Stefano Nichele

Stefano Nichele (født 1982) er en italiensk informatiker, og er tilsatt som professor ved Institutt for informasjonsteknologi ved Oslomet - storbyuniversitetet.

Nichele er også grunnlegger og ansatt i forskningsgruppen OsloMet Artificial Intelligence Lab - et senter for forsknings- og studentprosjekter innen kunstig intelligens og maskinlæring. Senteret er et samarbeid mellom Oslomet og Simula Metropolitan Center for Digital Engineering.

Nicheles fremste forskningsinteresser er kunstig generell intelligens, kunstig liv, komplekse systemer, evolusjonær utviklingsbiologi, biorobotikk, biologiske og kunstige nevrale nettverk og dyp læring.

Nichele har en mastergrad i informatikk fra Universitetet i Insubria i Italia. Han har også en doktorgrad i informatikk fra Norges teknisk-naturvitenskapelige universitet (NTNU). Doktoravhandlingen hadde tittelen Evolvability, Complexity and Scalability of Cellular Evolutionary and Developmental Systems, og ble publisert i 2015.

Nichele har tidligere arbeidet som forsker ved henholdsvis Institutt for datateknologi og informatikk ved NTNU og i forskningsgruppen Robotics, Evolution and Art Laboratory ved IT-universitetet i København.

Et utvalg av Nicheles vitenskapelige publikasjoner:

• Zhang, Jianhua; Yin, Zhong; Chen, Peng; Nichele, Stefano (2020). Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review. Information Fusion. Vol. 59.

• Pontes-Filho, Sidney; Lind, Pedro; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Tufte, Gunnar; Nichele, Stefano (2020). EvoDynamic: A Framework for the Evolution of Generally Represented Dynamical Systems and Its Application to Criticality. Castillo, Pedro A.; Laredo, Juan Luis Jiménez; de Vega, Francisco Fernández (Red.). Applications of Evolutionary Computation. Mangler. s. 133-148. Springer.

• Pontes-Filho, Sidney; Lind, Pedro; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Tufte, Gunnar; Nichele, Stefano (2020). A neuro-inspired general framework for the evolution of stochastic dynamical systems: Cellular automata, random Boolean networks and echo state networks towards criticality. Cognitive Neurodynamics.

• Valderhaug, Vibeke Devold; Heiney, Kristine; Huse Ramstad, Ola; Bråthen, Geir; Kuan, Wei-Li; Nichele, Stefano; Sandvig, Axel; Sandvig, Ioanna (2020). Criticality as a measure of developing proteinopathy in engineered human neural networks. 22 s. BioRxiv.

• Valderhaug, Vibeke Devold; Huse Ramstad, Ola; van de Wijdeven, Rosanne Francisca; Heiney, Kristine; Nichele, Stefano; Sandvig, Axel; Sandvig, Ioanna (2020). Structural and functional alterations associated with the LRRK2 G2019S mutation revealed in structured human neural networks. 27 s. BioRxiv.

• Mello, Gustavo; Pontes-Filho, Sidney; Sandvig, Ioanna; Valderhaug, Vibeke Devold; Zouganeli, Evi; Huse Ramstad, Ola; Sandvig, Axel; Nichele, Stefano (2020). Method to Obtain Neuromorphic Reservoir Networks from Images of in Vitro Cortical Networks. Huang, Tingwen (Red.). Proceedings of IEEE Symposium Series on Computational Intelligence (SSCI2019). Chapter: Neuromorphic Cognitive Computing (SNCC). s. 2360-2366. IEEE.

• Heiney, Kristine; Huse Ramstad, Ola; Sandvig, Ioanna; Sandvig, Axel; Nichele, Stefano (2020). Assessment and manipulation of the computational capacity of in vitro neuronal networks through criticality in neuronal avalanches. Huang, Tingwen (Red.). Proceedings of IEEE Symposium Series on Computational Intelligence (SSCI2019). Chapter: Artificial Life (ALIFE). s. 246-253. IEEE.

• Zhang, Jianhua; Li, Jianrong; Nichele, Stefano (2020). Instantaneous Mental Workload Recognition Using Wavelet-Packet Decomposition and Semi-Supervised Learning. Huang, Tingwen (Red.). Proceedings of IEEE Symposium Series on Computational Intelligence (SSCI2019). KAPITTEL. s. 409-415. IEEE.

• Zhang, Jianhua; Chen, Peng; Nichele, Stefano; Yazidi, Anis (2020). Emotion Recognition Using Time-frequency Analysis of EEG Signals and Machine Learning. Huang, Tingwen (Red.). Proceedings of IEEE Symposium Series on Computational Intelligence (SSCI2019). KAPITTEL. s. 403-408. IEEE.

• Berg, Joachim; Berggren, Nils Gustav Andreas; Borgeteien, Sivert; Jahren, Christian; Sajid, Arqam; Nichele, Stefano (2019). Evolved Art with Transparent, Overlapping, and Geometric Shapes. Bach, Kerstin; Ruocco, Massimiliano (Red.). Nordic Artificial Intelligence Research and Development: Porc. of Third Symposium of the Norwegian AI Society, NAIS 2019. 1. s. 3-15. Springer.

• Hanssen, Anders Braarud; Nichele, Stefano (2019). Ethics of Artificial Intelligence Demarcations. Nordic Artificial Intelligence Research and Development: Third Symposium of the Norwegian AI Society, NAIS 2019. 13. s. 133-142. Springer.

• Bergaust, Kristin; Nichele, Stefano (2019). "FeLT- The Futures of Living Technologies". Electronic Workshops in Computing (eWiC).

• Pontes-Filho, Sidney; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Nichele, Stefano; Tufte, Gunnar (2019). A general representation of dynamical systems for reservoir computing. Proceedings of the 9th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics. paper No. 8. IEEE.

• Roen, Haakon Haraldsen; Varankian, Vako; Nichele, Stefano; Bergaust, Kristin (2019). Gathering of the Hive: Investigating the clustering behaviour of honeybees through art and swarm robotics. Fellermann, Harold; Bacardit, Jaume; Goni-Moreno, Angel; Fuchslin, Rudolf (Red.). ALIFE 2019: Proceedings of the 2019 Artificial Life Conference. 00212. s. 505-506. MIT Press.

• Fullstendig liste over Nicheles publikasjoner, på Oslomets ansattside.
• Nicheles publikasjoner på DBLP: Computer Science Bibliography.