Recent

First Place, Citadel Data Open Championship (December 2021)

• Improved best practices in modeling global plastic waste trade and pollution to create framework for analyzing policy events
• Won $100,000 grand prize out of ~7,000 undergraduate, masters, and PhD students in global statistics and research competition

First Place, International Statistical Institute (ISI) Florence Nightingale Prize (July 2021)

• Identified drug abuse likelihood across multiple demographic characteristics using Bayesian methods and utilized a network analysis to identify gateway drugs leading to high-risk illegal drug abuse
• Placed first against ~300 teams across universities from the U.S., Canada, and other international schools

First Place, UC Berkeley Quant Trading Competition (April 2021)

• Utilized concepts of expected value, variance, and probability in 8 rounds of market making against other participants; placed first out of ~100 competitors from top universities
• Accurately adjusted markets according to “news” events (e.g. if making a market around GPA, a news event could be “50% of participants have a GPA over 3.8”)
• Attended information sessions with Jane Street, Citadel/Citadel Securities, Optiver, Flow Traders, and SIG
• Additionally won the Flow Traders sub-competition based on individual performance against all ~100 other competitors in identifying positive EV trades under uncertainty

First Place, American Statistical Association (ASA) SMU DataFest (April 2021)

• Created report and video (NDA protected) to characterize illegal drug usage populations and behaviors
• Identified drug abuse likelihood across multiple demographic characteristics (age, race, education, income, etc.)
• Utilized a network analysis to identify gateway drugs leading to high risk illegal drug abuse
• Placed first out of ~90 competitors across several schools based on individual and team performance

First Place, Mathematical Association of America (MAA) Texas Chapter Annual Competition (April 2021)

• Created 12 minute video demonstrating and exploring the effects of particle movement
  • Calculated energy costs associated with moving an agent on the x/y axis according to the energy function E = 1/y
  • Discovered insights on behavior near y-axis for discretely and continuously moving agents
  • Generalized energy costs associated with moving along any continuous curve and numerically solved integrals using Python
  • Identified characteristics of most efficient agent paths according to polynomial movement curves
• Won first place as an individual against predominantly four-person teams; award presented at the 2021 Texas MAA Conference

Third Place, Citadel East Coast Data Open (March 2021)

• Produced 18 page report in one week on arbitrage availability in European soccer markets in team of 4
  • Inferred European soccer team skills using match score outcomes
  • Identified and characterized betting arbitrage using linear/logistic regressions
  • Clustered time series data into regimes of arbitrage availability in Python
• 1 of ~100 students accepted into predominantly graduate and doctoral student competition based on resume, entrance exam, and short answer responses

First Place, HackLBS (London Business School) (February 2021)

• Created fully functioning web application in 24 hours enabling small farmers access to financing options by representing their produce as a digital blockchain asset
• Utilized React, JavaScript, Node, and wasp to create full stack web application
• Invited to pitch to a panel of venture capitalists and the London Business School’s Women in Business Conference

First Place, Texas A&M Datathon (October 2020)

• Built web application in 24 hours where users can input preferential living conditions and be recommended ideal cities based on custom implementation of k-nearest neighbors
• Utilized Python, Pandas, and Dash to create an interactive and visually appealing user interface

First Place, American Statistical Assocation (ASA) SMU DataFest (May 2020)

• Created report and video (NDA protected) identifying causes and results of fatigue in Canadian women’s rugby teams
• Synthesized large data set (>10GB) of player movement sampled at 1s intervals into usable features
• Recommended player fatigue mitigation strategies and potential risk factors to minimize fatigue-related injuries

Other

N/A, Hack the Burgh VII (March 2021)

• Built market making bot in 24 hours making the most profit by a significant margin through taking advantage of illiquidity
• Traded against naive price-taking bots by immediately purchasing all order flow and thus placing the only bid/ask offers on virtual exchange
• Created two page report illustrating how illiquidity in markets can lead to inefficiencies and malicious action

N/A, Wharton People Analytics Competition (March 2021)

• Analyzed data of Teach for America Corp Member applications and post-program satisfaction surveys to recommend selection and placement strategies (results NDA protected)
• Identified factors promoting and prohibiting teacher matriculation throughout different milestone of TFA’s two-year teaching program
• Discovered teacher and placement characteristics that cause higher levels of happiness and satisfaction to recommend teacher placement strategy

N/A, HackMIT 2020 (September 2020)

• Created web app to interactively teach young students about finance and investing
• Built visualizations and reactive components in Meteor, Python, and plotly to illustrate risk, reward, correlation, and other investing metrics and concepts
• Translated concepts from standard undergraduate finance program to easily understood modules to give access to underprivileged students