MARK QUIBOT
Computer Science researcher and developer specializing in Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP) tooling, and Multimodal Transformer Reasoning. Experienced in architecting offline/local RAG pipelines for privacy-preserving data extraction, implementing JSON-RPC tool schemas for agentic workflows, and deploying real-time telemetry streaming architectures for edge computer vision inference.
| OPERATOR: | Mark Lawrence M. Quibot |
| SPECIALIZATION: | AI Systems & Data Workflows (RAG, MCP, Transformers) |
| INSTITUTION: | Ateneo de Naga University (BS CS 2022–2026) |
| CURRENT ROLE: | Web Master & Infrastructure Administrator @ BAIA Cafe |
| CORE HONORS: | 1st Place AI.Deas R5 • Bloomberg Champion • 4th Runner-Up PSC |
| COORDINATES: | Naga City / San Pascual, Philippines |
AI.Deas Region 5
Awarded top honors for building an end-to-end hydrological streaming system fusing real-time computer vision inference with localized IoT telemetry.
Bloomberg Challenge
Recognized for engineering scalable data aggregation architectures for municipal disaster management and early warning alert systems.
Philippines Startup Challenge
Formulated enterprise data architecture blueprints and commercialization strategies for edge-to-cloud telemetry sensor nodes.
Web Master & Infrastructure Administrator
- Architected an enterprise-grade, cloud-managed network topology utilizing multi-tier VLAN segregation to isolate operational transactions, CCTV telemetry, and high-throughput guest traffic.
- Engineered and maintained the high-availability client web platform and social commerce integration pipeline for automated operations.
Management Information Systems Intern
- Contributed to diagnostic testing, database schema audits, and optimization modules for the university-wide PAMOS management system.
- Built custom automation scripts for administrative data migration and normalization pipelines, eliminating manual verification bottlenecks.
Bachelor of Science in Computer Science
- Curriculum emphasis: Distributed Systems, Artificial Intelligence, Database Architectures, and Software Engineering.
- Research specialization: Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP) tooling, and Multimodal Transformer Reasoning.
Data-RAG-using-Gemma-4-E4B
SYS: ON-DEVICEArchitected an on-device, zero-leakage Retrieval-Augmented Generation (RAG) framework using Google’s open-weight Gemma architecture for strict offline privacy. Features recursive semantic chunking, high-density vector embeddings, and local cosine-similarity retrieval without third-party API dependencies.
Mastering_GoG_TiM
SYS: TRANSFORMERMultimodal Transformer Reasoning Engine formulating state-representation tokenizers mapping heterogeneous game rules, board topologies, and visual matrices into unified latent embeddings. Integrates chain-of-thought (CoT) and multi-step inference patterns to mathematically evaluate multi-turn deterministic and stochastic decision paths.
Model Context Protocol (MCP) Tooling
SYS: PROTOCOLEngineered modular Model Context Protocol (MCP) servers running over stdio and SSE to safely expose execution tools and dynamic data pipelines to LLM agents. Defined strict JSON Schema definitions via Pydantic, implementing context boundary protections, token-budget caching, and structured execution pipelines.
Stormawatch: Edge Vision & Telemetry
SYS: STREAMINGBuilt a real-time streaming telemetry pipeline aggregating edge computer vision inference data (YOLOv8) with hydrological sensor arrays for localized flood tracking. Engineered an asynchronous time-series data cleaning and normalization pipeline feeding live public-facing monitoring dashboards.
Automation-for-my-Store & Baia Cafe
SYS: PRODUCTIONDesigned and implemented an automated Facebook Messenger conversational pipeline handling customer inquiries, catalog search, and automated transaction updates. Developed the client-facing digital showcase platform for BAIA Cafe, integrating menu schemas and commercial brand assets.
01 // AI & ML
- Retrieval-Augmented Gen (RAG) SPECIALIZED
- Model Context Protocol (MCP) SPECIALIZED
- Multimodal Transformers ADVANCED
- Local LLMs (Gemma) DEPLOYED
- Chain-of-Thought Reasoning ADVANCED
- Computer Vision (YOLOv8) CHAMPION
02 // DATA & KNOWLEDGE
- Vector Embeddings ACTIVE
- Semantic Search & Chunking ACTIVE
- PostgreSQL (pgvector) DEPLOYED
- MongoDB & MySQL PROFICIENT
- JSON-RPC Schemas OPERATIONAL
- Schema Validation (Pydantic) VERIFIED
03 // LANGUAGES & LIBS
- Python PROFICIENT
- JavaScript / TypeScript ADVANCED
- SQL (Postgres / MySQL) ADVANCED
- C / C++ PROFICIENT
- FastAPI & PyTorch ACTIVE
- Hugging Face & React ACTIVE
04 // TOOLS & INFRA
- FastMCP & SSE Protocols OPERATIONAL
- Claude Code & Cursor POWER USER
- Docker & Linux CLI DEPLOYED
- Git & Jupyter Notebooks OPERATIONAL
- Cloud Network Controllers 100% SLA
- Edge Telemetry Sensor Nodes INTEGRATED