Jared Cheang

I am a recent Masters’ Graduate looking to transition into AI Safety Research. I come from a Computing and Data Science background plus also a “Tech For Good” believer, having developed various AI-based solutions in the public sector.

My shift into AI Safety grew naturally out of my technical work over the past few years - while working with many different AI systems and applications, I saw firsthand just how popular they were becoming. But despite all the excitement, I realized there was a huge amount of work needed to make sure these systems are truly reliable and trustworthy, with the biggest concern coming from the latest models opening a massive box of problems given how incredibly powerful they are, yet we do not fully understand its inner workings.

This realization is what directed my focus towards AI Safety. Since then, I’ve been engaged with the local AI Safety community and picking up various upskilling courses, like the ENAIS AI Alignment course and Cooperative AI research module under Prof Tan Zhi-Xuan.

My experiences have helped me develop as a dedicated generalist, someone who enjoys contributing across various technical and leadership domains. This cross-functional mindset is grounded in a strong academic foundation, where I was fortunate enough to be awarded an accelerated direct Masters scholarship (top 3% of cohort) and offered a CS PhD at a top 10 institution. This foundation, alongside a belief in teamwork, has led to some rewarding practical outcomes. For example, I had the opportunity to lead a team that secured 1st runner-up in a national hackathon during my year abroad. This commitment to building and contributing also fueled my early entrepreneurial experience as a student co-founder, which successfully secured a capital grant of $10,000.

I am always keen to connect with others in the field. If you are interested in discussing collaborations on AI Safety research, please feel free to reach out!