• Helping ground up build lightweight CSS style rendering engine for Disney, ESPN and Hulu apps in C/C++, Rust and Typescript

• The engine must run on everything ranging from light compute devices like old broadcom reference spec cable tv boxes and fire stick tvs to heavy compute devices like a fully spec'd out Playstation 5

• Primarily worked on Meta Ray Ban Display and Oakley Meta Vanguard as well as other devices like Orion, Oakley Meta and Ray Ban Meta Smart Glasses under the Wearables Audio Systems Team

• Built highly optimized features like audio state crash recovery, and adaptive volume control to meet strict requirements due to limited hardware capabilities (i.e code that lives on device hardware and is **not** offloading compute to the phone or cloud)

• Audio State Crash Recovery restored audio state with only few frames of interruption (generally <= 1 second) and adaptive volume control would automatically adjust volume levels based on the user’s environment while they’re listening to any form of audio

• Built dashboard for displaying daily MCU and DSP memory usage analysis on Ray Ban Meta and other unreleased products using plotly

• Primarily worked with C++, C, Java, Python, Plotly and SQL

• Acquired by IMC Trading

• Collaborated with traders to build and design features for the prop shop’s systems to improve both fundamental and high frequency strategies.

Features/improvements would have to be capable of handling trades for strategies that can span days or fractions of a second

• Designed and Built an automated daily report with interactive dashboards for algo and FPGA analysis by replaying 100s of market updates before and after each of the algos’ +175,000 attempted CBOE and CME trades per day.

• The report would kick off at market close and used parallel processing to ensure it would finish running before the traders leave for the day (within an hour).

• Improved performance for accepting and persisting CBOE floor trades by using multithreading with immutable message passing

• Primarily worked with Java, Python, Pandas, Numpy, Plotly and C++

• Worked on the Kafka Dev team which owned the bank’s internal Apache Kafka infrastructure as a service platform which automatically handles tasks like managing Zookeeper clusters and allows teams to easily deploy applications handing both internal and external facing services

• Built and maintained new features for a highly reliable platform to help deploy applications capable of handling millions of dollars

• Aided in a Greenfield migration

• Worked with Apache Kafka, Java, Ansible, Junit, Bash Scripting as well as frameworks and technologies

• Taught the Rutgers Graduate/Masters School course: Python Methodologies for Data Science

• Aided in teaching students how to leverage Python for Data Science as well as the fundamentals of data science

• Graded all projects, assignments and exams