ShawnL
ShawnL1
AI & ML interests
- Multi-Agent Systems & Workflow Orchestration – self-evolving agent ecosystems, dynamic workflow generation (WorkFlowGenerator, AgentManager), and reinforcement-driven coordination strategies.
- Optimization Algorithms for Agents – experimentation with MIPRO, MASS, TextGrad, and AFlow to optimize prompt distributions, emergent reasoning strategies, and agent communication topologies.
- LLM-Centric Reasoning & Benchmarking – fine-tuning and evaluating LLM-driven agents on GAIA, HotPotQA, and MBPP, targeting measurable gains in reasoning depth and execution reliability.
- Data-Driven Financial AI – automated data ingestion (akshare), multi-scale feature engineering, and integration of technical indicators (MA, RSI, MACD, Bollinger Bands) for algorithmic trading pipelines.
- Hybrid Human-in-the-Loop Systems – approval-gated interceptors, adaptive feedback loops, and semi-automated validation layers for safe decision augmentation.
- Adaptive & Generative AI – workflow morphogenesis, representation learning, and algorithmic prompt evolution for scalable open-source research.
Organizations
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