Siddharth Krishna Kumar (Sid) is a Ph.D student in the lab of Dr. Shripad Tuljapurkar. He has received two Master’s degrees, one in Civil Engineering, and one in Statistics, both from Stanford University. Before coming to Stanford, Sid did his undergraduate studies in Civil Engineering at the Indian Institute of Technology, Guwahati. His research focuses on various aspects of demography and population biology.
This content has been transcribed from an interview that took place on Stanford campus Tuesday, November 3, 2015 with CEHG’s Director of Programs, Cody Montana Sam and Communications and Outreach Manager, Katie M. Kanagawa.
Can you start by telling us a bit about yourself?
I’m Sid, and I’m a fifth-year PhD student in the Department of Biology. I work primarily for Dr. Shripad Tuljapurkar (Tulja), but most of my projects have been joined with Dr. Marc Feldman.
What first brought you to science and biology?
It was kind of odd. I was a poor student with a destructive personality and then suddenly in the 11th grade, I got interested in math and everything changed almost overnight. I was drawn to mathematical applications in physics, and so that became my focus. I did my undergraduate studies in civil engineering and came to Stanford to pursue a Master’s in Environmental Fluid Mechanics.
When I first came here, I couldn’t have dreamed that I would study biology. I hadn’t taken a biology course since the 8th grade. In the spring quarter of my first year here, I did a research assistantship with Tulja. The experience was amazing. I learnt a lot, and ended up working for him for about 9 months. At the end of it, he came up to me and said “Sid, would you consider doing a Ph.D?” and this was too good an opportunity to pass up, so I said yes. That’s how my journey began.
Can you describe some of your current research?
Recently, I have been analyzing a model called GCTA, which is commonly used in heritability estimation. Heritability is defined as the percentage of variation in a trait (say height or blood pressure) that can be explained by additive genetic variation. GCTA produces a near ten-fold improvement in the heritability estimates over its predecessors, and is therefore widely popular. It has been cited more than a thousand times.
I found it odd that although the model uses an overly simplistic description of the genetic architecture, it produces near perfect estimates of heritability. I have analyzed the mathematical properties of this model and have shown that the estimates it produces are unstable and unreliable. We have sent the draft of our paper around and people seem very excited. I have my fingers crossed; I hope it gets published.
UPDATE: Since this interview in November 2015, Sid’s paper was published in PNAS and has caused quite a stir. Click here to read the whole story.
Is there one person in particular who has had the biggest impact on your career?
Tulja has had a profound influence. My views on everything ranging from science to time management have been strongly influenced by the innumerable coffee trips we have had together.
For my last 2 projects, I worked very closely with Marc [Feldman] and I’ve gotten a lot of invaluable guidance from him too.
Can you speak a bit to the role you see CEHG playing on Stanford campus?
The conferences and talks held by CEHG have broadened my network in the community. They have been a big part of my learning and scientific growth.
I know that CEHG does a lot for science outreach and I think this is extremely important. During my stint as a volunteer teacher, I noticed that a lot of grad students and post-docs are eager to volunteer, and the schools in underprivileged communities desperately need these volunteers, but there are few ways of making these groups connect. I think CEHG is playing the important role of mediator.
You’re planning to graduate this Winter (2016). What is next for you?
I will be working for a company called Upwork in Mountain View. I had interned there last summer and had a wonderful time. I am looking forward to this new phase of my life.
Do you have any advice for other grad students or scholars as they are navigating their careers?
Try and do one course every quarter. That way, you won’t feel like you didn’t accomplish anything for a long period of time, even if your experiments end up failing. A lot of the coursework I had done in completely unrelated subjects (numerical algebra, for instance) ended up being extremely important in the last project I worked on. Learning never goes to waste.