Data Science Seminars

University of Tartu Institute of Computer Science is organising data science seminars to a wider audience where researchers, lecturers, students, alumni and industry representatives are sharing their knowledge on the subject. The seminars are conducted in English. Seminars are recorded and can be viewed afterwards. 

Seminars are supported by the University of Tartu ASTRA project PER ASPERA Doctoral School of Information and Communication Technologies.

The seminars for 2022 have all been held. Stay tuned for new seminars in 2023!


Past seminars


 

 The seminar featured the following speakers:

You can find the seminar recording here.

The speaker Raivo Kolde has been supported by European Social Fund via „ICT programme“ measure.

Image

Seeing is believing and humans rely on their sight to make decisions. As a result, a lot of data we gather in various ways is visual. It is natural to want to get the most out of the data we have and one method toward achieving this is semantic segmentation. In essence, semantic segmentation means figuring out which pixels belong to which type of object. For example, how can a machine recognize a pedestrian on a road crossing or differentiate between fields and swamplands? Deep Learning has helped make huge strides in the field of semantic segmentation but there are still many challenges to overcome!

Speakers and presentations:

You can find the seminar recording here.

The benefits arising from Artificial Intelligence (AI) in terms of prediction accuracy, automation, new products and services or cost reduction are remarkable. But enterprises need to build trust and transparency in the data and algorithm used in AI systems to increase adoption. By default, AI systems such as machine learning or deep learning produce outputs with no explanation or context. As the predicted outcomes turn into recommendations, decisions or direct actions, humans tend to look for justification. Most experts in the field agree that AI systems should be less ambiguous to the end-users and subjects of algorithmic decision-making. In this seminar, four speakers from the University of Tartu and Wise will discuss the explainability and transparency of AI as well as the requirements and challenges of building a robust machine learning system.

Speakers and presentations:

You can find the seminar recording here.

Moderators:

  • Ahmed Awad, Professor of Data Systems @ University of Tartu, Estonia
  • Feras M. Awaysheh, Assistant Professor of Data Analytics @ University of Tartu, Estonia

Speakers:

  • Andreas Hellander (University of Uppsala): Scalable Federated Machine Learning with FEDn
  • Peter Richtarik (KAUST): EF21: A new, simpler, theoretically better, and practically faster error feedback
  • Aaron Ardiri (RIoT Secure): The Internet of Disconnected Things
  • Essam Mansour (Concordia University): A Data Discovery Platform Empowered by Knowledge Graph Technologies: Challenges and Opportunities

You can find the seminar recording here.

Moderator: Mark Fišel (UniTartuCS)

Speakers and presentations:

  • Anna Mischenko (AI_NORN): AI_NORN – programming robots as an art
  • Eduard Barbu (UniTartuCS): Devices to compute human creativity
  • Anna Aljanaki (UniTartuCS): Let there be music: when AI learns to compose
  • Jaanus Jaggo (UniTartuCS): The secret of making an endless world for a video game

You can find the seminar recording here.

 

Moderator: Riccardo Tommasini, Lecturer of Data Management at UniTartuCS

Speakers and presentations:

You can find the seminar recording here.

Moderator: Ülar Allas from High Performance Computing Center of UniTartu

Speakers and presentations:

You can find the seminar recording here.

Moderator: Elena Sügis (UniTartuCS)

Speakers and presentations:

  • Markus Lippus (MindTitan): Delivering on 85% of your AI projects
  • Kalev Koppel (STACC): Hired or fired by AI
  • Marlon Dumas (UniTartuCS): Process mining in action
  • Jaak Vilo (UniTartuCS): Supply chain for data scientists
  • Elena Sügis (UniTartuCS): Data science 101 for your business

You can find the seminar recording here.

(Online)

Introduction to the topic by:
Kaur Alasoo & Riccardo Tommasini (University of Tartu Institute of Computer Science)

Speakers and presentations:

  • Łukasz Grądzki (Bolt): Data Platform at Bolt: Lessons from scaling data infrastructure in a hyper growth company
  • Kristjan Eljand (Eesti Energia): Labelling the labelled
  • Rao Pärnpuu (Starship Technologies): Using datasets to develop and globally operate self-driving robots
  • Taivo Pungas: Datasets: the source code of Software 2.0.

You can find the seminar recording here.

(Online)

Moderator: Jaak Vilo (UniTartu ICS)

Speakers and presentations:

  • Krista Fischer (UniTartu, Estonian Genome Center): Nowcasting and forecasting of COVID-19 in Estonia: experiences from spring 2020
  • Hedi Peterson (UniTartu ICS): COVID-19 and us. Let the data speak.
  • Raivo Kolde (UniTartu ICS): Creating (inter)national COVID-19 evidence base through health data standardisation
  • Dan Bogdanov (Cybernetica, HOIA.me): COVID-19 contact tracing apps in Estonia and abroad

You can find the seminar recording here.

Moderator: Tambet Matiisen (UniTartu Autonomous Driving Lab)

Speakers and presentations:

  • Naveed Muhammad (UniTartu ICS): Autonomous driving – past, present and future
  • Martin Appo (Cleveron): Cleveron’s journey towards driverless delivery vehicle
  • Sergey Kharagorgiev (Starship Technologies): Computer vision for obstacle avoidance in the wild
  • Alex Kendall (Wayve): Creating an artificial driving intelligence

Moderator: Alexander Nolte (UniTartu ICS)

Speakers and presentations:

  • Marlon Dumas (UniTartu ICS): Data science and AI for business process improvement
  • Markus Lippus (MindTitan): The unexpected use cases for a machine that can listen
  • Sven Laur (STACC): Health insurance analytics: A case study at the Estonian Health Insurance Fund
  • Lauri Antalainen (CoreGrow): Optimizing production processes: how can data science help?

You can find the seminar recording here.

Moderator: Meelis Kull (UniTartu ICS)

Speakers and presentations:

  • Lauri Sokk (Smart City Tartu): Smart City Tartu – why we do what we do?
  • Hans Leis (Bercman Technologies): The Smart Pedestrian Crosswalk
  • Anti Gruno (Datel): Metallica concert through SAR eye, using Datel’s Early Warning system SILLE
  • Roman Meeksa (Tartu City Government): Tartu Smart Bike Share – how and what do we see?

You can find the seminar recording here.

Moderator: Meelis Kull (UniTartu ICS)

Speakers and presentations:

  • Ando Saabas (Taxify/Bolt): Interpreting tree-based models
  • Anna Aljanaki (Mooncascade): What music information retrieval can tell us about Eurovision?
  • Kairit Sirts (UniTartu): Understanding neural models for text analysis
  • Markus Lippus (MindTitan): Trust the machine, or do you really need to know what your algorithm is doing?

You can find the seminar recording here.

Moderator: Sherif Sakr (UniTartu ICS)

Speakers and presentations:

  • Mohamed Maher (UniTartu): SmartML – Towards Optimized Automated Machine Learning Pipelines in the Big Data Era
  • Felix Mohr (Paderborn University): ML-Plan – Automated machine learning via hierarchical planning
  • Martin Strohbach: IoTCrawler – Building a Search Engine for the Internet of Things
  • Mihkel Solvak (UniTartu): Anonymized i-voting log data: how can it be used or abused to understand voter behavior?
  • Lauri Sokk (Tartu City Government): Smart City since 1632

You can find the seminar recording here.

Moderator: Amnir Hadachi (UniTartu ICS)

Speakers and presentations:

  • Margus Tiru (Positium): Mobile Positioning Data for Human Spatio-Temporal Behavioural Analysis
  • Toivo Vajakas (Reach-U): Some thoughts on making use of passive mobile positioning data
  • Kalev Koppel (KappaZeta): Deep learning for satellites based grasslands monitoring. Lessons learned
  • Mikhail Iljin (Taxify): Real-time rebalancing of demand and supply at Taxify

You can find the seminar recording here

Moderator: Leopold Parts (UniTartu ICS)

Speakers and presentations:

  • Krista Fischer (UniTartu, Estonian Genome Center): Disentangling causes and effects – how can genetics help?
  • Taavi Tamkivi (dataminer.ee): Being a good cop of the data world – how to find criminals behind the lakes of data
  • Maris Alver (UniTartu, Estonian Genome Center): Implications of big data for clinical management of cardiovascular disease
  • Andrei Tsõmbaljuk (TransferWise): Machine Learning at TransferWise
  • Andres Võrk (Tni Tartu, CITIS): Examples of data-driven policy impact evaluation in Estonia

You can find the seminar recording here.

Moderator: Mark Fišel (UniTartu ICS)

Speakers and presentations:

  • Tanel Alumäe (TalTech): Speech Recognition
  • Silver Traat (TEXTA): Use cases from TEXTA
  • Sven Laur (STACC, UniTartu ICS): EstNLTK libraries for NLP
  • Risto Hinno (FeelingStream): Daily challenges with text mining
  • Kairit Sirts (UniTartu ICS): Clinical text Classification

You can find the seminar recording here. 

Moderator: Leopold Parts (UniTartu ICS)

Speakers and presentations:

  • Marek Rei (University of Cambridge): Human Interpretability of Machine Learning Models
  • Mihkel Solvak (UniTartu): Real-Time Predictive Economics
  • Toomas Kirt (Statistics Estonia): Big Data in Statistics
  • Kaspar Märtens (Oxford University): Modern Frameworks for Automated Inference
  • Krista Fischer (UniTartu): Disentangling Correlation and Causality in the Big Data Era
  • Alex Graves (DeepMind): Associative Compression Networks For Representation Learning

You can find the seminar recording here. 

Moderator: Tambet Matiisen (UniTartu ICS)

Speakers and presentations:

  • Raivo Sell (TUT): ISEAUTO – the first Estonian self-driving car project with Silberauto
  • Lindsay Roberts (Starship Technologies): Visual Localisation in Urban Environments
  • Lauri Tammeveski (Milrem Robotics): How to recognize different types of trees from quite a long way away
  • Allan Aksiim (Foundation for Future Technologies): Laws, Regulations and Ignorance
  • Andrej Karpathy (Tesla): The Challenges of Applying Machine Learning for Autonomous Vehicles (video broadcast)

You can find the seminar recording here. 

Moderator: Dmytro Fishman (UniTartu ICS)

Speakers and presentations:

  • Kaupo Palo (PerkinElmer): Microcopy image analysis
  • Karl Kruusamäe (UniTartu): Opening Machine's Eyes: Why We Need Image Analysis on Robotics?
  • Kaupo Voormansik (KappaZeta): Satellite Imagery Time Series Processing
  • Gholamreza Abarjafari (UniTartu): DeepVision for Human Behaviour Analysis

You can find the seminar recording here. 

Moderator: Raul Vicente (UniTartu ICS)

Speakers and presentations:

  • Jaan Aru (UniTartu ICS): Deep Learning and the Brain 
  • Robert Roosalu (MindTitan): Enterprise Deep Learning
  • Tambet Matiisen (UniTartu ICS): Keras Advanced Tips & Tricks
  • Hendrik Luuk (AlphaBlues): Automating customer service chat with AI

You can find the seminar recording here

Moderator: Meelis Kull (UniTartu ICS)

Speakers and presentations:

  • Kaur Alasoo (UniTartu ICS): Uncovering Hidden Biases in Data with Visualisation
  • Tormi Reinson (Pipedrive): Communicating Data with D3.js
  • Anto Aasa (UniTartu): Visualizing Data: Space & Time
  • Mirko Känd (IxD.ma): Everyone is a Data Scientist

You can find the seminar recording here.

Moderator: Leopold Parts (UniTartu ICS)

Speakers and presentations:

  • Ilya Kuzovkin (UniTartu ICS): Deep Learning Zoo
  • Mark Fišel (UniTartu ICS): Neural Machine Translation
  • Tanel Pärnamaa (Fits.me): A Neural Knowledge Language Model
  • Tambet Matiisen (UniTartu ICS): Life in OpenAI

Moderator: Leopold Parts (UniTartu ICS)

Speakers and presentations:

  • Jaak Vilo (UniTartu ICS): Data for Health
  • Eneli Oitmaa (Asper Biotech): Applying Bioinformatics Analysis in the Genetic Laboratory Settings
  • Dmytro Fishman (UniTartu ICS): Deep Learning in Health Care
  • Lili Milani (Estonian Genome Centre): Electronic Health Records and Genomes for Research

You can find the seminar recording here

Moderator: Kristjan Eljand (STACC)

Speakers and presentations:

  • Fredrik Milani (UniTartu ICS): Business Process Mining
  • Martin Märss (Swedbank): BI Concept in a Bank
  • Marlon Dumas (UniTartu ICS): Predictive Business Process Monitoring
  • Ester Eggert (TransferWise): Applying ML to Create Money without Borders
  • Nicola Vitucci (Open Data Day): Linked Data: A Quick Introduction

You can find the seminar recording here

Moderator: Leopold Parts (UniTartu ICS)

Speakers and presentations:

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