Dr. Mauri, A
Andrea Mauri is a Postdoc at the Faculty of Industrial Design Engineering and is interested in the design, implementation, and evaluation of novel computational methods and tools - focusing on hybrid human-AI methodologies - to support the design processes addressing societal problems by integrating human and societal needs and values.
Andrea Mauri effort is devoted to the design, implementation, and evaluation of novel computational methods and tools, focusing on humans in the loop and data science techniques. I am interested in applying this body of knowledge in the design and development of tools to study and address problems of societal relevance. Domains of interest I investigated include sustainability, mental health, vulnerable groups of people, digital libraries, and privacy. Examples of relevant challenges include:
- Efficiency and Effectiveness of AI: AI-based solutions need to be able to exploit and combine a large variety of diverse and heterogeneous data sources, including different media, different data formats with a diverse granularity in both space and time. This includes both studying new AI algorithms and investigating how to effectively involve human intelligence to cope with the limitations of AI.
- Data integration: information retrieved with AI needs to be integrated with the data obtained with traditional approaches. To this end, it is crucial to investigate the characteristics of the two approaches to complement their weaknesses. Here not only do we face the problem of integrating heterogeneous data, but also issues related to the intrinsic differences due to their different natures (e.g., lab studies controlled environment vs free forum discussions; strict experimental protocol vs chaos in social media)
- Process integration: to ensure AI is used at its fullest it is crucial to investigate how and where it can be embedded within the design process. AI can be envisioned as a tool to be used in parallel to traditional investigation methods, or support and drive the design process itself.
Previously, Andrea Mauri was a postdoc at the EECMS faculty of TU Delft, in the Web Information System Group.He investigated how user-generated content and social big data can complement traditional methodologies - like ethnographies and lab studies - to inform policymakers in different contexts, such as energy, policies for vulnerable youth, and the urban environment. He got his Ph.D. in Politecnico di Milano in Information Technology in 2016, with a thesis about the development of crowdsourcing applications.