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Thanyapisit Buaprakhong

●AI Engineer & Applied AI Researcher

Bangkok / Thailand

AI Engineer and applied AI researcher.

Thanyapisit Buaprakhong Portfolio / 2026

I build applied AI systems across financial technology and climate risk, from model evaluation and retrieval to production deployment.

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Profile

01 / About

Portrait of Thanyapisit BuaprakhongBangkok / AI

Models / Systems / Product

I build models,systems, and products.

AI Engineer and applied AI researcher with a B.Sc. in Computer Science (First Class Honors, GPA 3.83) and experience building LLM agents, retrieval-augmented generation (RAG) systems, computer vision models, time-series forecasts, and recommender systems. Developed research and industry solutions across financial technology and climate-risk domains, spanning model evaluation, vector retrieval, multimodal AI, and end-to-end application deployment.

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01.1 / Methods

Programming & Data

  • Python
  • SQL
  • C/C++
  • JavaScript
  • Go
  • Pandas
  • NumPy

Machine Learning

  • PyTorch
  • scikit-learn
  • NLP
  • Computer vision
  • Time-series forecasting
  • Clustering
  • Recommender systems
  • Model evaluation

Generative AI

  • LLM agents
  • RAG
  • Tool calling
  • Vector search
  • Autonomous planning
  • Multimodal AI
  • Visual question answering (VQA)

Engineering

  • FastAPI
  • Next.js
  • React
  • Flutter
  • PostgreSQL
  • Supabase
  • Firebase
  • CI/CD
  • IoT
  • Edge deployment

01.2 / Technical focus

01

Agent systems Planning, tool calling, self-correction, and multi-step execution.

02

LLM and retrieval Grounded RAG, vector search, fine-tuning, and multilingual systems.

03

Computer vision Detection, VQA, CCTV analytics, and edge inference.

04

Production engineering Full-stack products, data pipelines, deployment, and monitoring.

01.3 / Education

King Mongkut's University of Technology Thonburi

B.Sc. Computer Science, First Class Honors

GPAX 3.83

Kangwon National University

ASEAN Cyber Shield Exchange Program

Cybersecurity and AI

01.4 / Awards & recognition

  • 01Gold Medal and Best Paper Award, UAMC 2026
  • 02Winner, SuperAI Startup Pitching 2025
  • 03Finalist, DIVE 2024
  • 04Finalist, Seoul Tech Impact Challenge Hackathon 2024
  • 051st Runner-up, SET Hackathon 2023 - Wealth and Sustainability
  • 06Winner, SEC Datathon 2023
  • 07Winner, SCB10X Bangkok AI Hackathon 2023, Track 1
  • 08Bronze Medal, Super AI Engineer Season 3, 2023

Experience

02 / Practice

Research, product development, and production systems.

01
Jun 2025 - Dec 2025Bangkok, Thailand

InnovestX

Data Scientist Intern

  • Built an autonomous trading agent that ingests market data and evaluates signal-based strategies.
  • Designed an LLM investment advisory agent with tool calling over market and portfolio data, plus a grounded RAG assistant for internal research.
  • Mapped funnel drop-off and feature adoption across user segments to inform product and retention decisions.
02
Dec 2024 - May 2025Bangkok, Thailand

V89 Technology

Part-time AI Engineer

  • Developed object-detection models for real-time applications and optimized inference pipelines for edge deployment.
  • Integrated computer-vision systems with web and IoT platforms.
03
Dec 2023 - Aug 2024Remote

MIT Urban Risk Lab

Researcher Intern

  • Built NLP models for incident summarization and severity classification, plus computer-vision models for urban flood monitoring.
  • Developed climate-risk forecasting systems and a location-aware flood response chatbot grounded in live situational data.
04
Oct 2022 - Feb 2024Bangkok, Thailand

Artificial Intelligence Association of Thailand

AI Apprentice and Frontend Developer

  • Completed the Super AI Engineer program across vision, signal processing, NLP, big-data analysis, and IoT.
  • Built search, course discovery, and recommendation experiences for the SuperAI MOOC platform.
05
Mar 2023 - Jul 2023Bangkok, Thailand

CMSK - Center of Money Skills Knowledge

Machine Learning Engineer

  • Built a RAG question-answering system over an internal knowledge base.
  • Developed a recommendation engine using behavioral signals and content-based filtering.

Research

Google Scholar

03 / Publications

Peer-reviewed work in applied AI and computer vision.

Selected work

04 / Projects

Products built for real use.

Product case studies across AI coding, agentic data systems, international-student services, performance analytics, travel commerce, and on-device retail AI.

Open a project to see the full case study →