Spark Sessions 002

Tue Dec 10 2024 at 06:00 pm to 08:00 pm UTC+01:00

Faculty of Computer and Information Science | Ljubljana

Data Science@UL-FRI
Publisher/HostData Science@UL-FRI
Spark Sessions 002
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The Spark Sessions are all about about igniting your creativity and passion through inspiring talks and discussions!
About this Event

Spark Sessions 002


The Spark Sessions are a recurring event of the Data Science Initiative at the Faculty of Computer and Information Science. They are designed to facilitate the exchange of ideas and inspiration. The event consists of several snappy (5-7 min) presentations, followed by a casual gathering with refreshments:


  1. Intro: Is There a Data Engineering Minimum for a Professional Data Scientist? by Erik Štrumbelj
  2. Seeing Through Data: Eye Tracking Insights into Graph Comprehension by Leon Hvastja (Data Science Student, University of Ljubljana)
    Eye-tracking technology has gained traction over the past decade, mainly due to its increased availability. Traditionally, graphs were evaluated through performance metrics, but eye tracking offers a deeper understanding of the underlying cognitive processes involved. This technology has broad applications, including in education to enhance learning, in understanding disabilities, building cognitive models of perception, and understanding the differences between expert and non-expert users.
  3. Machine Learning and AI in Analysis of Neuroimaging Data by Grega Repovš (Professor, Department of Psychology, University of Ljubljana)
    Neuroimaging processing and analysis works on large amounts of multimodal data in spatial and temporal domains resulting in a wide range of features at mulitiple levels of observation. Machine learning and AI are becoming important tools in optimizing data preprocessing, enabling novel analytical approaches, relating neuroimaging features to individuals' cognition and behavior, and supporting diagnosis and treatment of brain diseases.
  4. Blazing Fast Computation with JAX by David Nabergoj (Young Researcher, University of Ljubljana)
    JAX is a Python library for accelerator-oriented array computation and program transformation, designed for high-performance numerical computing and large-scale machine learning. We'll see what makes it so much faster than PyTorch/Tensorflow, and how it achieves an over 4000x speed-up in reinforcement learning applications.
  5. What’s It Like to Crawl 100M Web Pages Every Week by Roq Xever (CEO and Founder, PredictLeads)
    I'll talk about the infrastructure, costs, and challenges we face while crawling the web for information on over 70 million companies.
  6. TBA Interested in filling this spot? !.
  7. Snacks and drinks and discussions.




Partnering with Forum podatkovne analitike.


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Faculty of Computer and Information Science, 113 Večna pot, Ljubljana, Slovenia

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