Autonomous AI research team: write a plan.md, spawn agents, train, verify, and deliver a clean ML repo.
Real-time TUI for monitoring cloud GPU training instances
C++/Python microstructure research engine for event-driven limit order book prediction and reproducible quantitative experiments.
A gated memory layer for trustworthy AI-assisted research workflows.
Skill中间件架构：AI时代研究能力的工程化封装（以固定收益研究为例）
Research-engineering portfolio: LLM evaluation, RAG, RLVR/post-training, machine learning, Rust systems, data engineering, and reproducible computation.
Automates hermetic environments (macOS/HPC) to eliminate drift. Provisions offline RAG (Gemma 2), compiles LaTeX manuscripts, and indexes local knowledge. Unifies infrastructure, writing, and inference into a single, audit-ready artifact.
Research prototype for trace-based observability and failure analysis in retrieval-augmented generation.
Factor-aware, physics-guided road-surface intelligence | 因子感知与物理引导的路面状态识别、摩擦可供性估计与可复现实验
Selected LLM, NLP, retrieval and vision-language research-engineering projects.
Event-driven quantitative research evidence engine with real-data risk studies, leakage-safe execution, corrected inference, and reproducible reports.
Open ML systems platform for training, profiling, evaluating, and serving AI models.
AI-powered Research Assistant using Groq, Llama 3.1, LangChain, and Tool Calling to autonomously search the web, read webpages, and generate structured research reports.
AI systems, quantitative research, and governed agent infrastructure.
Regime-aware portfolio using machine learning, financial time-series features, risk research engine with dynamic allocation, stress testing, factor diagnostics, reproducible research packages, and a Streamlit dashboard.
Research-engineering lab for LLM post-training, behavior evaluation, regression detection, and reliability reporting.
PyTorch benchmark for CTM-style adaptive computation, sparse-retrieval failure analysis, adaptive halting, and attention-supervised recovery.
ChronosLOB: Research platform for limit order book representation learning, calibration and execution-aware validation.
Evidence-first research engineering lab for reliable AI agents, evaluations, and ML systems.
Quantitative research and research engineering profile
Add a description, image, and links to the research-engineering topic page so that developers can more easily learn about it.
To associate your repository with the research-engineering topic, visit your repo's landing page and select "manage topics."