Actively Searching for Full-Time Opportunities | Masters @ UC Davis
Software Engineer for Omada.AI. Some areas that I am specialized in are large scale distributed systems in data storage and processing, transactional systems, data science/analytics, and AI agentic modelling. I am looking forward to participating in various fields to solve industry problems in a collaborative manner.
Developed AI tools for converting user social media preferences into regular social media post generation, alongside image and video generation
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Created multiple AWS workflows for asset generation, storage, and retrieval
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Worked on multi agent architecture to assign agents specialized tasks which transfer context between one another to allow for deeper reasoning and more detailed responses
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Wrote multiple OpenAI tools to allow for communication between OpenAI agents and backend workflows
Developed a microservice to automate production pipelines in Intel Foundry, reducing task time by 60%, eliminating 90% of human errors, and saving 20,000+ engineering hours annually
Architected a centralized data platform to integrate disparate data streams, enabling unified analytics via agentic tools, BI platforms, and dashboards. Built a custom dashboard and UI used by 20+ Intel teams & external vendors
Leading interns, I translate user stories into detailed system and technical designs, assist in implementation and debugging, and am accountable for timely delivery
Wrote APIs for data pull and access, alongside scripts which run at set intervals to create custom views for production data for daily engineer overview and analysis
Working in a instruction role for an Undergraduate Databases course. I conduct discussions covering course content, project implementation guidelines and strategies, as well as general coding help. I also host sessions to help students design system architecture and offer critiques of the pros and cons of their systems from an efficiency and correctness standpoint
I am working as a research assistant in ResilientDB at UC Davis under the guidance of Prof. Sadoghi on the Apache Incubator project ResilientDB. One of my main roles is implementing a new concurrency control protocol for the ResilientDB blockchain system. The original model utilized a serial execution method, while the solution I developed enables concurrent execution of transactions, allowing for parallel transaction processing with no loss in data integrity. A larger throughput allows for a greater number of batch requests to be processed, increasing the overall operating efficiency of the platform/system. My implementation currently increases throughput by over 7x, with my efforts now focusing on adding abort functionality to the system in an efficient manner.
In addition to my concurrency control role, I am also developing a visualization software known as ResView on top of the ResilientDB architecture in order for users to interface with the service in a streamlined and manageable manner. ResView allows users to send transactions to ResilientDB and displays the process of blockchain consensus in real time. This data is collected directly from the consensus protocol and tracks the transaction progression across the different phases and nodes. In addition to displaying consensus, ResView enables users to see how the different nodes collect messages from one another and the differences in the rate of message accumulation, which is a way to check on the healthiness of a node. Finally, ResView allows users to test faulty nodes to test edge cases where multiple nodes in the system are down or view changes are required to progress, which previously required hard coding faulty functionality.
For more info on ResilientDB, visit https://resilientdb.com/
My code can be found in the following repositories:
Working on automation scripts and visualization tools to create more efficient and accurate processes for chip development, allow for more detailed chip evaluation, and track efficacy of in-house and vendor recipes over time
