As a PhD student and researcher in MIT's Institute for Data, Systems, and Society, I utilize and contribute to state-of-the-art energy systems optimization models to understand how we can design affordable, reliable, and clean grids for the future.

At MITRE, I design optimization models for complex systems that help our federal sponsors solve problems. I explore problems in a wide range of areas including energy resilience, synthetic biology, and transportation and logistics.

At MIT, I contributed to GenX, an open-source optimization model for energy grid operations and planning. Using this model, I conducted novel research evaluating the cost-saving potential of power plant retrofits in transitioning to a low-carbon electric power system. See link to my master's thesis entitled "Retrofit Solutions to Electric Power Sector Decarbonization in the American Midwest".

As an Operations Research Intern with MITRE, I had the opportunity to 1) build USAF aircraft scheduling optimization models, 2) develop the IEEE standard for spectrum consumption modeling, and 3) design an economic impact model for new renewable energy developments. (1) I designed, implemented, and incorporated an algorithm that improved the aircraft maintenance flow at three times the rate of the previous standard. (2) I contributed core mathematical functionality and wrote over 300 unit tests to rigorously test MITRE's software for quantifying interference relationships between transmitters and receivers. (3) My economic model was used by local government planners while they explored how to transition their communities to a low-carbon grid.

On May 4, 2020, I successfully defended my Honors thesis on how ride-hailing platforms like Uber and Lyft can incorporate self-driving cars to improve urban mobility. By incorporating driver-rider pairings, storage, charging or refueling, and redistribution decisions all within the same framework, self-driving platforms nearly double the earnings of the traditional alternative. This economic competitiveness of a self-driving ride-hailing fleet unlocks a treasure trove of potential including safer roadways, faster and cheaper transit, cleaner air, decreased emissions, and reclaimed urban space. Read my full thesis at the attached link.

As a radio host with WCWM 90.9, I curated weekly content, managed audio recording and broadcast from a mixing console, hosted guests, told stories, and discussed campus culture at William & Mary.

As a Secretariat member for WMHSMUN, I served on the organizing team for William & Mary's Model UN conference which hosts hundreds of high school students and schools from all over the country. As the USG for Specialized Agencies, I recruited and managed a team of Directors, set deadlines, reviewed background guides, implemented committee designs, and ensured an optimal delegate experience. As Director of Technology for last year's conference, I redesigned the conference website at wmhsmun.org, and automated hours of work by replacing manual delegate-position pairing with an adaptation of the Bellman-Ford shortest path algorithm.

As an Assistant Chair at Harvard WorldMUN, I used parliamentary procedure to facilitate debate in conferences in Panama City (2018) and Madrid (2019). In Madrid, I wrote a technical briefing for a non-technical audience on artificial intelligence and machine learning for the UN Special Summit on Technology which discussed lethal autonomous weapons systems. In Panama City, I wrote an update paper on indigenous peoples and ethnic conflict for our SPECPOL committee which discussed the impact of climate change on uncontacted peoples.

As an intern, I forecasted hourly electric load in regions all across the United States by evaluating the statistical significance and stability of hundreds of variables and minimizing test error. I personally designed neural networks and long short-term memory networks which successfully forecasted energy prices on the wholesale market.

I worked with staff and analyzed previous casework to compile an informative web series on information design and data analytics to promote the company's social media presence.