• Maintained and developed automated software test frameworks for Optical Circuit Switch (OCS) platforms using Python and C#, enabling accurate validation of switching functionality, performance, and reliability.

• Developed Python automation tools to streamline and execute software test workflows, enabling faster, more reliable, and repeatable evaluation cycles.

• Implemented and deployed an AI model pipeline on GPU infrastructure to automatically generate test cases from product specifications and high-level design documents, improving test engineering efficiency.

• Engineered a specification-driven automation system that dynamically configures lab equipment and executes full test flows for the OCS R300, including designing core architecture and workflow logic.

• Performed regression and integration testing to identify defects early and ensure stability across OCS software releases.

• Developed and maintained test cases for new and existing software modules, expanding automated test coverage.

• Conducted manual and hardware-level validation of OCS devices to verify switching behavior and system reliability.

• Designed and benchmarked machine learning–driven methods for FIR tap tuning with live BER feedback, enabling faster

convergence and more robust high-speed optical communication

• Developed and launched service application layer, enabling seamless logging, communication, and data transfer between virtual machines (VMs), GPU servers, and the web application client.

• Designed and deployed backend infrastructure, building and integrating security systems and access controls to ensure safe and reliable model operation across environments.

• Develop and maintain backend API services to support secure data handling, candidate record management, and seamless integration with internal systems.

• Designed and benchmarked machine learning–driven methods for FIR tap tuning with live BER feedback, enabling faster convergence and more robust high-speed optical communication.

I teach a class of 10-15 students at Foothill Community College, covering the foundational aspects of computer science. As both a course instructor and TA, I lead weekly lectures, grade assignments, and provide ongoing feedback on student progression. The course introduces students to core programming concepts using an object-oriented language, focusing on topics such as the software life-cycle, procedural vs. object-oriented programming, IDE and debugging practices, documentation, and coding conventions in Python. Students also explore essential data types, basic data structures and algorithms, control structures, file I/O, functions, error handling, and testing.

In addition to teaching, I collaborate closely with other instructors, attending weekly meetings to reflect on lecture effectiveness, share insights, and discuss improvements to curriculum design and teaching methods. My leadership skills extend beyond the classroom, as I consistently guide students and contribute to enhancing the overall educational experience.

• Collaborated with PhD students and professors to conduct research on the environmental impact on strawberry phasing errors. Analyzed an extensive dataset comprising thousands of strawberry samples with over 30K gene biomarkers, 400+ environmental variables (including soil, water, sunlight, and humidity), and pedigree mapping.

• Quickly learned over 3,000 lines of R code, incorporating essential packages such as dplyr, tidyxl, tidyr, and gmodels, to efficiently extract, manipulate, and transform data into formats compatible with Beagle Software for gene phase prediction.

• Set up multiple versions of parameter files and initiated computing jobs on a Linux-based FARM data cluster to run different versions of Beagle Software. Ensured data quality and consistency throughout the research process. Communicated findings and insights effectively, presenting results to peers and experts in the field during regular progress meetings.

• Contributed to the development of a study on lipoproteins investigating the influence of diet and ethnicity on lipoprotein A levels within the human body working with a research team at UC Davis Genomics.

• Conducted wet lab experiments, including SDS-Page gels and Western Blots, as part of rigorous data collection processes, ensuring data accuracy and reliability. Employed advanced statistical techniques, such as confidence intervals, multiple correction, and linear regression analysis, to identify patterns, establish correlations, and determine causation within the data.

• Conducted analysis of results, interpreting data to form data driven conclusions.