The Future of Work Institute (FoWI) promotes productive and meaningful work as essential foundations of a healthy economy and society.

FoWI’s researchers focus on how people contribute to and benefit from new knowledge and practices, and their mission is to support thriving people and organisations in the digital age.

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Location: 

Future of Work Institute

Curtin Graduate School of Business 

78 Murray Street, Perth WA 6000


Telephone: +61 8 9266 4668


Email: fowi@curtin.edu.au

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Yukun Liu

Yukun Liu is currently a Postdoctoral Research Fellow at the Centre for Transformative Work Design. He received his PhD in Management and Organisations from the National University of Singapore (NUS) in 2017. Prior to starting his PhD at NUS, he received a Master’s degree in Business Administration from the Renmin University of China (RUC) in 2012 and a Bachelor’s degree in Human Resources Management from the Zhongnan University of Economics and Law (ZUEL) in 2010.

Yukun's research focuses primarily on employees' work experience and well-being. During his PhD, he was involved in several research projects that examined how certain experiences at work could influence employees' work effectiveness and well-being on a day to day basis. In his doctoral dissertation, he studied two seemingly opposite psychological states at the workplace, work engagement and mind wandering, and examined how these two types of mental experience at work could influence employees' daily work effectiveness (i.e., task performance) and daily well-being (i.e., burnout, satisfaction with job and life, etc.).

Since joining the centre in July 2017, Yukun has been working on a few projects relating to work design and employee well-being. He is currently engaged in exploring how certain characteristics of one's work could influence his or her health and well-being both in the short term (e.g., momentary, daily, or weekly effects) and in the long term (e.g., chronic effects accumulated through years or decades). The primary research approaches

he is employing include experience sampling (or daily dairy method),

time-lagged multi-wave examination, longitudinal modelling, etc.