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18 April 17:30-19:00Kitchen, Uminova Innovation

It's finally time again for AI Umeå's meet-up, an interest group for all AI professionals, enthusiasts, researchers and industry leaders who are passionate about artificial intelligence! At our regular meetups you will get engaging presentations and discussions from different AI angles, the latest news on technological advances, ethical considerations, societal effects and much more. A chance for those with an interest in AI to become part of a new network.

This time we are proud to present Lili Jiang, associate professor (docent) in Department of Computing Science, Umeå University with a doctoral degree in computer science. Her research focus on fusing data science and artificial intelligence, AI trustworthiness (e.g., privacy, fairness). 

Lilis work revolves around data-driven research, specifically focusing on knowledge extraction from user-generated content—think social media. Through techniques like data extraction, linkage, and federation, she navigates the intricate landscape of data privacy. Join the discussion as Lili provides valuable insights and sheds light on the challenges faced in this dynamic field!

Date: 18/4
Time: 17.30-19.00
Location: In the kitchen at Uminova Innovation, Tvistevägen 47A.
Language: English 

🌯🥤Enjoy a light meal while you soak up the wisdom. Just let us know about any allergies or dietary preferences when you register. The event is free to attend.

See you there!


Lili Jiang
Associate professor (docent) in Department of Computing Science, Umeå University. Doctoral degree in computer science. Research focus on fusing data science and artificial intelligence, AI trustworthiness (e.g., privacy, fairness).

🎙️✨ My talk: Data Science and Data Privacy

As AI-powered knowledge-capturing technologies become more prevalent, ethical questions arise regarding individual and group privacy. Concerns about privacy breaches emphasize the responsibility of researchers to ensure that algorithms and systems developed do not misuse personal information or inferred data obtained from individuals. Our work involves data-driven research for knowledge extraction from user-generated content (such as social media) through data extraction, linkage, and federation. In this talk, I’ll provide an overview of the background, challenges, and insights related to data science and data privacy.

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