chen xie

Designed and implemented coding agent evaluation benchmarks to expand task coverage and improve assessment reliability. Fine-tuned DeepSeek V4 Flash with LoRA SFT using ms-swift and integrated the model into the benchmark pipeline to measure performance gains.

Contributed to Terminus Bench, an open-source coding agent evaluation benchmark with sandboxed Docker environments for safely executing and testing AI-generated code. Designed new agent-eval benchmarks and integrated a LoRA fine-tuned DeepSeek V4 Flash model into the benchmark pipeline to improve assessment performance on coding agent tasks.

Built a multi-agent, multi-turn report generation system using RAG with short- and long-term memory. Implemented SFT plus DPO-style RL optimization to improve dialogue quality and increased key engagement metrics (transition rate and CTR), and developed an iterative Search-R1-inspired RL framework within a modular multi-LLM search pipeline.

Implemented fine-tuning pipelines on Azure ML Studio for multiple base models (including Llama3, GPT-4o, and Mistral) and managed training data via Azure Blob Storage. Built multilingual training pipelines, generated SBOM artifacts for data and model training/deployment steps, and evaluated fine-tuned models for Microsoft Teams meeting summaries.

Designed and implemented a cloud-native ML training platform deployed across two Kubernetes clusters, including user authentication and REST APIs for training-data management. Improved performance using Redis caching (reduced data retrieval time by 60%) and built task-queue architecture with Redis and gRPC, plus monitoring/alerting in Prometheus and Grafana that reduced false alerts from 46.6% to

Master of Science in Computer Engineering (Software Engineering track) at Carnegie Mellon University from 2021 to 2022.

Bachelor of Engineering in Chemical Engineering (Computation track) at Dalian University of Technology from 2015 to 2019.

Earned a Bachelor of Engineering in Chemical Engineering (Computation track) at Dalian University of Technology.