Kort om
Stefano Nichele is Associate Professor at the Department of Computer Science. Nichele is the founder and deputy head of the Applied Artificial Intelligence research group. He recently started the Living Technology Lab (part of OsloMet AI Lab), where artificial life and complex systems approaches are used to understand intelligence.
Research interests:
- Artificial Life, Complex Systems, Evo-Devo, Cellular Automata
- Artificial Intelligence, Biological and Artificial Neural Networks, Deep Learning, Reservoir Computing
- Bio-inspired and Evolutionary Computation, Neuro-evolution
Personal website: http://www.nichele.eu/
Forskningsgrupper
Forskningsprosjekter
-
FeLT- Futures of Living Technologies
Det kunstneriske forskningsprosjektet FeLT - Futures of Living Technologies, er motivert av interessen for relasjoner og interaksjon mellom mennesker, levende organismer og maskiner, forbindelser på grensen til hva vi kan oppfatte som det levende i dag.
-
Hybrid Deep Learning Cellular Automata Reservoir (DeepCA)
Et langsiktig prosjekt som søker å integrere biologisk og kunstig intelligens.
-
Self-Organizing Computational substRATES (SOCRATES)
Et langsiktig prosjekt med mål om å gjøre effektive og kraftige dataanalyser tilgjengelig overalt, fra den enkleste sensornoden til den mest komplekse superdatamaskinen.
Publikasjoner og forskningsresultater
Vitenskapelige publikasjoner
Heiney, Kristine; Huse Ramstad, Ola; Fiskum, Vegard; Christiansen, Nicholas; Sandvig, Axel; Nichele, Stefano; Sandvig, Ioanna
(2021).
Criticality, connectivity, and neural disorder: A multifaceted approach to neural computation.
Frontiers in Computational Neuroscience
.
Vol. 15:611183.
https://hdl.handle.net/11250/2728005
Fladby, Torgeir; Haugerud, Hårek; Nichele, Stefano; Begnum, Kyrre; Yazidi, Anis
(2020).
Evading a Machine Learning-based Intrusion Detection System through Adversarial Perturbations.
NN, NN (Red.).
RACS '20: Proceedings of the International Conference on Research in Adaptive and Convergent Systems. Research-article. s. 161-166.
Association for Computing Machinery (ACM).
https://hdl.handle.net/11250/2729788
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.
https://hdl.handle.net/11250/2724664
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
.
https://hdl.handle.net/11250/2657791
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.
https://hdl.handle.net/11250/2735243
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.
https://hdl.handle.net/11250/2735246
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.
http://hdl.handle.net/11250/2644970
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.
https://ieeexplore.ieee.org/document/9002693
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. 410-416. IEEE. 10.1109/SSCI44817.2019.9002997
