Owned and led the link analysis automation project end-to-end, cutting a manual two-day data processing pipeline down to a few hours, with results surfaced across heatmaps, pinmaps, a RAG chatbot, and more, all built from scratch and deployed as an internal dashboard at link-analysis.cisco.com.
Built and deployed debug-genie.cisco.com, a Snowflake + Streamlit platform that became the single source of truth for AI repair accuracy across global manufacturing partners (Flex, Foxconn, Fabrinet), tracking defect location prediction, component match, and technician feedback across tens of thousands of production units. Replaced weeks of ad-hoc SQL exports and cross-partner reconciliation meetings. Drove measurable manufacturing outcomes: fewer scrapped boards, fewer repair iterations, and reduced dependency on high-skill debug technicians, saving millions annually.
Built optimal RAG systems with attribute filtering from scratch for device log diagnosis.
Developed a multivariate anomaly detection process analyzing thermal telemetry across tens of thousands of production network devices to diagnose future corrosion beforehand purely from data.
Designed and built cloud-native log analytics and monitoring platform using Python, AWS (Lambda, S3, DynamoDB), and distributed data pipelines for real-time anomaly detection across enterprise systems.
Architected end-to-end data ingestion pipelines processing structured and unstructured logs, integrating LLM-powered insights for root-cause analysis and automated triage workflows.
Led backend development for scalable API layer (FastAPI/GraphQL) supporting analytics dashboards and AI-driven alerting across multiple customer deployments.
Implemented infrastructure-as-code using Terraform and CI/CD pipelines to enable reproducible cloud deployments and reduce environment setup time by 70%.
Benchmarked six anomaly detection models (including CADE, Isolation Forest, and autoencoders) on fraud transaction data from major banks across the US, UK, Canada, India, and Brazil.
Engineered rolling temporal features that improved AUC and precision during distribution shift periods. Presented findings directly to the Chief Analytics Officer.
Built full-stack tooling with React and Node.js to automate GTM workflows in Ansible Tower
Contributed to an intern-led discounting system projected to save $24M per year by replacing third-party vendor fees for gift cards with an in-house solution & presented directly to the CIO.
Led development of a license plate recognition pipeline using YOLOv4, TensorFlow, and OCR. Built and published a pip package for the company's API alongside full-stack work in Vue, Nuxt, and Next.js.
Machine Learning and Data Science M.S.
Electrical Engineering B.S.
Manufacturing Leadership Council
Jun 2025
Our project at Cisco, Agentic Virtual FA, was a finalist for the Manufacturing Leadership Award
Cisco
Jun 2025
Awarded to my team for the Virtual FA project (Agentic Virtual Failure Analysis)
HARD Hack | IEEE UC San Diego
Feb 2025
Won first place in the Advanced Category for developing a smart trash sorter
LPL Financial
Jan 2025
Winner of "Most Viable Solution" category in competition with over 40 teams
ACE Mentor San Diego
May 2019, 2020, 2023, 2024
Merit-based scholarship
HARD Hack | IEEE UC San Diego
Apr 2023
2nd place in UCSD hardware hackathon (selected out of 23 teams)
LateNightHacks
May 2022
Won Domain.com prize for LateNightHacks 2022
Domain.com
May 2022
Won Domain.com prize for LateNightHacks 2022
SD Hacks
Apr 2022
Winner of UCSD hackathon's Civic Engagement category (selected out of 30 teams)
I had the pleasure of managing Yusuf at Cisco and can confidently say he is an exceptional software engineer with tremendous potential. Yusuf stands out for his strong technical capability and natural curiosity for new technologies, especially in AI/ML. Even early in his career, he demonstrated an impressive ability to quickly learn, adapt, and take on challenging problems. His work on ML pipelines and RAG-based solutions in the supply chain space showed both depth and practical impact. Beyond his technical skills, Yusuf is an absolute pleasure to work with. He brings a positive attitude every day and contributes to a highly collaborative team environment. He is proactive in helping others, often stepping in to support teammates, troubleshoot issues, and accelerate overall progress. What truly distinguishes him is his passion for technology. Outside of work, he actively participates in hackathons and competitions, frequently earning top awards, clear proof of both his dedication and talent. I highly recommend him for any software engineering or AI/ML-focused role.
I've had the pleasure of working with Yusuf at Southwest Airlines. Throughout our time together, he consistently showed tremendous ownership and drove the vision and development of a critical feature while staying aligned with team objectives and timelines. He showcased strong technical skills and excelled in all stages of the project: design, development, and testing. Yusuf is a natural leader who seeks to help his teammates whenever possible. His self-starter mindset makes him resourceful and quick to execute. Even on ambiguous, ill-defined problems, he performed thorough analysis and proposed practical, well-scoped solutions. Beyond his professional strengths, Yusuf brought kindness, thoughtfulness, humor, and a bright personality that made collaboration genuinely enjoyable. His technical depth and positive team presence are a rare combination.
I met Yusuf during a mentorship program at UCSD, where he was an outstanding mentor who gave practical advice on coursework, research, and internships. We later took courses together and teamed up in major course projects and hackathons, including a 2nd place finish at HARD Hack 2023 and 1st place at HARD Hack 2025. Throughout these projects, Yusuf was highly professional in how he wrote and organized software, especially under intense time constraints. His programming, AI/ML, and data science skills are top-tier. He is also an excellent presenter who makes complex projects understandable for any audience. I am confident these strengths will carry forward to any role he pursues.