Computing for life
A new space for reflections at the interface of data, ML/AI, and biomedical research
Hi everyone, welcome!
I am a scientist working in the areas of computational biology and biomedical data science. That means I obsess about improving the ways in which all researchers can use the computer (algorithms & tools) to gain nuanced insights into health and disease from massive amounts of data.
What to expect in this space
My plan is to use this space to share and exchange thoughts about two broad areas:
I’ll write about topics and developments in my scientific fields, covering biomedical/computational problems, machine learning (ML)/AI methods & tools, publicly-available data, and open code & software.
And, from the perspective of a group leader, mentor, and educator, I will also write my reflections on academia & the scientific enterprise, research education & training, open science, and science communication.
[The most important part is done; feel free to skip to the end.]
Some personal context
… and this is the most personal it’s going to get!)
First, I belong to the Jurassic Park generation. This movie, which I saw when I was 9 years old and in a small theatre in a small South Indian suburb called Nagamalai, completely blew my mind. It filled me with fascination for genetics and molecular biology, and made me hope for an opportunity to do something in these areas when I grew up. Simultaneously, I have always had a deep love for mathematical and quantitative thinking. So, looking back, I consider myself lucky to have been able to follow both these streams throughout my education (without having to let go of one or the other) and make their confluence integral to my scientific career.
Next, having started my foray into computational biology in 2004–2006, I had the opportunity to be there at the early days of major advances in functional genomics and the application of ML to analyze, integrate, & gain insights from large numbers of high-dimensional datasets. These areas, along with the academic research & training enterprise itself, have transformed over these past 18 years, and I have had the good fortune to continuously work in this exciting interdisciplinary field building ML/AI methods & tools to advance biological and biomedical research.
Finally, though it feels like I had a straightforward journey to where I am now — K-12 ⭢ undergrad ⭢ grad school ⭢ postdoc ⭢ faculty position — my experiences along the way have been rich (with many highs & lows) and gained in the backdrop of two very different social, educational, & professional cultures (India & US). These experiences have, obviously, had a strong influence on my thinking about the education system, academic research, diversity-equity-inclusion in STEM, training & mentoring, and the role of science in society.
The exchange
In addition to writing a few things that may be interesting/useful to you, I mean for this to be a space for exchanging ideas with you. Folks from any background and at any career stage are welcome to chime in. And, to live up to this welcome, we all need to agree to keep our discourse constructive and respectful. From my end, I love to learn new ideas & perspectives, and am happy to change my mind about anything given compelling facts. So, keep your feedback coming. Cheers!