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| | 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. |
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1 - 7 of 7
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 Deep transfer learning in human-robot interaction for cognitive and physical rehabilitation purposes
Aqdus Ilyas C., Rehm M., Nasrollahi K., Madadi Y., Moeslund T., Seydi V. Pattern Analysis & Applications 25(3): 653-677, 2022. Type: Article
Despite the huge number of publicly available images, emotion recognition for real applications suffers from a lack of relevant images. This challenge is considered here, where the task involves interpreting the facial expressions of patients with...
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Oct 17 2022 |
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From being there to watching: shared and dedicated telepresence robot usage at academic conferences
Neustaedter C., Singhal S., Pan R., Heshmat Y., Forghani A., Tang J. ACM Transactions on Computer-Human Interaction 25(6): 1-39, 2018. Type: Article
“I was there” is a sentence that in the future might be synonymous with remotely watching, or being telepresent. When the “being there“ means attending scientific events aimed at increasing scien...
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Mar 1 2019 |
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Bayesian multi-tensor factorization
Khan S., Leppäaho E., Kaski S. Machine Learning 105(2): 233-253, 2016. Type: Article
Data mining is increasingly facing the problem of extracting new knowledge from experimental data collected from complex phenomena. To extract hidden information, such datasets can be decomposed into the components that underlie them. ...
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Feb 23 2017 |
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Introduction to autonomous mobile robots (2nd ed.)
Siegwart R., Nourbakhsh I., Scaramuzza D., The MIT Press, Cambridge, MA, 2011. 488 pp. Type: Book (978-0-262015-35-6)
This revised edition of a pioneering book on mobile robotics includes a contribution from an additional author, significantly increasing the number of pages....
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Sep 8 2011 |
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The one-second war
Kamp P. Communications of the ACM 54(5): 44-48, 2011. Type: Article
“What time is it?” When we answer this trivial question, we don’t care about seconds. However, as computer scientists, we should....
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Jul 13 2011 |
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Learning, planning, and control for quadruped locomotion over challenging
terrain
Kalakrishnan M., Buchli J., Pastor P., Mistry M., Schaal S. International Journal of Robotics Research 30(2): 236-258, 2011. Type: Article
Advancing the ability of a legged robot to traverse difficult terrains is a challenge. Even tests for such advanced engineering prototypes as the LittleDog quadruped usually take place on regular terrain. This paper presents an integra...
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Apr 18 2011 |
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A macroscopic analytical model of collaboration in distributed robotic systems
Lerman K., Galstyan A., Martinoli A., Ijspeert A. Artificial Life 7(4): 375-393, 2002. Type: Article
As stated by the authors, this paper presents a macroscopic analytical model of collaboration in a group of reactive robots, acting without explicit communication or coordination....
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Mar 12 2003 |
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