Agnese is a PhD Student at the Knowledge Media Institute (KMi), the Open University, UK. Her research focuses on combining Knowledge technologies with Machine Learning to enhance the robots' ability to assist humans on their daily tasks. Specifically, she is interested in how robots can visually learn how to build a model of their environment and maintain it over time. Recently, she was part of the organising team of the 1st International Robotic competition to be held in a shopping mall (the 2019 SciRoc Challenge). Agnese received her M.S. in Information Sciences and Technology from the Pennsylvania State University.

Keys: Robotics, Computer Vision, Semantic Mapping, Lifelong Machine Learning, Information Retrieval, Knowledge Management

Team: Gianluca Bardaro, Jason Carvalho, Enrico Daga, Enrico Motta

KMi at the ISWS 2022 Summer School

KMi's Agnese Chiatti wins prestigious L'Oréal-UNESCO Award for Women in Science

Athena Swan Silver Award Success

Meet HanS, the Health and Safety Robot Inspector

Agnese presents her research on robots with common sense at the AAAI Spring Symposium

Chiatti, A., Bardaro, G., Motta, E. and Daga, E. (2022) A Spatial Reasoning Framework for Commonsense Reasoning in Visually Intelligent Agents, Proceedings of the 8th International Workshop on Artificial Intelligence and Cognition (AIC 2022), Örebro, Sweden

Chiatti, A., Motta, E. and Daga, E. (2022) Robots with Commonsense: Improving Object Recognition through Size and Spatial Awareness, Workshop: the 2022 AAAI Spring Symposium on Machine Learning and Knowledge Engineering for Hybrid Intelligence (AAAI-MAKE 2022), CEUR

Bardaro, G., Daga, E., Carvalho, J., Chiatti, A. and Motta, E. (2022) Introducing a Smart City Component in a Robotic Competition: A Field Report, 9, Frontiers Media S.A.

Chiatti, A. (2021) Towards Visually Intelligent Agents (VIA): A Hybrid Approach, 18th Extended Semantic Web Conference, ESWC 2021, Virtual, Online

Chiatti, A., Motta, E., Daga, E. and Bardaro, G. (2021) Fit to Measure: Reasoning about Sizes for Robust Object Recognition, Proceedings of the AAAI2021 Spring Symposium on Combining Machine Learning and Knowledge Engineering (AAAI-MAKE 2021), International Virtual Event