Arthit Suriyawongkul

Bangkok, Thailand

Dublin, Ireland

I am an information engineer and researcher working at the intersection of AI ethics, data governance, and software engineering standards. I am currently a PhD researcher in AI ethics and data governance at the School of Computer Science and Statistics, Trinity College Dublin, funded by the Research Ireland Centre for Research Training in Digitally-Enhanced Reality (d-real).

My research asks how software engineering practices and technical standards can bridge the technical and legal layers to make AI systems accountable. A large part of my PhD work is about a vocabulary for system trustworthiness and accountability — mapping the accountability requirements of automated decision-making systems onto the technical capabilities of MLOps.

I am an active contributor to open standards and open-source software. I co-wrote the Linux Foundation whitepaper on the AI Bill of Materials (AI BOM) and contribute to the AI and Dataset profiles of the System Package Data Exchange (SPDX) specification, the Data Privacy Vocabularies and Controls Community Group (DPVCG), and the PyThaiNLP natural language processing library. In 2025 I was a Google Summer of Code contributor adding SPDX 3.0 support to the NTIA conformance checker.

My training spans information technology, cognitive science and natural language, and anthropology — which gives me a cultural lens for translating complex technical systems into policy-ready, auditable practice. I also volunteer for the Thai Netizen Network, a digital civil-rights group based in Bangkok.

news

May 01, 2025	Selected as a Google Summer of Code 2025 contributor with SPDX, adding SPDX 3.0 support to the `ntia-conformance-checker`. 🎉
Oct 01, 2024	A condensed version of my work on AI governance and technical standards — data standards for accountability across the AI system lifecycle appeared in the Council of State Journal (วารสารกฤษฎีกา), Vol. 4, No. 4, 2024.
Jan 15, 2024	Co-authored the Linux Foundation whitepaper Building an AI Bill of Materials.

selected publications

ICSE SEIP
Building an Open AIBOM Standard in the Wild

Gopi Krishnan Rajbahadur, Keheliya Gallaba, Elyas Rashno, and 4 more authors

In Proceedings of the IEEE/ACM 48th International Conference on Software Engineering: Software Engineering in Practice, Apr 2026

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An experience report on developing the AI Bill of Materials (AIBOM) specification, an extension of the ISO/IEC 5962:2021 SPDX SBOM standard that captures AI components such as datasets and iterative training artifacts. Framed through Action Research, it documents a global, multi-stakeholder effort of over 90 contributors, validated against major regulations and ethical standards (EU AI Act, IEEE 7000), industry use cases, practitioner interviews, and an industrial case study.
@inproceedings{rajbahadur2026aibom, title = {Building an Open {AIBOM} Standard in the Wild}, author = {Rajbahadur, Gopi Krishnan and Gallaba, Keheliya and Rashno, Elyas and Suriyawongkul, Arthit and Bennet, Karen and Stewart, Kate and Hassan, Ahmed E.}, booktitle = {Proceedings of the IEEE/ACM 48th International Conference on Software Engineering: Software Engineering in Practice}, series = {ICSE-SEIP '26}, year = {2026}, month = apr, address = {Rio de Janeiro, Brazil}, }

Implementing AI Bill of Materials (AI BOM) with SPDX 3.0: A Comprehensive Guide to Creating AI and Dataset Bill of Materials

Karen Bennet, Gopi Krishnan Rajbahadur, Arthit Suriyawongkul, and 1 more author

Oct 2024

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@misc{bennet2024aibom,
  title = {Implementing {AI} Bill of Materials ({AI} {BOM}) with {SPDX} 3.0: A Comprehensive Guide to Creating AI and Dataset Bill of Materials},
  author = {Bennet, Karen and Rajbahadur, Gopi Krishnan and Suriyawongkul, Arthit and Stewart, Kate},
  year = {2024},
  month = oct,
  publisher = {The Linux Foundation},
}

arXiv

A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms

Gavin Abercrombie, Djalel Benbouzid, Paolo Giudici, and 13 more authors

Jul 2024

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A collaborative, human-centred taxonomy of AI, algorithmic and automation harms, designed to be clear to a broad set of audiences and to be flexible, extensible, and interoperable. Refined iteratively with topic experts and crowdsourced annotation testing as a tool for civil society, educators, policymakers, product teams, and the public.

@misc{abercrombie2024taxonomy,
  title = {A Collaborative, Human-Centred Taxonomy of {AI}, Algorithmic, and Automation Harms},
  author = {Abercrombie, Gavin and Benbouzid, Djalel and Giudici, Paolo and Golpayegani, Delaram and Hernandez, Julio and Noro, Pierre and Pandit, Harshvardhan and Paraschou, Eva and Pownall, Charlie and Prajapati, Jyoti and Sayre, Mark A. and Sengupta, Ushnish and Suriyawongkul, Arthit and Thelot, Ruby and Vei, Sofia and Waltersdorfer, Laura},
  year = {2024},
  month = jul,
  publisher = {arXiv},
  doi = {10.48550/arXiv.2407.01294},
}

NLP-OSS

PyThaiNLP: Thai Natural Language Processing in Python

Wannaphong Phatthiyaphaibun, Korakot Chaovavanich, Charin Polpanumas, and 6 more authors

In Proceedings of the 3rd Workshop for Natural Language Processing Open Source Software (NLP-OSS 2023), Dec 2023

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PyThaiNLP is a free and open-source natural language processing library for the Thai language implemented in Python, providing software, models, and datasets for Thai. The paper outlines its functionalities, datasets and pre-trained language models, development milestones, and how industrial and research communities use it.

@inproceedings{phatthiyaphaibun2023pythainlp,
  title = {{PyThaiNLP}: Thai Natural Language Processing in Python},
  author = {Phatthiyaphaibun, Wannaphong and Chaovavanich, Korakot and Polpanumas, Charin and Suriyawongkul, Arthit and Lowphansirikul, Lalita and Chormai, Pattarawat and Limkonchotiwat, Peerat and Suntorntip, Thanathip and Udomcharoenchaikit, Can},
  booktitle = {Proceedings of the 3rd Workshop for Natural Language Processing Open Source Software (NLP-OSS 2023)},
  publisher = {Association for Computational Linguistics},
  address = {Singapore},
  year = {2023},
  month = dec,
  pages = {25--36},
  doi = {10.18653/v1/2023.nlposs-1.4},
}