1999. After spending two years at CERN (the European Center for Nuclear Research) and 5 years in the UK as Lecturer, she became full professor at the University of Geneva in 2010. Since 2016, she is the Director of the Computer Science Center of the University of Geneva, Switzerland. She has been nominated in 2018 among the 100 digital shapers in Switzerland. Her research interests relate to the engineering of decentralised software with self-organising and emergent behaviour. This involves studying natural systems, designing and developing artificial collective systems, and verifying reliability and trustworthiness of those systems. Giovanna co-founded the IEEE International Conference on Self-Adaptive and Self-Organising Systems (SASO) and the ACM Transactions on Autonomous Adaptive Systems (TAAS), for which she served as EiC from 2005 to 2011. She recently set up a Digital Innovation Hub at the University of Geneva which aims at developing innovative services for the academic community, as well as others organisation bringing together students, researchers and stakeholders.

The lecture will take place in Andreas-Pfitzmann-Bau, Großer Ratssaal (APB/1004).

About Prof. Emily Cross

Emily S. Cross works as a Professor of Cognitive Neuroscience at Bangor University in Wales, where she directs the Social Brain in Action Laboratory. Through her research, she explores the experiential factors that shape the human brain and behavior when learning new actions or watching others in action. Using intensive training interventions and research paradigms involving dance, acrobatics and robots, she is particularly interested in questions concerning observational learning throughout the lifespan, motor expertise, aesthetics, and how people’s expectations shape human-robot interactions. Originally trained in dance and theatre, Emily completed undergraduate studies at Pomona College in California, a Fulbright fellowship in New Zealand, and a PhD in cognitive neuroscience at Dartmouth College, where she also performed and toured as a dancer. Her research has been supported by a number of national and international funding bodies, including the National Institutes of Health (USA), the Humboldt Foundation (Germany), the Volkswagen Foundation (Germany), the Netherlands Organisation for Scientific Research (NL), Marie Curie Actions (EU), the Economic and Social Research Council (UK), and the Ministry of Defense (UK). Two of her professional passions include advocating for women in science and exploring new ways to engage and excite the public about human neuroscience research.