Andmeteaduse seminarid

Moderaatorid:

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

Esinejad:

• Andreas Hellander (Uppsala Ülikool): 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 Ülikool): A Data Discovery Platform Empowered by Knowledge Graph Technologies: Challenges and Opportunities

Seminari salvestist saab järele vaadata siit.

Moderaator: Mark Fišel (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

• 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

Seminari salvestist saab järele vaadata siit.

12.05.2021 | Velocity 360: A tour on the 3rd dimension of Big Data

Moderaator: Riccardo Tommasini (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

• Emanuele Della Valle (Politecnico di Milano; Quantia Consulting): Taming velocity: A tale of four streams
• Matteo Ferroni (Bottega52): Fight data gravity with event-driven architectures
• Niccolò Raspa (SIGHUP): Accelerating data science with MLOps and cloud native technologies

Seminari salvestist saab järele vaadata siit.

Moderaator: Ülar Allas (Tartu Ülikooli teadusarvutuste keskus)

Esinejad ja ettekanded:

• Ott Oopkaup (TÜ teadusarvutuste keskus): High performance computing: A look into how large-scale data storage and processing is done
• Reedik Mägi (TÜ Geenivaramu): Computational challenges in genomics: association studies, genetic risk scores and AI
• Kaur Alasoo (TÜ arvutiteaduse instituut): Automating the processing of terabyte-scale data with software containers and workflow engines
• Velle Toll (TÜ füüsikainstituut): HPC for weather, climate and Earth system prediction
• Pekka Manninen (LUMI superarvuti): LUMI: the European flagship supercomputer of the North

Seminari salvestist saab järele vaadata siit.

Moderaator: Elena Sügis (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

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

Seminari salvestist saab järele vaadata siit.

Sissejuhatus teemasse: Kaur Alasoo & Riccardo Tommasini (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

• 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.

Seminari salvestist saab järele vaadata siit.

Moderaator: Jaak Vilo (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

• Krista Fischer (TÜ, Geenivaramu): Nowcasting and forecasting of COVID-19 in Estonia: experiences from spring 2020
• Hedi Peterson (TÜ arvutiteaduse instituut): COVID-19 and us. Let the data speak.
• Raivo Kolde (TÜ arvutiteaduse instituut): 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

Seminari salvestist saab järele vaadata siit.

Moderaator: Tambet Matiisen (TÜ isejuhtivate sõidukite labor)

Esinejad ja ettekanded:

• Naveed Muhammad (TÜ arvutiteaduse instituut): 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

Moderaator: Alexander Nolte (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

• Marlon Dumas (TÜ arvutiteaduse instituut): 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?

Seminari salvestist saab järele vaadata siit.

Moderaator: Meelis Kull (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

• Lauri Sokk (Tark 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 Linnavalitsus): Tartu Smart Bike Share – how and what do we see?

Seminari salvestist saab järele vaadata siit.

Moderaator: Meelis Kull (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

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

Seminari salvestist saab järele vaadata siit.

Moderaator: Sherif Sakr (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

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

Seminari salvestist saab järele vaadata siit.

Moderaator: Amnir Hadachi (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

• 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

Seminari salvestist saab järele vaadata siit.

Moderaator: Leopold Parts (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

• Krista Fischer (TÜ, Geenivaramu): 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 (TÜ, Geenivaramu): 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

 Seminari salvestist saab järele vaadata siit.

Moderaator: Mark Fišel (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

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

Seminari salvestist saab järele vaadata siit.

Moderaator: Leopold Parts (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

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

Seminari salvestist saab järele vaadata siit. 

Moderaator: Tambet Matiisen (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

• Raivo Sell (TalTech): 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 (videoülekanne)

Seminari salvestist saab järele vaadata siit.

Moderaator: Dmytro Fishman (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

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

Seminari salvestist saab järele vaadata siit. 

Moderaator: Raul Vicente (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

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

Seminari salvestist saab järele vaadata siit.

Moderaator: Meelis Kull (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

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

Seminari salvestist saab järele vaadata siit.

Moderaator: Leopold Parts (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

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

Moderaator: Leopold Parts (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

• Jaak Vilo (TÜ arvutiteaduse instituut): Data for Health
• Eneli Oitmaa (Asper Biotech): Applying Bioinformatics Analysis in the Genetic Laboratory Settings
• Dmytro Fishman (TÜ arvutiteaduse instituut): Deep Learning in Health Care
• Lili Milani (Eesti Geenivaramu): Electronic Health Records and Genomes for Research

Seminari salvestist saab järele vaadata siit.

Moderaator: Kristjan Eljand (STACC)

Esinejad ja ettekanded:

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

Seminari salvestist saab järele vaadata siit. 

Moderaator: Leopold Parts (TÜ arvutiteaduse instituut)

Esinejad ja ettekanded:

• Leopold Parts (TÜ arvutiteaduse instituut): Sissejuhatus
• Raul Vicente (TÜ arvutiteaduse instituut): Machine Learning in the Lab
• André Karpištšenko (Proekspert, PlanetOS): Machine Learning in Production
• Vladimir Šor (Plumbr): Java Performance Monitoring at Plumbr
• Mark Fišel (TÜ arvutiteaduse instituut): Natural language Processing
• Taavi Tammiste (Mooncascade): Finding Real World Use-cases for Data Science
• Amnir Hadachi (TÜ arvutiteaduse instituut): Urban Sensing: From Mobility to Localization