Courses

  • Introduction to Cultural Analytics: Data curation and analysis (with Pandas), Fall 2022.
  • Introduction to Cultural Analytics: Applied Machine learning, Fall 2022.
  • Python programming for beginners, Fall 2022.
  • Digital Implementations in Heritage: Getting started with Jupyter Lab notebooks and OCR, Fall 2022.
  • Digital Implementations in Heritage: Text Recognition (OCR), Fall 2021.

Supervision

  • Doctoral student: Raphaela M. Heil, Department of IT, Uppsala University. Thesis title: Document Image Processing for Handwritten Stenography Recognition – Deep Learning-based Transliteration of Astrid Lindgren’s Stenographic Manuscripts. Co-supervisor, 2018 – Present.
  • Thesis Subject Reader, Sushruth Badri, Masters thesis: Data Science – Machine Learning and Statistics. Title: Analysis and evaluation of facial feature extraction techniques in age estimation with bias mitigation. 30 credits, second cycle, Feb. – April 2023. 
  • Project supervisor, 3 students, Masters in Data Science Project: Liang Cheng, Adam Axelsson and Jonas Frankemölle, Department of IT, Uppsala University. Title: Marginalia and Machine Learning: a Study of Durham University and Uppsala University Marginalia Collections. Main supervisor, 15 credits, second cycle, Fall 2022.
  • Project co-supervisor, 3 students, Masters in Data Science Project: Sushruth Badri, Erik Norén and Christoph Nötzli, Department of IT, Uppsala University. Title: Bias in image classification algorithms. Assistant supervisor, 15 credits, second cycle, Fall 2022.
  • Project intern: Vasiliki Sampa, Department of ALM, Uppsala University. Topic: Preparing annotations for object detection on archaeological data, Fall 2022.
  • Project intern: Rekha Pelassa, Department of ALM, Uppsala University. Topic: Preparing annotations for object detection on archaeological data, Spring 2022.
  • Project supervisor, 2 students, Masters in Data Science Project: Dmitrijs Kass and Charalampos Poulikidis Moutsanas, Department of IT, Uppsala University. Title: AttentionHTR: Handwritten Text Recognition Based on Attention Encoder-Decoder Networks. Main supervisor, 15 credits, second cycle, Fall 2021.
  • Project supervisor, 5 students, Masters in Data Science Project: Simon Leijon, Hampus Widén, Martin Sundberg, Petter Sigfridsson and Jonathan Kurén, Department of IT, Uppsala University. Title: Document Image Binarization for Heavily Degraded Swedish Manuscripts. Main supervisor, 15 credits, second cycle, Fall 2021.

Training

  • Academic Teacher Training course, Uppsala University, fall 2022. Extent: five weeks on a full-time basis.
  • Supervising Doctoral Students, Uppsala University, Spring 2022. Working hours correspond to three weeks of full-time staff training.
  • IBM Data Science Professional Certication. Completed courses: what is data science, tools for data science, data science methodology, Python for data science and AI, Databases and SQL for data science, Data analysis with Python, Data visualization with Python, and Machine Learning with Python (100% grades), 2020.
  • Course in IPR and commercialization, Communication and Outreach: Intellectual property rights and commercialization, Uppsala University, March 2018.
  • Student-active learning, Uppsala University. One-day workshop – spring 2017.