Youngjun Cho

Youngjun Cho
Associate Professor, Director of MSc DDI || GDI & WHO Collaborating Centre for AT
[email address hidden]
+44 (0)20 3108 7177 (x57177)
Room: Rm 403
UCLIC and Computer Science
169 Euston Road
London, NW1 2AE
United Kingdom

Brief biography

Youngjun Cho is Associate Professor in the department of computer science at UCL and one of the key academic staff in GDI and MSc DDI (Disability, Design and Innovation). Also, he is a co-founder 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 mental states (e.g. stress). He obtained a PhD in computational physiology from Faculty of Brain Sciences and UCLIC at UCL (and obtained a MSc in Robotics, a BSc in ICT - summa cum laude). In 2011-2018, he worked as a senior research scientist at LG Electronics (full-time: 2011-2015, leave of absence: 2015-2018) and led a variety of industrial research projects. Amongst his contributions, novel 3D input and gesture recognition technologies (for advanced touch screen solutions in vehicles) were successfully commercialised in collaboration with automobile manufacturers including Porsche and BMW.

At UCL, his research has been funded by EPSRC, Bentley Motors, EC H2020, NTT, and DfID. Also, his earlier academic studies (including 4-year BSc, 2-year MSc, 3-year PhD) were fully funded - the primary funders includes prestigious scholarship/grant bodies: EC H2020, UCL-ORS, National Research Foundation of Korea, LG and Samsung. He has authored more than 70 articles (including patents) in areas related to affective, physiological computing, machine learning, human-computer interaction, accessible user interfaces, and multimodal sensing and feedback. Some of the achievements have been featured in forums for the general public such as BBC News, Phys.Org, Imaging and Machine Vision Europe, Science Daily, and SBS News.

1His definition of physiological computing is technology that helps us listen to our physiological and psychological needs and adapts its functionality. Its three technical components are physiological sensing, affect recognition and bio-feedback.

Research Supervision

As of 2023, Dr. Youngjun Cho supervises 9 PhD students, 2 Research Fellows, and over 10 MSc/MEng students (on average per year).
[Research Fellows]
• Dr. Mark Quinlan (PhD in Explainable AI and Cyber Security from the University of Oxford)
• Dr. Guangyu Ren (PhD in Deep Learning and Computer Vision from Imperial College London)

[PhD students]
• Jitesh Joshi (PhD student, Primary supervision)
• Katherine Wang (PhD student, Primary supervision)
• Zak Morgan (PhD student, Primary supervision)
• Merlin Kelly (PhD student, Primary supervision)
• Roxana Ramirez Herrera (PhD student, Co-supervision with Prof Holloway, Dr. Carlson)
• Shu Zhong (PhD student, Co-supervision with Prof Obrist)
• Simon Wei (PhD student, Co-supervision with Prof. Berthouze)
• Wen Mo (PhD student, Co-supervision with Prof Holloway and Dr Singh)
• Yifu Liu (PhD student, Co-supervision with Prof. Berthouze)

[Alumni - primary supervision only]
• Jade Savage (Physiological Computing, 2017/18 MSc in CSML, BSc from UCL) - DeepMind Scholarship | Microfocus
• Delaney Warren (Physiological Computing & AT, 2019/20 MSc in DDI, BSc from UCLA) - UCLFAA Scholarship
• Meg Obata (Physiological Computing & AT, 2019/20 MSc in DDI, BSc from Johns Hopkins University) - UCLFAA Scholarship
• Amit Patel (Machine Learning, 2018/19 MSc in ML)
• Chang Liu (Physiological Computing, 2018/19 MSc in DS) - Currently PhD Student
• Alok Suresh (Machine Learning, 2019/20 MSc in CSML) - Lanterne
• Zak Morgan (Machine Learning, 2019/20 MEng in CS, BSc from UCL) - Currently PhD Student
• Katherine Wang (Virtual Reality & AT, 2019/20 MSc in DDI, BSc from Penn state university) - Currently PhD Student
• James Wong-You (Human-Computer Interaction, 2018/19 MSc in HCI) - NHS
• Brian Min (Machine Learning, 2017-21 BSc/MEng in CS) - American Express
• Seunghoi Kim (Machine Learning, 2019/20 MEng in CS)
• Mahdi Nasrollahi (Machine Learning, 2019/20 MEng in CS)
• Su Yeon Oh (Haptics & AT, 2019/20 MSc in DDI)
• Yuliang Chen (Physiological Computing & AT, 2019/20 MSc in DDI)
• Bei Xiang (Haptics and Visual Impairment, 2019/20 MSc in DDI)
• Yu-Wei Yang (Physiological Computing and AT, 2020/21 MSc in DDI) - NHS
• Clara Moge (Physiological Computing, 2020/21 MSc in HCI, BSc from UCL) - Google / Youtube
• Yun Jung Yeh (Physiological Computing & AT, 2020/21 MSc in DDI) - JP Morgan
• William Davies (Physiological Computing, 2020/21 MSc in Machine Learning, BSc from UCL) - Amazon
• Steven McDonald (Physiological Computing, 2020/21 MSc in Machine Learning, BSc from Univ of Manchester) - Precise TV
• Yuxuan Liu (Physiological Computing & AT, 2020/21 MSc in DDI) - Huawei
• Pauline Hohl (Physiological Computing & AT, 2020/21 MSc in DDI) - CareLineLive
• Tianyun Hu (Physiological Computing, 2020/21 MSc in HCI) - Huawei
• Selina He (Physiological Computing, 2021/22 MSc in DDI, BSc from UCL) - KPMG
• Phoenix Wang (Physiological Computing, 2021/22 MSc in DDI, BSc from Univ of Toronto) - Cisco
• Sebastian Pauwels (Blockchain and Disability, 2021/22 MSc in DDI)
• Henry Drake (Physiological Computing, 2020-22 MSc in HCI, BSc from UCL)
• Sweccha Kansakar (Physiological Computing, 2018-22 BSc/MEng in CS) - Microsoft
• Rafaela Baquero Aguilar (Physiological Computing & VR, 2021/22 MSc in DDI, BSc from University of California, Berkeley)
• Rory Nicholas (Machine Learning, 2022/23 BSc in CS)
• Vincent Leong (Research Assistant in Bentley Comfort AI, 2021)
• Emil Almazov (Research Assistant in Bentley Comfort AI, 2021)
• Dr. Irena Arslanova (Short-term Postdoc, 2022)
• Yukun Zhou (Research Assistant in AI in Dementia Care, 2021-2022)


Programme Director, MSc Disability, Design and Innovation
COMP0145 (Module Leader, 100%): Research Methods & Making Skills
COMP0053 (Module Contributor, 30%): Affective Computing and Human Robot Interaction
COMP0159 (Module Leader): MSc Disability, Design and Innovation (DDI) - Dissertation

Boards and Committees

• UCL Grand Challenge of Transformative Technologies member: 2019 - present
• Snowdon Scholarship review panel (national level): 2019 - 2022
• Teaching Committee of MSc Disability, Design and Innovation: 2019 - present
• Conference Organising Committee: e.g. ACII 2022 (Tutorial Chair), ACII 2021 (Special Session Chair), ICMI 2020 (Senior Program Committee), ACII 2019 (Senior Program Committee) etc

Full Publication and Patent