Pavlin Poličar

Publications

Peer-Reviewed Articles

  1. Klemenc et al., "Automated Assignment Grading with Large Language Models: Insights From a Bioinformatics Course", Frontiers in Neuroinformatics, 2026. (link)
  1. Poličar et al., "Automated Assignment Grading with Large Language Models: Insights From a Bioinformatics Course", Bioinformatics, 2025. (link)
    Oral Presentation at ISMB/ECCB 2025.
  2. Poličar, Zupan, "Uncovering temporal patterns in visualizations of high-dimensional data", Machine Learning, 2025. (link)
  1. Poličar et al., "Teaching bioinformatics through the analysis of SARS-CoV-2: project-based training for computer science students", Bioinformatics, 2024. (link)
    Oral Presentation at ISMB 2024.
  2. Poličar et al., "openTSNE: a modular Python library for t-SNE dimensionality reduction and embedding", Journal of Statistical Software, 2024. (link)
  1. Poličar, Zupan, "Refining Temporal Visualizations Using the Directional Coherence Loss", Proceedings of the 26th International Conference on Discovery Science, 2023. Porto, Portugal (link)
  2. Poličar et al., "Nation-wide ePrescription Data Reveals Landscape of Physicians and their Drug Prescribing Patterns in Slovenia", Proceedings of the 21st International Conference on Artificial Intelligence in Medicine, 2023. Portorož, Slovenia (link)
  1. Moroz et al., "Evolution of glutamatergic signaling and synapses", Neuropharmacology, 2021. (link)
  2. Poličar et al., "Embedding to Reference t-SNE Space Addresses Batch Effects in Single-Cell Classification", Machine Learning, 2021. (link)
  1. Stražar et al., "scOrange — a tool for hands-on training of concepts from single-cell data analytics", Bioinformatics, 2019. (link)

Preprints

  1. Poličar et al., "Generating Statistical Charts with Validation-Driven LLM Workflows", In review. (link)
  2. Poličar et al., "Inferring Chronic Treatment Onset from ePrescription Data: A Renewal Process Approach", In review. (link)
  3. Bischoff et al., "velotest: Statistical assessment of RNA velocity embeddings reveals quality differences for reliable trajectory visualizations", In review. (link)
  4. de Bodt & Diaz-Papkovich et al., "Low-dimensional embeddings of high-dimensional data", In review. (link)
  5. Poličar, Zupan, "VERA: Generating Visual Explanations of Two-Dimensional Embeddings via Region Annotation", In review. (link)
Journal Conference Preprint

Talks & Seminars

Honors & Awards

Open-Source Software