Publications
For citation metrics and automatically indexed versions, see Google Scholar. Workshop papers are labelled separately from main-conference publications. An asterisk is not used for contribution because author-contribution statements are available for only some manuscripts.
Peer-reviewed conference publications
Beyond Major Floods: Deep Learning for Detecting Shallow Water Inundation in Agricultural Areas
Phongsakon Mark Konrad, Toygar Tanyel, Serkan Ayvaz.
Ten deep-learning segmentation models for three-class Sentinel-1 SAR mapping; ResNet-UNet matched DeepLabv3+ with lower compute and memory requirements.
Workshop publications
Self-Reports Do Not Identify Self-Models: An Identifiability Test for Counterfactual Reports
Phongsakon Mark Konrad, Toygar Tanyel, Serkan Ayvaz.
Environment-shift tests across three open models show that correct counterfactual reports do not by themselves identify a self-model bound to the intervention.
Decoded but Unused: Instruction Tuning Routes Moral Framing into the Judgment Readout
Phongsakon Mark Konrad, Toygar Tanyel, Serkan Ayvaz.
A matched pretrained and instruction-tuned audit separates a representation that is decodable from one that is causally routed into judgment.
A Path Already Walked: On Inheriting Network-Neuroscience Tools for Mechanistic Interpretability
Phongsakon Mark Konrad, Toygar Tanyel, Serkan Ayvaz.
A position paper specifying the graph objects, projections, null models, and failure criteria needed for a disciplined transfer of network-neuroscience tools.
Architecture Without Architects: How AI Coding Agents Shape Software Architecture
Phongsakon Mark Konrad, Tim Lukas Adam, Raffaele Terrenzi, Serkan Ayvaz.
Five mechanisms and six prompt-architecture coupling patterns describe how coding agents make implicit architectural choices.
CAKE: Cloud Architecture Knowledge Evaluation of Large Language Models
Tim Lukas Adam, Phongsakon Mark Konrad, Raffaele Terrenzi, Finn Gunnar Lukas, Rukiye Yilmaz, Kamil Sierszecki, Serkan Ayvaz.
A 188-question, expert-validated benchmark evaluates 22 model configurations across knowledge levels and response formats.
A Reference Architecture for Agentic Hybrid Retrieval in Dataset Search
Raffaele Terrenzi, Phongsakon Mark Konrad, Tim Lukas Adam, Serkan Ayvaz.
An auditable Plan-Retrieve-Evaluate architecture combines BM25, dense retrieval, reciprocal-rank fusion, and offline metadata augmentation.
Preprints and manuscripts
Coverage Debt: Pricing the Conformal Coverage Gap Through a Real Electricity-Market Redesign
Phongsakon Mark Konrad, Tim Lukas Adam, Serkan Ayvaz.
Across eight European bidding zones, a static conformal calibration loses coverage with volatility and creates a matching decision-level loss-floor breach; refreshed calibration restores the guarantee.
Documented contribution: conceptualization, methodology, software, formal analysis, data curation, visualization, and original draft.
Challenges in Deep Learning-Based Small Organ Segmentation: A Benchmarking Perspective for Medical Research with Limited Datasets
Phongsakon Mark Konrad, Andrei-Alexandru Popa, Yaser Sabzehmeidani, Liang Zhong, Madhulika Tripathy, Andrei Constantinescu, Elisa A. Liehn, Serkan Ayvaz.
Ten models, ablations, bootstrap uncertainty, and independent distribution-shift data show that architecture rankings are unstable in very small cardiovascular histology datasets.
Documented contribution: conceptualization, data curation, formal analysis, methodology, software, visualization, validation, and original draft.
How Much of Non-Destructive Fruit-Ripeness Assessment Is Real? A Confound-Controlled, Low-Cost Visible Hyperspectral Study Across Five Fruit
Phongsakon Mark Konrad, Casper Kunstmann-Olsen, Jacek Fiutowski, Serkan Ayvaz.
A species-only baseline separates genuine spectral skill from fruit recognition: visible spectra retain a strong within-species ripeness signal, while pooled firmness is heavily confounded.
Documented contribution: conceptualization, methodology, software, formal analysis, investigation, data curation, visualization, and original draft.
Acceptance Cards: A Four-Diagnostic Standard for Safe Fine-Tuning Defense Claims
Phongsakon Mark Konrad, Toygar Tanyel, Serkan Ayvaz.
A claim-specific audit checks statistical reliability, fresh-subject generalization, mechanism alignment, and transfer before upgrading a held-out improvement to a full defense claim.
The Open-Box Fallacy: Why AI Deployment Needs a Calibrated Verification Regime
Phongsakon Mark Konrad, Tim Lukas Adam, Anders C. H. Merrild, Riccardo de Rosa, Raffaele Terrenzi, Toygar Tanyel, Serkan Ayvaz.
Argues that mechanistic evidence should be one input to use-specific deployment governance and proposes a six-component Verification Coverage standard.