From Research Analyst in quantitative finance to Engineer in a BioTech Startup.

Please tell us a little bit about yourself.

I am a computational engineer and I enjoy using scientific computing and data-driven approaches to solve real-world problems.

How did having a Ph.D. in Mechanical Science & Engineering prepare you for a career in the biotech industry?

My Ph.D. research work was in the fields of computational nanofluidics/nanobiotechnology. I built computational tools to understand and exploit the fluid behavior in/around micro/nanoscale geometries with targeted applications in the areas of:

• Nanoscale technologies for water purification
• Nanopore-based sensing of DNA, proteins, etc.
• Carbon-dioxide sequestration
• Quantitative finance.

So, there is a significant overlap between my Ph.D. training and responsibilities at OmniVis.

How did you first hear about OmniVis and why did you want to join the team?

I heard about OmniVis from a friend. Two big reasons for me to join OmniVis were:

• A good match of my training and professional experience with the job requirements/responsibilities.
• An opportunity to re-enter into the fields of science & technology from quantitative finance.

What does your day-to-day look like? What are your key responsibilities for OmniVis?

My primary responsibilities are:

• Perform data analysis for the science team for improvement and optimization of the diagnostic technology.
• Computationally assist the engineering team (through numerical simulations) for testing and improvement of the mechanical/fluidic design and performance of the diagnostic device.
• Develop data-infrastructure/tool-kit for consuming the diagnostic data and building predictive models for disease outbreaks.

What has been your favorite project you have been working on and why?

Among the projects undertaken in the first three weeks, ‘Identification of the best assay parameters for SARS-2 diagnostic technology’’ has been a great fun project to work on. The project required collaboration between the science team (domain experts/lab scientists who designed the diagnostic technology) and me (a data-driven engineer with no technical knowledge of the process) to identify the best assay parameters for the SARS-2 detection process. It was a very satisfying experience to work in such a complementary-expertise environment and produce statistically meaningful and physically sensible results.

Fun Fact About Yourself!

• I am a train-enthusiast, and as a young kid wanted to be a train/loco driver.
• My wife and I like building/repairing bikes. We were members of the bike-project of Urbana-Champaign until 2015 and built our own bikes from the assortments of donated/discarded bikes.