Research Output per year
Personal profile
Education/Academic qualification
Artificial intelligence, expert systems, Doctor, University of Milan
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
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 2012 2019
2
Citations
(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 journal › Article › Academic › peer-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 proceeding › Conference contribution › Academic › peer-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. 8858940Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Self-tuning
Fuzzy C-means Clustering
Swarm Intelligence
Particle swarm optimization (PSO)
Partitioning
4
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 journal › Article › Academic › peer-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 24 p.Research output: Contribution to journal › Article › Academic › peer-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: Other › Career, 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 types › Invited talk › Scientific
Courses
Student theses
Predicting the turnaround time of an aircraft: a process structure aware approach
Author: van Hassel, O., 20 Dec 2019Supervisor: Firat, M. (Supervisor 1), Genga, L. (Supervisor 2) & Nobile, M. (Supervisor 2)
Student thesis: Master
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