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A PhD graduate from the National University of Singapore with an interesting backstory. I spent my first 3 years of grad school in the Engineering but transferred to the Business School in 2021 when two supervisors left me. Drawing from my experiences in the field, I now study the psychology of technology and understanding how employees respond to AI, robots, and technology.


About Me

Values I learnt along my journey

Despite being initially rejected, and having two supervisors leave, I've almost completed my Ph.D.


I learnt three sets of skills: teaching, consulting, and research, to thrive in different environments.


In each stage of my career, I assessed my shortcomings to decide which skills to develop.


My Story

My first jobs focused on following a cookie-cutter approach to consulting projects. This left me disillusioned, seeking alternative paths aligned with my passion and values.

During my time at University, I gained a reputation among my peers for my proficiency in statistics and research methods.

I left my job to establish a business teaching statistics and research methods to university students. However, I lacked the skills to scale and expand.

I decided to pursue a Ph.D. in Industrial Systems Engineering and Technology Management (Engineering Faculty) at the National University of Singapore.

The first hurdle I encountered was getting accepted into the Ph.D. program as my initial application was rejected.

Undeterred, I decided to apply for a master's degree instead. I worked tirelessly, balancing my tuition center to fund my studies while attending my master's classes part-time.

I began taking Ph.D level courses and applied to take the Ph.D qualifying exams. My goal was to complete all the necessary requirements and seamlessly transition into the Ph.D. program.

My dedication paid off when my supervisor offered me a full-time research assistant position. Being officially employed by the university also granted me a tuition concession.

During this time, I led several consulting projects, often bridging the gap between the company's executives and AI technical experts.

I also personally secured over $500,000 worth of research grants and was overseeing an additional $4 million in grants for my team.

My supervisor abruptly left the university in the second year of my Ph.D. candidacy. All my research funding became temporarily frozen, and my contract terminated within the month, jeopardizing my tuition concession.

I arranged a transfer to the Business School. However, I had to undertake additional modules and retake all my qualifying exams.

After ten months of administrative procedures, where I self-funded my Ph.D studies, I finally transitioned to the business school. But I would face my third significant hurdle, when my new supervisor also left the university.

The Business School was research-intensive, and many of my skills were less relevant. The currency in this new environment revolved around theoretical work and publishing top research papers.

Due to financial and time constraints, I made the decision to aim for graduation within the next three years despite the additional requirements.

My first goal was to establish a distinct research identity for myself.

Reflecting on my past experiences, I decided to focus on the psychology of technology.

I helped write a book chapter on the psychology of robots and AI to become familiar with the literature.

This facilitated many networking and collaborative opportunities, leading to several first-author projects.

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