Kimberly Wu

Designed and implemented a greenfield prototype to map supplier and material-level risks to components in Microsoft’s Bill of Materials (BOM), enhancing traceability and compliance visibility across hardware for Azure datacenters and devices.

Built an LLM-driven entity resolution ranker to optimize internal and third-party data joins; boosted NDCG score from 0.79 to 0.98 and increased evaluation case accuracy from 79.2% to 97.9%.

Designed and deployed an interactive UI using React Flow, enabling business users to visualize risk relationships.

Designed and implemented a scalable backend infrastructure to manage multimodal data using React and backend APIs by developing a custom dashboard to display complex data visualizations and insights; allowed for real-time data access.

Engineered a data processing pipeline to handle diverse data types efficiently, performing validation and transformation.

Engineered and designed a SIEM (Security Information and Event Management) platform to enhance threat detection capabilities and response efficiency; achieved a 75% accuracy improvement in anomaly detection rates.

Developed detection logic with embedded ML and deep learning algorithms using scikit-learn, Tensorflow, and PyTorch.

Analyzed large-scale open-source datasets using pandas, ensuring robust data cleaning and transformation.

improved efficiency of structured data into structured text; deployed using Kubernetes/Azure by developing a data ingestion and normalization platform using Node.js, Fastify, Redis, Mongo, and Kafka.

introduced and implemented a seed coordination and flake ID generation service; enhanced traceability and monitoring of requests within the distributed platform.

scaled server to process 1M+ concurrent requests to acheive an apdex of 0.85 over thousands of requests.

Developed a distance vector routing protocol; enabled efficient packet forwarding on simulated network environments.

Designed and implemented packet validation and buffer handling logic to filter redundant packets, enhancing efficiency.

Built mechanisms for handling multi-hop routing and dynamic route adjustments in response to network changes; utilized advanced network simulation environments to test routing behaviors under various network conditions.

Engineered a robust traceroute tool to efficiently map network paths; accurately identified intermediary routers between source and destination node across diverse network configurations—improving network diagnostics and monitoring.

Designed packet transmission/reception processes using Python sockets; ensured reliable & precise communication.

Integrated advanced parsing algorithms like IPv4, ICMP, and UDP headers to enhance the tool’s accuracy in interpreting packet data, determining route mappings, and reducing packet drop rates; tested on real-world networks.

Designed a file sharing and access control system using cryptographic techniques (RSA-OAEMP, HMACs, PRNGs, digital signatures) to ensure security of files and sharing actions; allows for bandwidth optimized sharing of file information.

Incorporated a secure communication channel for file invitations between users & access revocation system for owners.

Engineered and developed a fully functional CPU model by simulating digital circuits and logic components.

Integrated various CPU components including the ALU, registers, control unit, and memory interface, ensuring efficiency by implementing parallelism to enable simultaneous execution of multiple operations and optimize execution time.