Chris Cao

Computer Science @ University of Toronto

Experiences

Amazon - Software Development Engineer Intern (June 2026 - August 2026)
  • Designed a declarative rule engine for Amazon's financial reconciliation pipeline, representing source-specific reconciliation logic as typed abstract syntax trees to classify transactions and generate traceability metadata across 1B+ daily financial transactions.
  • Built typed abstract syntax tree infrastructure for declarative reconciliation rules, normalizing predicates and enforcing deterministic precedence, conflict detection, and ambiguity checks in Java.
  • Implemented versioned rule deployment with stage and region gates, release blocking, CloudWatch alarm integration, and rollback paths using AWS CDK, S3/AppConfig, Lambda, and CloudWatch.
Far Data Lab - Research Assistant (May 2026 - August 2026)
  • Building C++ and Python data-processing infrastructure for LLM-powered query execution in DuckDB, integrating semantic filters, joins, aggregations, and top-k operators into analytical database workflows.
  • Optimizing model-call latency and inference cost through batching, adaptive execution, and cost-aware query planning.
SITH Lab - Research Assistant (March 2025 - August 2025)
  • First-authored an IEEE Computer Architecture Letters paper on GPU cache security, identifying a reproducibility flaw in a reported side-channel attack.
  • Debugged low-level accelerator security simulations in gem5 by rerunning attack traces, analyzing simulation logs, and tracing false positives to a trace-counting bug and fixed RNG seed using C++, Python, and Bash.
  • Containerized architecture-simulation dependencies with Docker to improve reproducibility across hardware and software security experiments.

Education

University of Toronto - BSc Computer Science
  • Co-op Program, expected May 2027.
  • GPA: 3.94
  • Awards and Honors: University of Toronto Excellence Award, Dean's List, Undergraduate Student Research Award.
  • Courses: Data Structures and Algorithms, Operating Systems, Databases, Parallel Programming, Machine Learning.