Research

Publications

Published, accepted, and preprint work across computer graphics, medical imaging AI, and formal verification.

07 entries

Venue
Conference PaperPreprintJournal Article
Areas
Speech and Language ProcessingComputer GraphicsFormal VerificationMedical Imaging AI
  1. 01 Conference Paper Accepted, to appear Speech and Language Processing 2026 21st International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP) 2026

    A Glossary Must Be Scoped to the Speech It Will Hear: Terminology Control for Live Thai-English Medical Captioning

    Teejuta Sriwaranon, Monchai Lertsutthiwong

    A deployed real-time Thai-English captioning system for medical conferences built around a deterministic term-protection layer: one curated glossary grounds an LLM correction stage over ASR finals, and protected terms are masked before a black-box MT call and restored afterwards, with an append-on-loss fallback. On 440 synthesized utterances with known ground truth, the best configuration reaches 90.0% term fidelity against 47.9% for corrected text through plain MT; on 54.1 minutes of real speech, a support check blocks 19 of 20 off-domain glossary insertions.

    Speech TranslationCode-SwitchingThai NLPTerminology ControlLive CaptioningMedical NLP
    BibTeX
    @inproceedings{sriwaranon2026glossary,
      title = {{A Glossary Must Be Scoped to the Speech It Will Hear: Terminology Control for Live Thai-English Medical Captioning}},
      author = {Teejuta Sriwaranon and Monchai Lertsutthiwong},
      year = {2026},
      booktitle = {2026 21st International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)},
      note = {Accepted, to appear}
    }
  2. 02 Conference Paper Accepted, to appear Computer Graphics 2026 30th International Computer Science and Engineering Conference (ICSEC) 2026

    Cross-Specimen Forecasting of Copper Oxidation Appearance for Physically Based Rendering

    Teejuta Sriwaranon, Borworntat Dendumrongkul, Tanapat Chamted, Sirichai Leelachao, Pizzanu Kanongchaiyos

    A system that observes a copper plate with a fixed camera, forecasts its appearance ten accelerated units ahead, and converts the forecast into metallic-roughness PBR maps. Under leave-one-recording-out evaluation across an accelerated-chamber and an open-air recording, a training-free global affine color extrapolation is the only method that beats repeating the last observed frame in both directions (+11.7% and +51.2%), while chamber-trained learned models improve only on held-back frames of their own recording.

    Appearance ForecastingPBR MaterialComputer GraphicsSurface OxidationCross-Specimen Generalization
    BibTeX
    @inproceedings{sriwaranon2026crossspecimen,
      title = {{Cross-Specimen Forecasting of Copper Oxidation Appearance for Physically Based Rendering}},
      author = {Teejuta Sriwaranon and Borworntat Dendumrongkul and Tanapat Chamted and Sirichai Leelachao and Pizzanu Kanongchaiyos},
      year = {2026},
      booktitle = {2026 30th International Computer Science and Engineering Conference (ICSEC)},
      note = {Accepted, to appear}
    }
  3. 03 Conference Paper Accepted, to appear Formal Verification 2026 30th International Computer Science and Engineering Conference (ICSEC) 2026

    Timed-Automata Verification of Payload-Link Supervision, Watchdog Gating, and A/B Boot Policy in STM32 Flight Software

    Borworntat Dendumrongkul, Natdanai Hirunsirikul, Teejuta Sriwaranon, Phongsatorn Saisutjarit, Pizzanu Kanongchaiyos

    Verifies an abstracted design model of three interacting recovery mechanisms in an STM32 small-satellite flight-software prototype (payload-link supervision, a health-gated hardware watchdog, and a CRC-validated A/B bootloader) as UPPAAL timed automata. Across fifteen model configurations and 254 TCTL formulas every verdict matches a pre-declared oracle; model checking exposes one design defect, confirmed and fixed in source, and the verified bounds are checked against hash-verified hardware traces from 90 fault-injection trials.

    Formal VerificationTimed AutomataUPPAALEmbedded SystemsFlight Software
    BibTeX
    @inproceedings{dendumrongkul2026timedautomata,
      title = {{Timed-Automata Verification of Payload-Link Supervision, Watchdog Gating, and A/B Boot Policy in STM32 Flight Software}},
      author = {Borworntat Dendumrongkul and Natdanai Hirunsirikul and Teejuta Sriwaranon and Phongsatorn Saisutjarit and Pizzanu Kanongchaiyos},
      year = {2026},
      booktitle = {2026 30th International Computer Science and Engineering Conference (ICSEC)},
      note = {Accepted, to appear}
    }
  4. 04 Conference Paper Accepted, to appear Formal Verification 2026 30th International Computer Science and Engineering Conference (ICSEC) 2026

    Formal Verification of DirectX11 Graphics Pipeline Using Colored Petri Nets

    Borworntat Dendumrongkul, Teejuta Sriwaranon, Nuengwong Tuaycharoen, Wiwat Vatanawood

    A compositional Colored Petri Net model of all ten stages of the DirectX 11 graphics pipeline, with the core rasterization path exhaustively verified against six LTL properties spanning safety, liveness, boundedness, and resource correctness. Breadth-first exploration reaches up to 208,905 states; a fault-injection matrix shows every checker is sensitive to its own fault, and two properties fail in stronger forms: per-lane starvation freedom under an arbitration policy DX11 permits, and token conservation under geometry-shader fan-out.

    Formal VerificationColored Petri NetsGraphics PipelineDirectX 11Model Checking
    BibTeX
    @inproceedings{dendumrongkul2026formal,
      title = {{Formal Verification of DirectX11 Graphics Pipeline Using Colored Petri Nets}},
      author = {Borworntat Dendumrongkul and Teejuta Sriwaranon and Nuengwong Tuaycharoen and Wiwat Vatanawood},
      year = {2026},
      booktitle = {2026 30th International Computer Science and Engineering Conference (ICSEC)},
      note = {Accepted, to appear}
    }
  5. 05 Preprint Computer Graphics arXiv preprint (cs.GR, cs.CV) August 2026

    What Will This Copper Look Like Later? Forecasting Surface Appearance and Rendering It as a PBR Material

    Teejuta Sriwaranon, Borworntat Dendumrongkul, Tanapat Chamted, Pizzanu Kanongchaiyos

    A system that forecasts how copper surfaces evolve as they oxidize and renders the predicted appearance as a PBR material (albedo, normal, roughness, metallic) from a single camera observation. A learned spatio-temporal model underperforms last-frame copying on unseen specimens, while a closed-form global color extrapolation transfers successfully, improving accuracy by 13.4-16.7% depending on the prediction horizon, indicating that learned models encode specimen-specific corrosion patterns whereas global color trajectories generalize.

    Appearance ForecastingPBR MaterialComputer GraphicsSurface OxidationSpatio-Temporal Modeling
    BibTeX
    @misc{sriwaranon2026copper,
      title = {{What Will This Copper Look Like Later? Forecasting Surface Appearance and Rendering It as a PBR Material}},
      author = {Teejuta Sriwaranon and Borworntat Dendumrongkul and Tanapat Chamted and Pizzanu Kanongchaiyos},
      year = {2026},
      eprint = {2608.28102},
      archivePrefix = {arXiv},
      primaryClass = {cs.GR},
      doi = {10.48550/arXiv.2608.28102},
      url = {https://arxiv.org/abs/2608.28102}
    }
  6. 06 Journal Article Medical Imaging AI IEEE Access June 2026

    An End-to-End Deep Learning Pipeline for Automated Mandible Virtual Surgical Planning Using Real-World Clinical Data

    Nattapon Kamboonsri, Teejuta Sriwaranon, Natdanai Tantisereepatana, Chedtha Puncreobutr, Boonrat Lohwongwatana, Gregory B. Olson, Alessandro Tel, Massimo Robiony, Titipat Achakulvisut, Peerapon Vateekul

    An end-to-end deep learning pipeline that automates mandible virtual surgical planning from real-world clinical data, combining volumetric segmentation and reconstruction to streamline the workflow for maxillofacial surgery.

    Deep LearningVolumetric SegmentationVolumetric ReconstructionAutomated PipelineVirtual Surgical Planning
    BibTeX
    @article{kamboonsri2026endtoend,
      title = {{An End-to-End Deep Learning Pipeline for Automated Mandible Virtual Surgical Planning Using Real-World Clinical Data}},
      author = {Nattapon Kamboonsri and Teejuta Sriwaranon and Natdanai Tantisereepatana and Chedtha Puncreobutr and Boonrat Lohwongwatana and Gregory B. Olson and Alessandro Tel and Massimo Robiony and Titipat Achakulvisut and Peerapon Vateekul},
      year = {2026},
      journal = {IEEE Access},
      doi = {10.1109/ACCESS.2026.3702327},
      url = {https://ieeexplore.ieee.org/document/11557298}
    }
  7. 07 Conference Paper Formal Verification 2026 23rd International Joint Conference on Computer Science and Software Engineering (JCSSE) June 2026

    Fine-Grained Formal Verification of an Asynchronous Speaker Diarization Pipeline Using Hierarchical Timed Colored Petri Nets

    Teejuta Sriwaranon, Nuengwong Tuaycharoen, Wiwat Vatanawood

    A fine-grained hierarchical Timed Colored Petri Net (HTCPN) model of an asynchronous speaker diarization pipeline that exposes three generalizable structural deadlock patterns in concurrent AI pipelines. Seven correctness properties are verified, including a novel attribution consistency property, showing that sub-module decomposition is necessary for complete pipeline verification.

    Formal VerificationHierarchical Petri NetsSpeaker DiarizationReachability AnalysisDeadlock FreedomLiveness
    BibTeX
    @inproceedings{sriwaranon2026finegrained,
      title = {{Fine-Grained Formal Verification of an Asynchronous Speaker Diarization Pipeline Using Hierarchical Timed Colored Petri Nets}},
      author = {Teejuta Sriwaranon and Nuengwong Tuaycharoen and Wiwat Vatanawood},
      year = {2026},
      booktitle = {2026 23rd International Joint Conference on Computer Science and Software Engineering (JCSSE)},
      doi = {10.1109/JCSSE68839.2026.11597080},
      url = {https://ieeexplore.ieee.org/document/11597080}
    }