About me
Current interests
My overarching interest is encapsulating the complexity of (biological) systems. I love exploring and developing tools that allow analysis of the molecular biological system as a whole.
Most recently, this has brought me to representation-based approaches, primarily in transcriptomics and proteomics.
In a more general sense, I enjoy learning about how other fields (from NLP to GIS) approach 'data', and theorising about information more broadly.
Academic background
I always like to say that I ended up in life sciences due to a single gif,
which solidified my fascination for the molecular mechanisms of life. The life sciences did face competition when picking my major (which you do at enrolment in the Netherlands) though,
as fields like computer science, systems-oriented sciences, and policy and society were at the back of my mind.
I did really like biology and chemistry's experiment-based approach to science, and so I enrolled in Molecular Life Sciences
(now Molecular and Biophysical Life Sciences) in Utrecht.
That programme, primarily hosted by the Chemistry department,
definitely shaped me as a scientist; emphasising fundamental understanding over rote memorisation, focusing on the big picture instead of navel-gazing on one factor,
and prioritising independent thought over blindly following protocols.
After my first year, I did leave the chemistry labs behind, as I realised their (excellent) work in structural biology was not what I was looking for:
analysing genomes and transcriptomes, rather than painstakingly figuring out individual protein structures, was much closer to my goal of understanding what makes cells tick.
As such, I indulged in programming and statistics, as deciphering (biological) datasets to understand large-scale biology was what really got my attention.
In a way, that was a natural fit, bringing back some of the computer science skills and systems outlook that had appealed to me in the past as well.
In doing so, I even got to work at the group that
originally coined the term bioinformatics!
In keeping with this interdisciplinary trend, I decided to look beyond the Netherlands to go study in Hong Kong for a semester.
While there, I focused on politics, society, and governance of East Asia, to gain a scholarly background in radically different academic disciplines and to satisfy my interests in global affairs.
Although the different standards of these 'foreign' disciplines definitely took some getting used to, I've gained some of the most valuable academic experience of my career here.
Although I am a natural scientist at heart, learning to do research for history and political science thoroughly reminded me that our scientific persuits are fundamentally human endeavours,
with all the pitfalls that that brings. Many choices in science and technology have real-world consequences, from utilising
mass incarcerated populations' genomes in authoritarian regimes in population genetics
to crime-predicting algorithms leading to self-fulfilling prophesies in ML, and these topics deserve proper thought.
After returning to Utrecht, I finished up my bachelor by following a minor in Applied Data Science and doing my thesis research in genomic regulation of transcription.
At that point, there really was no question that I wanted to continue for a master in bioinformatics.
Looking around Europe, Copenhagen caught my eye: perhaps the biggest life sciences hub in Europe, with great bioinformatics faculty hosting a great MSc programme, and in a lovely city to boot.
Ever since, I've been nothing but glad that I've been admitted here, as it's been great to get involved with leading bioinformatics work in both academia and industry.