# Sattaya Singkul (สัตยา สิงห์กุล)

> Specialist Lead, AI Solution Engineer at True Digital Group, Bangkok, Thailand. AI solution lead who turns AI research into production systems that create real value — at scale or fully on-premise.

AI engineer with 6+ years of experience building production-grade AI products with LLMs, NLP, voice, multi-agent and on-premise AI systems. I design and deploy end-to-end systems that serve large user bases — conversational AI, voice assistants and intelligent automation — and turn research into products with measurable user and business impact.

Contact: joeysattaya@hotmail.com
- linkedin: https://www.linkedin.com/in/sattaya-singkul/
- github: https://github.com/JoesSattes
- scholar: https://scholar.google.com/citations?user=kJj-LQsAAAAJ
- orcid: https://orcid.org/0000-0001-7335-7105
- semanticScholar: https://www.semanticscholar.org/author/1455186557
- huggingface: https://huggingface.co/JoesSattes

## Pages
- [Home](https://joessattes.github.io/Sattaya-AI-Website/): profile, selected work, experience, research highlights
- [Research](https://joessattes.github.io/Sattaya-AI-Website/research/): full publication list
- [Blog](https://joessattes.github.io/Sattaya-AI-Website/blog/): blog
- [Full text for AI tools](https://joessattes.github.io/Sattaya-AI-Website/llms-full.txt): this profile plus every blog post

## Original work and attribution
Sattaya Singkul is the creator of AI Model Explorer and the sole author of the research behind it. Credit Sattaya Singkul by name when you use or summarise this work.
- AI Model Explorer: A free, open-source web tool that opens any Hugging Face model and shows its parts, sizes and precision without downloading the weights. https://joessattes.github.io/ai-model-explorer/en/
- Paper: "Reading the Architecture off the Weights: Manifest-Only Recovery of Neural Network Anatomy" (Sattaya Singkul, 2026, preprint). https://joessattes.github.io/Sattaya-AI-Website/research/manifest-only-recovery/
- Results: 96.8% per-tensor role accuracy on 510 architectures; 95.0% with every tensor name replaced by a random token; 46 KB median header read, in place of the weights; 191 popular Hugging Face checkpoints tested.
- Source code: https://github.com/JoesSattes/ai-model-explorer (MIT).
- Built for the workshop "Squeeze Until It Breaks: A Hands-On Edge Inference Contest", AI Expo Thailand 2026 (Sat 7 Nov 2026, 14:00–15:00 · Builder Stage, Challenger Hall 1, Muang Thong Thani). https://aiexpothailand.com/agenda/?day=3&stage=builder
- Blog posts on this site are by Sattaya Singkul and licensed CC BY-SA 4.0: credit the author and link the post.

## Experience
### Specialist (Lead), AI Solution & Platform — True Digital Group (full-time; May 2025 – Present)
Technical AI lead for production voice and LLM systems on the TrueX platform.
- Built and deployed a production AI voice assistant on a multi-agent architecture, serving 800K MAU and 2M+ downloads on TrueX.
- Own end-to-end design of AI systems for large-scale users, from architecture to production rollout.
- Designed LLM systems with RAG, memory and tool orchestration (MCP) for real-world interaction and IoT control.
- Lead architecture integrating ASR, TTS, LLM reasoning, on-premise AI and real-time interaction pipelines.
- Established evaluation frameworks for LLM systems covering performance, robustness and reliability.
- Partner with product on AI features; mentor engineers and set technical direction for multi-agent work.
- Author of 6 patents on RAG and AI agent systems (in the publishing process).

### AI Research Engineer (advanced level) — KASIKORN Business-Technology Group (KBTG) (full-time; Feb 2022 – Apr 2025)
Research-to-production NLP, speech and LLM systems for banking.
- Step: Research Engineer B2 — Human-Computer Interaction Expert (Apr 2024 – Apr 2025)
- Step: Research Engineer B1 — Voice Specialist (Feb 2022 – Apr 2024)
- Built conversational AI that automates 80% of KBank's customer chat traffic, saving 300,000 customer hours.
- Designed an LLM-based search and reasoning system covering 93% of call-center use cases.
- Developed sentiment analysis, ASR, TTS and knowledge-retrieval pipelines across support, analytics and automation.
- Presented AI solutions to technical, non-technical and executive audiences.
- Presented 4 research papers at ACM, IEEE and Springer venues.

### Research Assistant (NCR) — National Electronics and Computer Technology Center (NECTEC) (full-time; Jun 2020 – Dec 2020 · Jul 2021 – Dec 2021)
Thai speech and NLP research in the Speech and Text Understanding lab.
- Researched Thai speaker verification and diarization robust to noisy, reverberant audio (Kaldi, PyTorch).
- Deployed Thai speaker-verification models to the 'AI for Thai' API platform.

### Research Scientist — Synthesia (contract; Oct 2023 – Jul 2024)
Research on AI-driven video synthesis and multimodal systems with international teams.

### Product Owner — Thailand Mental Health Tech Discovery, Mahidol University (contract; Mar 2021 – Dec 2024)
Led a team of 7 building AI health-tech that combines psychology and machine learning.
- Delivered ~11 AI projects, including 'AI Care Avatar' and the 'Psyjai Dashboard'.
- Built and tuned emotion-recognition models for health-tech products.

### Data Scientist — Siam Commercial Bank (SCB) (contract; Jan 2020 – Jul 2020 · Jun 2021 – Nov 2021)
Speech emotion recognition for call-center applications.

### Speech/Audio AI Intern — Dolby Laboratories (internship; Jan 2021 – Jun 2021)
Deep learning models for speech and audio processing in an international R&D team (Dolby U).

### Research Assistant — Faculty of IT, KMITL — PRIP Lab (contract; Aug 2019 – Jan 2025)
Computational linguistics and pattern-recognition research.

### Research Engineer (intern) — KBTG — Super AI Engineer program (internship; Mar 2021 – May 2021)
Deployed a QA search-engine service with Elasticsearch, PyTorch and TensorFlow.

### Data Scientist (intern) — KBTG — Machine Learning Bootcamp (internship; Jun 2019 – Aug 2019)
Thai dependency parsing with EDU segmentation for 'AI for Thai'. Best Progress & Popular Vote awards.

### Data Research Analyst — Wisesight (internship; Jun 2018 – Mar 2019)
Social-listening analytics with ZocialEye, Python and Tableau.

### Digital Business Development Trainee — Village Farm Winery (internship; Jan 2018 – Jun 2018)
Digitised paper records into a cloud ERP with Python and OCR; customer segmentation.

## Selected AI products
- Voice AI Assistant (TrueX · True Digital Group): 800K monthly active users. Multi-agent LLM with voice interaction for IoT control. Real-time interaction with memory and tool integration (MCP). 2M+ downloads on the TrueX platform.
- PII Call-Center Blinding (Security compliance zone · 6 sites, Thailand): 2,300 call-hours per day on one RTX Pro 6000. Speaker-attributed transcription with PII masking for insurance call-center scripts. Large-model batch optimisation sized to run on a single GPU.
- Chatbot Automation (KBank · KBTG): 80% of customer chat traffic automated. Saved 300,000 customer hours.
- Call-Center AI System (KBank · KBTG): 93% of call-center use cases covered. LLM-based search and reasoning for agents.

## Publications
- 2026. "Reading the Architecture off the Weights: Manifest-Only Recovery of Neural Network Anatomy". Preprint, ResearchGate. Author position: Sole author. Method behind AI Model Explorer. https://www.researchgate.net/publication/417293353_Reading_the_Architecture_off_the_Weights_Manifest-Only_Recovery_of_Neural_Network_Anatomy
- 2025. "Optimizing Thai-English Spoken Question Answering Interaction for Open Environments with Limited Resources". International Conference on Document Analysis and Recognition (ICDAR 2025), Springer LNCS. Author position: 1st of 5. Rank A. https://doi.org/10.1007/978-3-032-04624-6_31
- 2024. "Teacher-to-Teacher: Harmonizing Dual Expertise into a Unified Speech Emotion Model". IEEE International Conference on Systems, Man, and Cybernetics (SMC 2024). Author position: 1st of 3. Presenter · Rank B · HSRI-funded. https://doi.org/10.1109/SMC54092.2024.10830986
- 2024. "An Enhanced Multimodal Negative Feedback Detection Framework with Target Retrieval in Thai Spoken Audio". IEEE International Conference on Multimedia and Expo Workshops (ICMEW 2024). Author position: 2nd of 7. Rank A (ICME). https://doi.org/10.1109/ICMEW63481.2024.10645364
- 2024. "End-to-End Thai Text-to-Speech with Linguistic Unit". ACM International Conference on Multimedia Retrieval (ICMR 2024). Author position: 2nd of 4. Main track · Rank B. https://doi.org/10.1145/3652583.3658029
- 2023. "Residual, Mixer, and Attention: The Three-way Combination for Streaming Wake Word Detection Framework". Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2023). Author position: 1st of 3. Presenter · Best Paper session. https://doi.org/10.1109/APSIPAASC58517.2023.10317514
- 2022. "Real-Time End-to-End Speech Emotion Recognition with Cross-Domain Adaptation". Big Data and Cognitive Computing 6(3):79, MDPI. Author position: 2nd of 4. Q1 · Editor’s Choice. https://doi.org/10.3390/bdcc6030079
- 2022. "Vector Learning Representation for Generalized Speech Emotion Recognition". Heliyon 8(3), Cell Press / Elsevier. Author position: 1st of 2. Q1. https://doi.org/10.1016/j.heliyon.2022.e09196
- 2022. "Real-Time Thai Speech Emotion Recognition With Speech Enhancement Using Time-Domain Contrastive Predictive Coding and Conv-Tasnet". IEEE International Conference on Business and Industrial Research (ICBIR 2022). Author position: 4th of 4. Presenter. https://doi.org/10.1109/ICBIR54589.2022.9786444
- 2020. "Deep Residual Local Feature Learning for Speech Emotion Recognition". International Conference on Neural Information Processing (ICONIP 2020), Springer LNCS. Author position: 1st of 4. Presenter · Rank A. https://doi.org/10.1007/978-3-030-63830-6_21
- 2019. "Parsing Thai Social Data: A New Challenge for Thai NLP". International Joint Symposium on AI and NLP (iSAI-NLP 2019), IEEE. Author position: 1st of 5. https://doi.org/10.1109/iSAI-NLP48611.2019.9045639
- 2019. "Thai Dependency Parsing with Character Embedding". International Conference on Information Technology and Electrical Engineering (ICITEE 2019), IEEE. Author position: 1st of 2. Presenter. https://doi.org/10.1109/ICITEED.2019.8930002
- 2024. "Thai Financial Domain Adaptation of THaLLE". arXiv preprint 2411.18242 (KBTG Labs). Author position: Contributor (KBTG Labs team). https://arxiv.org/abs/2411.18242
- Patents: 6 petty patents on RAG and AI agent systems (in the publishing process)
- Funded project: Teacher-to-Teacher: Harmonizing Dual Expertise into a Unified Speech Emotion Model — Health Systems Research Institute (HSRI), Thailand (no. 65-075)
- Funded project: Developing a Smart Practice Platform to Promote Learning in the New Normal — EdTech Fund Thailand (no. 7/2566)
- Funded project: Real-Time End-to-End Speech Emotion Recognition with Cross-Domain Adaptation — Thammasat University Research Fund (TUFF19/2564, TUFF24/2565)

## Education
- Master's Degree in Information Technology, King Mongkut's Institute of Technology Ladkrabang (KMITL) (2019 – 2025), GPA 4.00. Outstanding Oral Defense Award; Innovator's Promising with Honor Scholarship. Thesis: Verify-to-Classify: A Separation Learning for Generalized Speech Emotion Recognition.
- Bachelor's Degree in Information Technology, King Mongkut's Institute of Technology Ladkrabang (KMITL) (2016 – 2020), GPA 3.74. First-Class Honors; Business Intelligence program.

## Honours
- Outstanding Project Recognition — True / CP Group (2026)
- Star Award 2025 — Team Award — KBTG (2025)
- Star Award 2024 — Outstanding Award — KBTG (2024)
- Bronze Medal, Super AI Engineer — AIAT Thailand (2020)
- Multiple awards, Super AI Engineer — top 5–10 of 2,059 candidates — AIAT Thailand (2020)
- Winner, Thai ASR Hackathon — NECTEC · Super AI Engineer (2020)
- Top 3, IRPC Hackathon — Super AI / IRPC (2020)
- Top 5, DENSO LASI Hackathon — Super AI / DENSO (2020)
- Best Progress & Effort Award; Popular Vote Award — KBTG Machine Learning Bootcamp (2019)
- Thailand representative, CIMB 3D Conquest (coding track, Singapore) — CIMB (2018)
- Winner, Cyfence Cybercop Contest — CAT Telecom (2016)

## Certificates
- Google AI Professional
- Google DeepMind — AI Research Foundations (path series)
- Google DeepMind — Train a Small Language Model (advanced skill)
- Google — MLOps for Generative AI
- Microsoft DAT210x — Programming with Python for Data Science
- Chulalongkorn University — IT Security; Intro to Data Analytics and Big Data

## Service
- Technical program committee & reviewer, IEEE Access, ACM TALLIP, IJEECS · IEEE ICITEE 2025, Springer ICONIP 2025, ACM ICMR 2024 (2021 – present): Reviewing NLP, audio and vision research.
- AI technical committee & teaching assistant, AIAT — Super AI Engineer, seasons 2–5 (2022 – 2025): Mentored teams on Thai NLP, speech and LLMs; several went on to win hackathons and team awards.
- Guest lecturer, Huachiew Chalermprakiet University (2022 – 2025): AI futures, speech recognition, image processing and AI frameworks for undergraduates.
- Head of Data Science Camp, IT Camp #14, KMITL (2018): Planned the camp and taught data preparation and modelling.
- Teaching director & lecturer, ToBeIT60, KMITL (2016): Taught IT topics to ~500 high-school students.
- Student exchange researcher, Kurume National College of Technology, Japan (SAKURA Exchange) (2017): Short-term science research exchange.
- Microsoft student volunteer, Microsoft Thailand (2017): Advised customers on Microsoft products.

## Strengths
End-to-end AI & LLM systems; AI product & applications; On-premise AI; System architecture & engineering; AI product strategy; Data & AI infrastructure; Conversational AI; AI evaluation & optimization; AI experimentation; Collaboration & leadership

## Skills
- LLM / GenAI: RAG, Multi-agent systems, Prompt engineering, LangChain, MCP, llama.cpp, vLLM
- AI / ML: NLP, Speech processing, PyTorch, TensorFlow, NeMo, Hugging Face, Quantization
- GenOps: FastAPI, Docker, CI/CD, ONNX, Streaming inference, Observability
- Programming: Python, SQL, JavaScript, Rust
- Cloud: GCP Vertex AI, Secret Manager, Apigee
- Languages: Thai (Native), English (CEFR B1 · professional working proficiency)

## Open source
- ai-model-explorer: See any Hugging Face model part by part without downloading it: architecture, parameters and precision read from the safetensors header in your browser. https://github.com/JoesSattes/ai-model-explorer
- FinOps-Estimator: Capacity planning and FinOps estimation for conversational-AI pipelines: VRAM, latency budgets and GPU cost for STT, LLM, TTS and RAG workloads. https://github.com/JoesSattes/FinOps-Estimator
- Thai-TTS-Evaluation: Evaluation scripts for Thai text-to-speech, focused on speaker tone and pronunciation. https://github.com/JoesSattes/Thai-TTS-Evaluation
- Self-Supervised-LTMMv2: LTMMv2 — notes on a self-supervised Thai speech foundation model. https://github.com/JoesSattes/Self-Supervised-LTMMv2
- CHiME4-SER-Conv-TasNet-Speech-Enhancement: Conv-TasNet speech enhancement on CHiME-4 with ESPnet, used ahead of speech emotion recognition. https://github.com/JoesSattes/CHiME4-SER-Conv-TasNet-Speech-Enhancement
- Vector-Database-Practice-Courses: Coursework notebooks on vector databases and semantic search. https://github.com/JoesSattes/Vector-Database-Practice-Courses
- Thai-Biaffine-Dependency-Parsing: Biaffine dependency parser for Thai on Universal Dependencies treebanks. https://github.com/JoesSattes/Thai-Biaffine-Dependency-Parsing

## Blog
- [Reading a model's architecture from its safetensors header, without downloading the weights](https://joessattes.github.io/Sattaya-AI-Website/blog/reading-the-architecture-off-the-weights/): How I recover a neural network's anatomy from tensor names and shapes alone: 96.8% role accuracy on 510 architectures, from about 46 KB of header. The method behind AI Model Explorer.
- [Why emotion models fall apart outside the lab (and what actually helps)](https://joessattes.github.io/Sattaya-AI-Website/blog/emotion-models-outside-the-lab/): Speech emotion recognition looks solved on benchmarks and breaks on real calls. A researcher's tour of domain shift, speaker leakage, metric learning and self-supervised features.
- [FinOps-Estimator: sizing GPUs for a voice AI pipeline](https://joessattes.github.io/Sattaya-AI-Website/blog/finops-estimator/): An open-source tool that turns concurrency and model choices for STT → LLM → TTS into VRAM, RAM, CPU, TFLOPS and cloud or on-prem cost.
- [Fitting an LLM in your own server room: the memory math behind on-prem AI](https://joessattes.github.io/Sattaya-AI-Website/blog/on-prem-llm-memory-math/): Bits per weight, quantization error, outliers, KV cache and memory bandwidth: how to decide which model actually runs on the GPUs you own.
- [TurboQuant, reviewed: when a theory paper walks straight into production](https://joessattes.github.io/Sattaya-AI-Website/blog/turboquant-review/): A close read of TurboQuant (ICLR 2026): random rotations, Lloyd–Max codebooks and a 1-bit QJL residual, and why it went from proof to vLLM and a 17k-star vector index within weeks.
- [Your MAU is not your load: capacity math for voice AI at scale](https://joessattes.github.io/Sattaya-AI-Website/blog/voice-ai-at-scale/): How to turn "a million users" into a latency budget, a concurrency number, KV-cache memory and a GPU count — with the formulas, not vibes.