Professional

Research

I have a  strong  science and technology research track record in diverse areas. These include academic work in systems biology and computational neuroscience, along with avocational work in quantitative finance.

Google Scholar publications here.

Academic Research

My academic research studied how simple biological systems, like genes or neurons, work together to produce complex life-like behaviors.

My PhD in systems biology studied how genes enable complex cellular behaviors by working together in “circuits.”  This discipline bridges a molecular description of living matter (DNA, protein, etc) with a behavioral description of living organisms (such as how cells respond to external stimuli). Using both experiments and models, I discovered and characterized a "timer" genetic circuit in the soil bacterium Bacillus subtilis. As a former electrical engineer, I enjoyed discovering and working out this circuit's unique hybrid digital-analog architecture and mechanism.

Two key takeaways emerged from my PhD. (1) A new understanding of circuit mechanisms behind cellular timers. Before this, cell-autonomous timers were rarely recognized (especially in microbes) and their molecular mechanisms were unclear. (2) An appreciation that gene regulation is highly dynamic. My work shows how pulsed gene regulation can enable complex cellular behaviors, here via a novel dynamic circuit design we named "polyphasic feedback."

I published this work in PLoS Biology (editor's synposis here) and Current Biology. My colleagues and I also reviewed pulsed gene regulation for a broad audience in Science.

My earlier Masters research modeled how biological neural networks can reliably store short term memories. Portions were published in Cerebral Cortex. My Masters thesis won two Best Thesis prizes from MIT's Electrical Engineering and Computer Science department. 

Other Research

In quantitative finance, I studied a simple approximation for the cumulative costs of annual Assets Under Management (AUM) fees.  These costs can be larger than most people realize. This result, building on work of John Bogle, Charles Ellis, and William Sharpe, helps conceptualize fee impacts on portfolios similar to how the Rule of 72 helps conceptualize growth rates and the Four Percent Rule helps conceptualize safe retirement withdrawals. The results are currently posted as preprint "Investment AUM Fee Costs: Evaluating a Simple Formula" (SSRN preprint). They have been accepted for Spring 2024 publication in the UNSW mathematics magazine Parabola.