● Enhanced internal tool for experimentation on large query sets from various search engines, utilizing Microsoft Azure web services, Azure Blob Storage, Azure CosmosDB, and Microsoft SQL Server. This optimization improved the relevance of Bing search engine results and contributed to increased search engine optimization and brand recognition for Bing and its partners.

● Successfully adapted the organization's web-scraper to changes in major search engines' search result page formats, ensuring the reliable delivery of scalable and well-formed search result data to data scientists. This critical update ensured the availability of high-quality data for analysis and insights.

● Developed a user-friendly Knockout.js file explorer-like web UI, enabling collaborative git-based collaboration on Jupyter Notebooks hosted on Bing's internal search engine experimentation tooling. This innovation improved productivity, collaboration, and streamlined the development process for data scientists and engineers.

● Adapted C# business logic and microservice’s video conversion API to support FFmpeg overlay of brand logos on all camera-recorded video clips, boosting search engine optimization and brand recognition for the company and its partners.

● Launched an ASP.NET feature using Web Forms to handle new file image uploads on the existing partner portal architecture, seamlessly overlaying partner-specific logos as individualized watermarks on video clips generated under their respective customer accounts.

● Built Ember.js UI and C# business logic to receive and delegate IoT data submitted by end-users, leveraging Ember’s convention-over-configuration paradigm to rapidly prototype and utilizing ASP.NET’s C# AJAX web services and REST APIs to process up to 100,000 submissions per day. This initiative provided a surplus of training data for a proprietary video object classifier, significantly enhancing its accuracy and performance.

● Updated and maintained internal C# tooling to incorporate new customer feedback parameters in video clip text metadata during the download of customers’ video clips. This improvement bolstered Alarm.com's proprietary machine learning software and drastically reduced the manual on-site ground truthing bottleneck, enhancing operational efficiency.

● Facilitated engaging discussions on paradigm differences between functional (OCaml), imperative (Ruby), and logical (Prolog) programming languages. Helped students gain a comprehensive understanding of these languages and their suitable approaches for solving real-world problems across various domains.

● Provided instruction on multithreading fundamentals and offered assistance to students in troubleshooting their simulations of an asynchronous spaceship-and-spaceport Ruby multithreading project. Guided students in effectively managing locking, signaling, and race conditions to ensure the project's successful completion.

● Delivered comprehensive lessons on OCaml recursion and closures, equipping students with the necessary skills to tackle assorted OCaml algorithm problems. Demonstrated the fundamental concepts and real-world applications of a functional approach to programming through hands-on projects and exercises.

● Educated students on the unique paradigm differences between Prolog and other programming languages. Showcased how to define relationships between objects, leveraging Prolog's logic-based approach to efficiently produce results for common queries in the absence of traditional functions.