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Giuseppina Carla Gini
Politecnico di Milano
Milano, Italy
 

After graduating with a degree in physics from the University of Milano, Giuseppina Gini specialized in computer science as a post-doc fellow and worked on different artificial intelligence projects at the Politecnico di Milano (1972-1976). From 1976 to 1987, she held an assistant professor position at Politecnico di Milano, as well as various appointments as a visiting scholar and research assistant at Stanford University (California, USA) (in the Artificial intelligence Laboratory of the Computer Science Department and in the NMR Laboratory of the Medical School) and at SRI. Since 1987, she has been an associate professor at Politecnico di Milano, Faculty of Computer Engineering.

Gini has written and edited two books, and has authored about 200 refereed papers in scientific journals, books, and conference proceedings. Among other professional services, she organized and chaired the Symposium on Predictive Toxicology (Stanford, March 1999) for the American Association of Artificial Intelligence, and the AI&Math special session on Knowledge Exploration in Predictive Toxicology (January 2000).

She has been a partner in 16 international research projects (for NATO and the EU), and the coordinator of an EU project devoted to the development of new expert system methods in predictive toxicology. Moreover, she has directed seven national research projects.

Her main areas of research are knowledge representation and reasoning, with an emphasis on algorithms, biologically inspired solutions, hybrid systems, and computational efficiency. The main application areas in which she focuses her work are spatial and visual reasoning, human-machine interaction, and data mining. Over the course of her career, she has developed languages, simulators, and planners. In addition, she has cooperated with many European research centers over the past 15 years on various projects related to toxicity modeling, predictive systems, data mining, and in silico models.

Gini has been a reviewer for Computing Reviews since 1985, and has over 60 published reviews.


     

Assessing neural network scene classification from degraded images
Tadros T., Cullen N., Greene M., Cooper E.  ACM Transactions on Applied Perception 16(4): 1-20, 2019. Type: Article

Image processing and understanding human vision have shared interests and methods since the beginning of computer vision research. In recent years, deep learning and in particular convolutional neural networks (CNNs) have been applied to both, as ...

 

Industry-scale knowledge graphs: lessons and challenges
Noy N., Gao Y., Jain A., Narayanan A., Patterson A., Taylor J.  Communications of the ACM 62(8): 36-43, 2019. Type: Article

Many companies provide users with access to disparate services, from search to complex interactions, all of which need a large body of general and specific knowledge represented in knowledge graphs....

 

Cooperative heterogeneous multi-robot systems: a survey
Rizk Y., Awad M., Tunstel E.  ACM Computing Surveys 52(2): 1-31, 2019. Type: Article

To automatically solve complex tasks--for example, in domestic services, intelligent transportation, surveillance, and emergency response--we expect that one single robot cannot succeed; so, heterogeneous multi-agent robots could be the ...

 

A brave new world of genetic engineering
Greengard S.  Communications of the ACM 62(2): 11-13, 2019. Type: Article

While CRISPR, Gene Knockout Kit (GKO), and cryo-electron microscopy (Cryo-EM) may be acronyms unknown to the larger computer science (CS) community, they are well known in genetic engineering research. Software and hardware are extending and chang...

 

Learning from human-robot interactions in modeled scenes
Murnane M., Breitmeyer M., Ferraro F., Matuszek C., Engel D.  SIGGRAPH 2019 (ACM SIGGRAPH 2019 Posters, Los Angeles, CA,  Jul 28, 2019) 1-2, 2019. Type: Proceedings

Usually robots are checked and tested in virtual environments before delivering them to the real world. In this poster, however, the robot is only virtual, and users interacting with it are also rendered in virtual reality....

 
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