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Personal profile

Education/Academic qualification

Artificial intelligence, expert systems, Doctor, Università degli Studi di Milano-Bicocca

Fingerprint Dive into the research topics where Marco Nobile is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Particle swarm optimization (PSO) Engineering & Materials Science
Parameter estimation Engineering & Materials Science
Particle Swarm Optimization Mathematics
Biological systems Engineering & Materials Science
Parameter Estimation Mathematics
Graphics Processing Unit Mathematics
Global optimization Engineering & Materials Science
Self-tuning Mathematics

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Research Output 2012 2019

1 Citation (Scopus)

A novel framework for MR image segmentation and quantification by using MedGA

Rundo, L., Tangherloni, A., Cazzaniga, P., Nobile, M., Russo, G., Gilardi, M. C., Vitabile, S., Mauri, G., Besozzi, D. & Militello, C., Jul 2019, In : Computer Methods and Programs in Biomedicine. 176, p. 159-172 14 p.

Research output: Contribution to journalArticleAcademicpeer-review

Magnetic resonance
Image segmentation
Image Enhancement
Magnetic Resonance Spectroscopy
Image enhancement

A novel multi-objective approach to fuzzy clustering

Spolaor, S., Fuchs, C., Kaymak, U. & Nobile, M. S., 2019, (Accepted/In press) 2019 IEEE Symposium Series on Computational Intelligence.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Fuzzy clustering
Multiobjective optimization
Global optimization
Sorting
Clustering algorithms

A swarm intelligence approach to avoid local optima in fuzzy c-means clustering

Fuchs, C., Spolaor, S., Nobile, M. & Kaymak, U., 1 Jun 2019, 2019 IEEE International Conference on Fuzzy Systems, FUZZ 2019. Piscataway: Institute of Electrical and Electronics Engineers, 6 p. 8858940

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Self-tuning
Fuzzy C-means Clustering
Swarm Intelligence
Particle swarm optimization (PSO)
Partitioning
3 Citations (Scopus)

Biochemical parameter estimation vs. benchmark functions: a comparative study of optimization performance and representation design

Tangherloni, A., Spolaor, S., Cazzaniga, P., Besozzi, D., Rundo, L., Mauri, G. & Nobile, M., Aug 2019, In : Applied Soft Computing. 81, 13 p., 105494.

Research output: Contribution to journalArticleAcademicpeer-review

Parameter estimation
Global optimization
Evolutionary algorithms
Artificial intelligence
Blood

Computational Intelligence for life sciences

Besozzi, D., Castelli, M., Cazzaniga, P., Manzoni, L., Nobile, M. S., Ruberto, S., Rundo, L., Spolaor, S., Tangherloni, A. & Vanneschi, L., 23 Oct 2019, In : Fundamenta Informaticae. 171, 1-4, p. 57-80

Research output: Contribution to journalArticleAcademicpeer-review

Computational Intelligence
Life sciences
Artificial intelligence
Swarm Intelligence
Protein folding

Prizes

Best paper award at IEEE CIBCB 2019

Marco Nobile (Recipient), 11 Jul 2019

Prize: OtherCareer, activity or publication related prizes (lifetime, best paper, poster etc.)Scientific

Bioinformatics
Artificial intelligence

Activities 2017 2017

  • 1 Invited talk

Turning uncertainty and lack of quantitative data into dynamic models with fuzzy logic

Marco Nobile (Speaker)
Oct 2017

Activity: Talk or presentation typesInvited talkScientific

Courses

Business Analytics

1/09/15 → …

Course

Computational Intelligence

1/09/18 → …

Course