• Applying Natural Language Processing and Latent Semantic Analysis to announcements from the Fed• Created a corpus of Federal Reserve speeches and minutes for natural language processing • Examining how the tone of transcripts and minutes of FOMC meetings changes over time and how those changes are related to economic indicators, using sentiment analysis • Generated the topic proportion for FOMC meetings and transcripts using machine learning techniques such as Latent Dirichlet allocation (LDA)• Comparing Fed transcripts to corresponding minutes to discover whether the minutes are an accurate summary of the transcripts, or if they are crafted to send specific messages to investors

• Assisted with blockchain and cryptocurrency presentations and research• Collaborated with team members and management to create a trading bot that used multiple indicators to recognize trends and automatically execute trades• Collected data on cryptocurrency indicators and helped identify the most useful indicators• Created Presentations on PowerShell, Splunk, Game Theory, to facilitate learning for clients and partners

• Completed a project for National Bureau of Economic Research “Evolution of U.S Bank Supervision”• Examined National banks balance sheet and conditions from 1887 to 1901• Compared performance of different banks during the time period and observed how it is related to banks structure of loans, management, core business, exposure to risk, reserves• Constructed a time series database in Excel with over 250 variables for each bank and performed both quantitative qualitative statistical analysis• Investigated how different banks dealt with the Panic of 1893• Compose banks bibliography and summarized the conditions of banks during the period