3. Data, Science & AI

Enterprise LLM fine-tuning solution using LoRA, QLoRA, and PEFT techniques for efficient model adaptation.

Builds enterprise-grade RAG systems using vector databases and embedding strategies for knowledge-aware AI applications.

Provides a structured CRISP-DM data science workflow for FYP projects with MLflow tracking, phase-based guidance, and model validation.

AI-powered serverless PostgreSQL platform with intelligent branching orchestration for scalable data management and application development.

Automates statistical validation for ML models including hypothesis testing, confidence intervals, and APA-formatted reporting to meet academic standards for theses and conferences.

Generates and executes Python code to analyze large log datasets, detect patterns, and extract actionable insights.

Provides context for a Data Science FYP implementing CrossViT for COVID-19 chest X-ray classification, including dataset specs, model architecture, and evaluation metrics.

AI-powered enterprise document processing system for intelligent analysis, content extraction, and workflow automation across multiple formats.

AI-powered MCP server orchestrator with ML-based performance analysis, intelligent plugin management, and Context7 integration for enterprise AI infrastructure.

Optimizes AI system performance by analyzing session patterns and implementing adaptive learning for continuous knowledge refinement.

Provides SQL best practices, pgTAP testing, sqlfluff linting, and query optimization for efficient database development.

Parses Chinese Union Version biblical text with Strong's Numbers into structured semantic groups, supporting compound detection for scholarly analysis.

Assists in bioinformatics research, experiment planning, analysis execution, and scientific project management workflows.

Provides a production chain calculator for Oxygen Not Included using a SQLite database extracted from the game's decompiled source code.

Creates interactive data visualizations with pyecharts, generates HTML reports, and applies best practices for effective data presentation.

Provides reference for optimizing PostgreSQL queries, interpreting EXPLAIN output, and tuning database performance to resolve slow query issues.

Comprehensive reference for designing PostgreSQL database schemas, including data types, indexing, constraints, and performance optimization patterns.

Provides expertise on AWS Cost and Usage Report (CUR) data structure, column formats, and analytical patterns for cost optimization.

Enables creation, editing, and analysis of Excel spreadsheets (.xlsx, .csv, .tsv) for data-driven tasks like financial modeling.

Validates screenplays for AI video generation with Veo 3, chunking scenes into 8-second segments, scoring feasibility risks, and generating continuity prompts.

Guides AI agent system design and optimization using Anthropic best practices and current research through interactive analysis and documentation.

Adds AI-driven Q&A to ChatKit UI, enabling users to ask questions about highlighted text with seamless integration.

Framework for structuring effective prompts for Veo 3 video generation, ensuring all 8 mandatory components are included for professional results.

Generates and manages AI-driven ideas through a structured pipeline including prompt engineering, duplicate detection, and real-time logging.