Postgraduate valedictorian diaries

Our postgraduate valedictorians did not just complete their journeys with advanced knowledge in their respective spheres – in the process, they have gained valuable learnings beyond academics.

Dr Yeo Zhen Yuan
PhD in Physics

For Dr Yeo, his academic experiences at the Faculty of Science have shaped him into not just a physicist, but a scientist who understands that research is as much about human connection, intellectual courage and embracing the unknown – as it is about equations and experiments.

During his PhD candidature, Dr Yeo devised statistical models to characterise carbon allotropes for better battery performance. He also identified a new dengue genotype and pioneered an Expectation-Maximisation and Compression (EMC) algorithm that boosts electron-microscopy resolution by orders of magnitude. These breakthroughs, published in Advanced Materials and Nature Scientific Reports, stem from his interdisciplinary science training in the Special Programme in Science and collaborations with the National Environment Agency and the Centre for Advanced 2D Materials (CA2DM).

He had the opportunity to draw on his interdisciplinary training during an attachment at the Environmental Health Institute, where he “approached biological data with a physicist’s toolkit” in a study on the evolution and global dispersal patterns of a newly discovered cosmopolitan genotype of dengue virus type 2. By applying first principles thinking to phylogenetic data, he developed a visualisation that helped illustrate the virus’s evolution and heterogeneity in a new way.

He says, “This experience taught me that the most exciting science often happens when different fields share their unique perspectives. It reinforced my belief that interdisciplinary thinking isn’t just useful; it’s essential for tackling complex real-world challenges.”

Another standout moment in his journey was developing unsupervised machine learning methods to classify materials science spectra from STEM-EELS (Scanning Transmission Electron Microscopy – Electron Energy Loss Spectroscopy). The traditional analysis methods were prohibitively time-consuming and required extensive expert knowledge, making them unscaleable for large datasets. Dr Yeo worked with materials scientists at CA2DM to create algorithms that could automatically identify chemical phases in complex materials. What made this project special was how it “democratised access to advanced analysis” – suddenly, researchers without years of spectroscopy expertise could extract meaningful insights from their data.

He says, “This taught me that the best computational tools don’t replace human understanding; they amplify it, making sophisticated analysis more approachable and interpretable for the broader scientific community.”

Dr Yeo describes his PhD journey as “a long, winding hike that kept changing direction. There were wrong turns, lucky breaks and plenty of help from friends along the way.” One of the “most profound moments” for him – that “I don’t know” is not an admission of failure but the beginning of discovery. During his qualifying exams, he froze on a fundamental question and admitted his uncertainty. The examiner smiled and said, “Now you’re thinking like a scientist.” This moment was truly an eye-opening one, when he realised that “intellectual honesty and humility are strengths, not weaknesses.”  Whether facing hypothesis failures or experimental dead-ends, each setback became data, each question led to better questions, and each “I don’t know” opened new avenues of investigation.

Dr Yeo will be joining NUS’ Department of Statistics and Data Science as a Research Fellow, leveraging machine learning to uncover nanoparticle binding events.

Dr Shi Jia Yu, Venodda
PhD in Mathematics

Dr Shi describes her academic journey at the Faculty of Science as “enlightening and unforgettable, shaping my life in profound ways.” Her research focuses on stochastic control and optimisation, especially their applications in solving portfolio allocation and systematic market-making problems in finance.

During her four years as a postgraduate here, she had access to the best resources and a multitude of enriching learning experiences. For instance, as a Teaching Assistant leading tutorials for undergraduate classes, she says, “I saw similar confusion that I had gone through and also came across bright new ideas brought up by my students. At the end of each semester, reading their feedback made me feel like the hard work was worth it.”

In addition, she describes talking with students and seeing their progress as “very rewarding…it is amazing how helping others was a circle of reciprocity leading back to my own sense of fulfilment.”

Her internships enabled her to gain practical insights into the differences between research theory and real-world practices. She adds, “In the research world, we only cared about the convergence of algorithms and the mathematical elegance of results. In practice, the scenarios were much more complicated; we had to consider costs, test strategy volumes and specifically, address the time and space complexity of algorithms.” Equally crucial, Dr Shi learned that in industry, communicating ideas well and in an intuitive way is the key to “how ideas actually spread.”

She says, “We were given the opportunity to bridge our research with industry and apply our knowledge to solve real-world problems. I believe this is the source of NUS’ unceasing vitality.”

She has fond recollections of how small moments, when she took time for herself outside the office, led to greater clarity of thought.

“When I was researching the use of mini-batch Gaussian Process algorithms for mean field games, I was stalled trying to prove the algorithm’s stability and convergence.” However, after stopping by the Singapore Botanic Gardens, “New connections formed and new ideas popped up. Taking breaks in nature – you never know when an insight will hit!” she says.

Dr Shi is currently an Equity Derivatives Quantitative Strategist at investment banking company Morgan Stanley.