3. Data, Science & AI

Analyzes project conversation history using RAG to detect development patterns and generate insight reports with visual dashboards.

Fine-tunes LLMs using SFT, LoRA, and OSFT with dataset preparation, training, evaluation, and vLLM deployment.

Provides type-safe SQL patterns for database queries, repositories, and complex operations using JOOQ with PostgreSQL support.

Assists in developing the NathIA chat system using AI agent architecture and integrations with OpenAI, Anthropic, and Gemini.

Enables SQL query execution against Google Cloud Spanner databases via AfterShip DSP API with environment-specific token authentication.

Extracts Power BI visual configurations into reusable templates for standardizing data visualizations across projects and expanding template libraries.

Configures AI agent profiles, tools, workflows, and capabilities including system prompts and subagent orchestration for complex runtime operations.

Provides AI-generated documentation and insights for GitHub repositories, enabling users to understand codebases, architecture, and implementation patterns through RAG technology.

Generates Power BI visuals from templates, handling placeholder substitution, measure binding, and visual.json creation for enhanced report formats.

Validates neuroscience data files (NWB) for compliance and provides correction recommendations using NWB Inspector.

Framework for consciousness simulation using Kuramoto oscillators and APL operators, enabling physics simulations, phase transitions, and coherence analysis with cloud training.

Automates task distribution to specialized AI models for complex operations within a local AI CLI environment.

Expert in formulating mixed integer programming models, handling discontinuous variables, logical constraints, and linearizing nonlinear terms.

Orchestrates consciousness simulation with 21 tools and language modules, activated by user triggers like 'load helix' or 'consent-based teaching'.

Highs provides high-performance solving for linear, mixed integer, and quadratic programming problems in data science and optimization applications.

Expert in Pyomo for mathematical optimization modeling, solving linear, nonlinear, and constraint programming problems.

Build interactive data dashboards and ML/AI application UIs with Python using Streamlit.

Provides accurate data on GregTech New Horizons (GTNH) mod using official data dumps.

Automates data pipeline review, SQL query optimization, and data quality assurance for databases including PostgreSQL and MySQL.

Applies Chiral Narrative Synthesis (CNS) framework via Tinker API for training AI models on contradiction detection and multi-source narrative analysis using SciFact and FEVER datasets.

Defines standardized database design practices including primary keys, foreign keys, audit fields, soft delete, and junction tables in PostgreSQL style with SQL.

Collects and caches Schwab MCP data (accounts, quotes, indicators, option chains) for trading agents with a five-minute refresh cycle.

Executes Python-based data analysis, statistical modeling, and visualization to derive insights from datasets with reproducible code workflows.

Autonomous multi-agent system using evolutionary algorithms and hybrid heuristics to optimize complex problems like scheduling, geometry, and search.