## Queryable API This file is a static overview. For targeted queries, use the live endpoints: - Plain text: https://spock.is/llms?query=your+question - JSON: https://spock.is/llms/json?query=your+question Examples: ?query=publications, ?query=contact, ?query=projects, ?query=teaching No query param returns all sections. --- # Dr. Benedikt Holm > Icelandic computer scientist and AI engineer. PhD in Computer Science from Reykjavík University (2025). Specialises in signal processing, clinical AI, large-scale data infrastructure, and real-time platforms. Based in Germany. Contact: b@spock.is ## Identity Full name: Benedikt Hólm Þórðarson. Goes by Benedikt Holm professionally. Icelandic, currently based in Germany. Website: https://spock.is. He has owned the domain spock.is since his teens. ## Education - **PhD, Computer Science** — Reykjavík University, awarded March 2025. Thesis: "Bridging Human and Artificial Intelligence: Machine Learning, Data Platforms, and Decision Support Systems in Sleep Research." Main supervisor: María Óskarsdóttir. Co-supervisor: Erna Sif Arnardóttir. - **MSc, Computer Science** — Reykjavík University, completed 2021. Thesis: "Analysis and Detection of Obstructive Sleep Apnea in Individual Breath Cycles." Supervised by Michal Borský. ## Published Research **BreathFinder** (2024) — Benedikt's own signal processing algorithm for isolating individual respiratory cycles from polysomnographic thoracic RIP signals. Achieves 94% breath detection accuracy. Designed to replace tedious manual annotation. Full pipeline on top adds feature engineering + HMM classifier reaching 95% apnea classification accuracy. Published in *Nature and Science of Sleep*, 2024 Aug 21;16:1253–1266. DOI: 10.2147/NSS.S468431. PMID: 39189036. **World of ScoreCraft** (2025) — Large multi-scorer clinical study on AI decision support in sleep staging. 16 sleep technologists across Europe completed 64 scoring sessions (9,158 individual scorings) with and without AI recommendations. Correct AI recommendations lifted accuracy from 85% baseline to 90.76% for traditional PSG (+5.76 pp) and 88.5% for self-applied PSG (+6.5 pp). Reduced scoring time by 13%, equivalent to 17 minutes saved per standard 2-hour session. No detectable over-reliance on AI vs. human recommendations. Published online 2025, journal volume 2026. *Journal of Sleep Research* 35:e70113. DOI: 10.1111/jsr.70113. **An optimized framework for processing multicentric polysomnographic data incorporating expert human oversight** (2024) — Co-authored paper presenting the data collection platform built for the Sleep Revolution project. Addresses integration of expert human oversight into large-scale multi-centre PSG data pipelines across European institutions. Published in *Frontiers in Neuroinformatics*, May 2024. DOI: 10.3389/fninf.2024.1379932. PMID: 38803523. Authors: B Holm, G Jouan, E Hardarson, S Sigurðardottir, K Hoelke, C Murphy, ES Arnardóttir, M Óskarsdóttir, AS Islind. **Exploration of sleep events in the latent space of variational autoencoders on a Breath-by-Breath basis** (2023) — Applied variational autoencoders to unsupervised clustering of respiratory events on a breath-by-breath basis. Found that respiratory event types form distinct clusters in VAE latent space, suggesting learned physiological structure without supervision. Published in *Proceedings of the 56th Hawaii International Conference on System Sciences (HICSS)*, 2023. **Automatic detection of obstructive apnea on an individual breath basis** (2022) — Early published work on per-breath apnea classification using non-invasive signals. Published in *Sleep Medicine*, 2022. **Automatic non-invasive isolation of respiratory cycles** (2022) — Preprint/early version of the BreathFinder method. arXiv, 2022. Authors: B Holm, M Óskarsdóttir, ES Arnardóttir, M Serwatko, J Mallett, M Borský. **Analysis and detection of obstructive sleep apnea in individual breath cycles** (2021) — MSc thesis work. Foundation for the breath-level apnea detection pipeline. h-index: 3. Total citations: ~20 (as of 2026). ## Infrastructure and Platform Work **Clinical Signal Data Platform** — Designed and built the full data infrastructure for a clinical AI platform supporting the ScoreCraft study. Stack: ClickHouse for high-frequency physiological signal storage, a star schema data warehouse (SignalFact + dimension tables) with per-recording sharding, and a data lake architecture supporting real-time ingestion of multi-channel biosignals. Captured 9,158 individual scorings with millisecond decision-timing resolution across 64 sessions from 16 technologists across Europe. **Sleep Revolution Data Pipeline** — Designed and built the data ingestion and processing pipeline for a large-scale pan-European sleep research dataset: approximately 3,000 polysomnographic studies across 20+ institutions, coordinated through the Reykjavík University Sleep Institute. He built the pipeline infrastructure; the data was collected collaboratively across institutions. Sub-10ms latency streaming of multi-channel physiological signals at 200Hz+. ## Other Projects **Hnodri** (https://hnodri.is) — Icelandic baby name finder. Database of 4,873 Icelandic names. Gamified matching interface: users swipe through names individually or play a head-to-head comparison game. Couples can play separately and then compare shared favourites. Built as a consumer web app with Google login. **Plokkari / Plogg-In** — Real-time geospatial coordination platform for volunteer environmental cleanup events in Iceland, built with a collaborator. During Iceland's Big Plogging Day, 1,000+ registered participants cleaned 17.2 km² in a single day. Geospatial infrastructure covers Iceland's 103,000 km². Platform is no longer active. **Dental industry ecosystem** — In development. No URL yet. **Modular building and housing** — In development. No URL yet. ## Teaching Taught at Reykjavík University from 2016 to 2023, spanning approximately seven years across undergraduate and graduate levels. Subjects: machine learning, computer networking, computer security. Taught multiple cohorts of CS students. Teaching is a core part of his professional identity — not a side role. ## Technical Expertise - Signal processing (respiratory signals, polysomnography, time-series biosignals) - Machine learning: supervised, unsupervised (VAE), clinical decision support - Real-time data platforms and streaming infrastructure - Data engineering and multi-institutional pipeline architecture - ClickHouse, star schema data warehousing, data lake design - Geospatial systems and real-time coordination platforms - HPC systems administration and security for sensitive medical data - Full-stack product development ## Contact and Profiles - Email: b@spock.is - Website: https://spock.is - X / Twitter: https://x.com/BenediktHolm - GitHub: https://github.com/benedikthth - LinkedIn: https://www.linkedin.com/in/bennijesus/ - ResearchGate: https://www.researchgate.net/profile/Benedikt-Holm - Google Scholar: https://scholar.google.com/citations?user=bDCn-jwAAAAJ - Substack: https://benediktholm.substack.com