Hybrid Intelligence: Human-AI Co-evolution and Learning in Multi-realities (HI)

This research theme aims at developing data processing and computing technology for helping humans and machines understand each other in the following ways:

• By including machine learning methods for interpreting human emotions, intentions, preferences, and decision-making, it analyses facial expressions, body behaviors and physiological signals
• Endowing machines with capabilities for expressing emotions through advanced interactive behavior synthesis algorithms
• Helping humans to understand machines by visualising and explaining the internal states and status of data, algorithms, and models through multi-modality for mixed-reality interfaces

Contact person: Prof. Guoying Zhao

This theme strives to understand human learning and interaction processes to build systems which:

• Augment, rather than replace, human intelligence
• Emphasise our strengths and compensate for our weaknesses

This theme will utilise multimodal data based on multi-reality platforms and human-machine understanding to train, work, and collaborate with humans and AI, and then transfer the responsibility to humans. Hybrid Intelligence may need to acquire new human skills, which this theme also strives to gain understanding of.

Contact persons: Prof. Sanna Järvelä; Prof. Hanna Järvenoja

This theme investigates AI-methods for extending and changing human perception by means of digital spaces and realities, which co-exist with our physical world.

Virtual, mixed, and augmented reality technologies enable interaction with various degrees of virtual content in cyberverse and metaverse, thus seamlessly integrating human senses with multiple, concurrent realities. Intelligence augmentation, in turn, can enhance the cognitive abilities of humans by means of virtual assistants, and provide capabilities that go beyond normal perception.

Overall, this theme seeks to develop solutions that will demonstrate how multi-realities and AI together can boost human capabilities while bringing them to the next level.

Contact person: Prof. Janne Heikkilä

This theme investigates the ways in which Hybrid Intelligence can impact people's well-being in areas affecting the quality of life. This theme explores, for example, how the enhancement of augmented care can improve healthcare, and how Hybrid Intelligence can support continuous, life-long learning and education. This theme will work with various undeserved people and stakeholders to develop adaptive platforms for implementing Hybrid Intelligence.

This theme will provide feedback for the previous themes via cyclic processes, which help to push forward positive effects in future developments while mitigating the negative ones. The 6G connectivity expertise will facilitate the development work.

Contact person: Prof. Kristina Mikkonen

Leader: Prof. Sanna Järvelä, sanna.jarvela@oulu.fi

Vice leader: Prof. Guoying Zhao, guoying.zhao@oulu.fi

Prof. Janne Heikkilä, janne.heikkila@oulu.fi

Prof. Hanna Järvenoja, hanna.jarvenoja@oulu.fi

Prof. Kristina Mikkonen, kristina.mikkonen@oulu.fi

For general inquiries about the research programme, please contact coordinator Satu Kaleva, satu.kaleva@oulu.fi

For media inquiries and other communication related matters, please contact Anniina Keiskander, anniina.keiskander@oulu.fi, +358 50 436 3958

Tenure researchers

Andy Nguyen, Assistant Professor (tenure track) in Educational Technology; Artificial Intelligence (AI) in Education, Learning and Learning Processes, Faculty of Education and Psychology. andy.nguyen@oulu.fi

Haoyu Chen, Assistant Professor (tenure track) in Emotion AI, deep learning, human behaviour understanding, Center for Machine Vision and Signal Analysis (CMVS), Faculty of Information Technology and Electrical Engineering. haoyu.chen@oulu.fi

Juho Kannala, Part-time professor (tenure track) of augmented reality technologies in the Center for Machine Vision and Signal Analysis (CMVS), Faculty of Information Technology and Electrical Engineering. juho.kannala@oulu.fi

Post-doctoral researchers

Sari Pramila-Savukoski, Postdoctoral researcher in Emerging sustainable effects of human technology interaction on the quality of life theme. sari.pramila-savukoski@oulu.fi

Luna Huynh, Postdoctoral researcher in Learning Process Data Analytics theme. luna.huynh@oulu.fi

Sofoklis Kakouros, Postdoctoral researcher in Data and algorithm assisted AI theme.
Sofoklis.Kakouros@oulu.fi

Xiaoting Wu, Postdoctoral researcher in Emerging sustainable effects of human technology interaction on the quality of life theme. xiaoting.wu@oulu.fi

Fang Kang, Postdoctoral researcher in Data and algorithm assisted AI Hybrid Intelligence theme.
Fang.Kang@oulu.fi

Doctoral researchers

Boshra Najari, Doctoral researcher in Learning Process Data Analytics theme.
Boshra.Najari@oulu.fi

Yueyi Yang, Doctoral researcher in Data and algorithm assisted AI Hybrid Intelligence theme.
Yueyi.Yang@oulu.fi