Supervised by: Professor Brokoslaw Laschowski Working on inverse reinforcement learning for neuroscience

Tools and algorithms for securities and equities market making on the Quantitative Trading Solutions team. Developed a low latency market data feed for OTC market data using Java. Aggregated quotes to create a multi level quote book and published data to internal apps using Kafka and Streambase. Engineered a fault-tolerant, low-latency FIX gateway (Java, Aeron, Chronicle). Leader election and automatic failover across bare metal machines using Zookeeper. Developed a Python reconciliation service for FIX orders/executions reports. Detected breaks, emailed alerts and archived artifacts to Azure Blob Storage and SQL Server.. Shipped middle office APIs in C#/ASP.NET. Authored high-volume SQL procs/queries and optimized with indexes/parallelism for multi-million-row workloads. Delivered a live fills/executions pipeline. Produced data to Kafka, bridged to Lightstreamer, developed Angular/TypeScript UI with real-time filters (symbol, client). Handled CI/CD using Azure Pipelines to Kubernetes environments configured using Kustomize and managed containers and images using Docker. Languages and Technologies: Python, Java, C#, C++, HTML/CSS, TypeScript, Angular, ASP.NET, SQL, Microsoft SQL Server Management Studio, Kafka, Docker, Kubernetes, Git, Azure DevOps, Wrangler, Splunk Cloud

Worked on the development of NetLiNQ EMS management platform for wireless and broadband networking equipment. Created end-to-end components such as map features to display eNBs and CPEs as well as location search and radius filtering components using Angular, Diesel, ElasticSearch, and Google GeoCoding API. Created a Python script that algorithmically updates ElasticSearch fields through HTTP endpoints. Created a Docker image for the script which is used for a Kubernetes periodic job through GitHub Actions. Created a Go script that takes in a JSON file for bulk uploading devices and validates the user through Keycloak Oauth. The script then validates the file based on a predefined schema. If valid, devices are bulk uploaded to MongoDB. Implemented Agile methodologies and Scrum framework throughout development as well as Jira and Confluence.

Full Stack Developer for the Kidney Health Education and Research Group (KHERG) in the Multi-Organ Transplant Program and Centre for Mental Health at the University Health Network (UHN) and University of Toronto. Worked on the development of several websites including Kidney Health Education and Research Group, Explore Transplant Ontario, and Symptom Care using React, JavaScript, HTML/CSS, PHP, and WordPress.

Undergraduate research assistant under Professor Tovi Grossman with a focus on Human Computer Interaction. Worked on the development of Blocks-To-Code, an educational IDE which serves as an intermediary transition from block-based to text-based programming using TypeScript, Monaco Editor, and React. Developed multiple features including a spotlight search where users can input various blocks of code by using an autocomplete feature. Developed a settings menu to toggle features such as colored blocks and typing in the editor. Also worked on the research study of Coding Steps. A study showcasing the effects of AI generators on novice programmers. Second author of the corresponding paper which was accepted into the prestigious CHI 2023 conference.