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Youngjun Cho is a lecturer in the department of computer science at UCL and a key academic member in GDI and UCLIC. Also, he is a co-founder and principal AI architect of KIT-AR (UCL/Sintef Spinout company). He explores, builds and evaluates novel techniques and technologies for the next generation of artificial intelligence-powered physiological computing1 that boosts disability technology innovation.
He has pioneered mobile thermal imaging-based physiological sensing and automated detection of affective states (e.g. mental stress). He obtained a PhD in computational physiology and thermography from Faculty of Brain Sciences at UCL. In 2011-2018, he worked as a senior research scientist at LG Electronics and led a variety of industrial research projects, successfully commercialising his novel sensing and machine learning technologies (e.g. gesture-driven advanced touchscreen for vehicles). He has authored more than 60 articles (including patents) in areas related to affective, physiological computing, human-computer interaction and multimodal sensing and feedback. At UCL, his research has been funded by Bentley Motors, EC H2020, NTT, EPSRC and DfID. Some of the achievements have been featured in forums for the general public such as BBC News, Phys.Org and Imaging and Machine Vision Europe.
1His definition of physiological computing is technology that helps us listen to our bodily functions and psychological needs and adapts its functionality. Its three technical components are physiological sensing, psychological state recognition and bio-feedback.
Youngjun Cho is a lecturer in the department of computer science at UCL and a key academic member in GDI and UCLIC. Also, he is a co-founder and principal AI architect of KIT-AR (UCL/Sintef Spinout company). He explores, builds and evaluates novel techniques and technologies for the next generation of artificial intelligence-powered physiological computing1 that boosts disability technology innovation.
He has pioneered mobile thermal imaging-based physiological sensing and automated detection of affective states (e.g. mental stress). He obtained a PhD in computational physiology and thermography from Faculty of Brain Sciences at UCL. In 2011-2018, he worked as a senior research scientist at LG Electronics and led a variety of industrial research projects, successfully commercialising his novel sensing and machine learning technologies (e.g. gesture-driven advanced touchscreen for vehicles). He has authored more than 60 articles (including patents) in areas related to affective, physiological computing, human-computer interaction and multimodal sensing and feedback. At UCL, his research has been funded by Bentley Motors, EC H2020, NTT, EPSRC and DfID. Some of the achievements have been featured in forums for the general public such as BBC News, Phys.Org and Imaging and Machine Vision Europe.
1His definition of physiological computing is technology that helps us listen to our bodily functions and psychological needs and adapts its functionality. Its three technical components are physiological sensing, psychological state recognition and bio-feedback.
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Jitesh Joshi,Youngjun Cho
Electronicsno. 7 (2024): 1334
CoRR (2023)
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CoRR (2023)
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SENSORSno. 19 (2023): 8244-8244
Temitayo Olugbade, Lili Lin, Alice Sansoni, Nihara Warawita, Yuanze Gan,Xijia Wei,Bruna Petreca, Giuseppe Boccignone,Douglas Atkinson,Youngjun Cho,Sharon Baurley,Nadia Bianchi-Berthouze
2023 11TH INTERNATIONAL CONFERENCE ON AFFECTIVE COMPUTING AND INTELLIGENT INTERACTION, ACIIpp.1-8, (2023)
2023 11TH INTERNATIONAL CONFERENCE ON AFFECTIVE COMPUTING AND INTELLIGENT INTERACTION WORKSHOPS AND DEMOS, ACIIWpp.1-8, (2023)
Int. J. Hum. Comput. Stud. (2023): 103078-103078
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