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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.


     

Configuration analysis and design of a multidimensional tele-operator based on a 3-P(4S) parallel mechanism
Xiao X., Li Y., Wang X.  Journal of Intelligent and Robotic Systems 90(3-4): 339-348, 2018. Type: Article

Parallel robots that use closed kinematic chains have interesting mechanical properties, such as stiffness, high precision, and good load capacity, at the cost of an increasing complexity in designing and solving their kinematics. This paper propo...

 

Computing all minimal hitting sets by subset recombination
Zhao X., Ouyang D., Zhang L.  Applied Intelligence 48(2): 257-270, 2018. Type: Article

In model-based fault diagnosis, there are two main components: a first-order-logic-modeled system, and the conflict set among the observations of the real system and the predictions from the model. If the system is faulty, the minimal candidate di...

 

Solving the robot-world hand-eye(s) calibration problem with iterative methods
Tabb A., Ahmad Yousef K.  Machine Vision and Applications 28(5-6): 569-590, 2017. Type: Article

Calibration means building the transformation matrices between the robot end effector and the camera (call it Z), and between the robot base and the reference system (call it X). The mathematical expression is the matrix equation, in homogeneous c...

 

A survey of imperatives and action representation formalisms
Srinivasan B., Parthasarathi R.  Artificial Intelligence Review 48(2): 263-297, 2017. Type: Article

What is an action? The agent observes two states at different times; if there is a change, then an action occurred. This implicit definition of action is adopted in this paper. At the beginning of artificial intelligence (AI), first-order logic wa...

 

Scalable computational techniques for centrality metrics on temporally detailed social network
Gunturi V., Shekhar S., Joseph K., Carley K.  Machine Learning 106(8): 1133-1169, 2017. Type: Article

To analyze social networks, where social interactions change over time, special graphs and methods are needed. In this paper, social networks are represented as temporally detailed (TD) networks; the aim is to compute centrality metrics on them, b...

 
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