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.
Future seminars
Past seminars
The Data Science Seminar "AI for SE: Do you have the right vibe?" took place place as a sTARTUp Day 2026 side-event on 28 January at 16:15 at the Delta study building lecture hall 1037.
The seminar explores how the quickly evolving availability of GenAI tools helps to analyse and improve the quality of software applications, no matter whether these applications have been developed manually, generated with the help of GenAI tools like GitHub Copilot, Gemini, or ChatGPT (to name just a few), or are a hybrid of both.
Special focus is set on discussing opportunities and challenges related to AI-supported code analysis, and AI-generated test code and test data. The goal of the seminar is to showcase the state-of-practice in the Estonian industry as well as to understand how academia can be of help to industry by adjusting its teaching and connecting its research to the needs of the companies and government agencies.
Schedule:
15.45 Gathering and welcome coffee
16.15 Opening words from Professor of Software Engineering Dietmar Pfahl.
16.25 Chief Government Technology Officer at Nortal Priit Liivak, "You need to work to make AI work"
16.45 Data Scientist at Swedbank Artem Mateush, "Spare Tire or Steering Wheel? How GenAI Fits — and Transforms — Software Team Culture"
17.05 Associate Professor in Informatics at the University of Tartu Institute of Computer Science Marina Lepp, "The Learning Vibe with AI: How Students Perceive, Use, and Perform in Programming"
17.30 Coffee break
18.00 Hanna Tagen, Head of Software Engineering at IndiGO Technologies
18.20 Toomas Römer, VP of Engineering at Bolt
18.40 Panel discussion
19.00 Networking
The academic organiser of this event is Professor of Software Engineering Dietmar Pfahl.
Data Science Seminar "Autonomy Fabric for AI-Driven Operations" takes place 11 December at the University of Tartu Delta study building auditorium 1037. The seminar starts at 16:15 with welcome coffee being served from 15:45.
December’s Data Science Seminar will highlight an important aspect in the era of AI, autonomy fabric, which is more than a tech stack. It is the operating layer of the physical world.
By tightly integrating sensing, AI, and automation across edge and cloud, it transforms today’s fragmented systems into coordinated, real-time operations. The shift is transformational: organisations move from reactive workflows to predictive, and ultimately autonomous, services that are safer, faster, and more sustainable.
This edition of Data Science Seminars examines how to design that layer: streaming perception from cameras and sensors, running low-latency models at the edge, synchronising decisions across fleets and infrastructure, and closing the loop to actuators and business systems.
Schedule:
15:45–16:15 Gathering and welcome coffee
16:15 Opening words from Amnir Hadachi, Associate Professor of Smart City Technologies
16:25 Olena Chornovol, CEO and co-founder of GaiaHub
16:45 Huber Flores, Associate Professor of Pervasive Computing at the University of Tartu Institute of Computer Science
17:05 Eric Grono, Lead Data Analyst at Veriff
17:25– 17:55 Coffee break
17:55 Agustin Zuniga, Postdoctoral researcher at the University of Helsinki
18:15 Jakob Mass, Research Engineer at IndiGO
18:35 Panel discussion led by Amnir Hadachi
18:55 Networking
The organisers of this event are Associate Professor of Smart City Technologies Amnir Hadachi and Associate Professor of Pervasive Computing Huber Flores.
The seminar "Data Science & AI: research, practice, and education" took place 2 October during Tallinn Data Week 2025. Event goers were able to hear about approaches taken by companies, as well as collaboration and education opportunities offered by the university.
Agenda
16:30 Gathering and welcome coffee
17:00 “Data Science and AI @UniTartuCS”
Jaak Vilo, University of Tartu Institute of Computer Science, Head of Chair of Data Science
17:20 “How to be successful with AI?”
Kristjan Jansons, MindTitan, Co-founder and CEO
17:40 “Data Science at SEB”
Stefano Ciaci, SEB, Data Scientist
18:00 “From Competitions to Business Impact: Becoming a GenAI Engineer"
Kea Kohv, Telia, GenAI Engineer
18:20 Break
18:40 “Sanctions and AI: Balancing Opportunity and Responsibility”
Kadri Pirn, Salv, VP of Screening and Monitoring Business Unit
19:00 “Data and skills in the age of AI”
Meelis Kull, University of Tartu Institute of Computer Science, Professor of Artificial Intelligence
19:20 Panel discussion
20:00 Networking
This event was supported by the Ministry of Education and Research Centres of Excellence grant TK213 Estonian Centre of Excellence in Artificial Intelligence (EXAI).
The Data Science Seminar "Decoding Humans: How Data Drives Human-Centric Solutions" explores how the evolving data landscape is reshaping product design and user experience. It examines how emerging data technologies are enabling the creation of more insightful, responsive, and truly human-centered solutions — and what new approaches and ways of thinking they are beginning to inspire.
Speakers:
- Agne Kinks, Director of Product Intelligence at Pipedrive, "Customer-Centric Innovation: Pipedrive’s Data-Driven Product Strategy"
- Grace Eden, Associate Professor of Interaction Design at the University of Tartu Institute of Computer Science, "Quantified Life: the datafication of human activities in a data-driven world"
- Hegle Sarapuu-Johanson, Chief Innovation Officer at Trinidad Wiseman, "From Clicks to Clarity: How Usability Metrics Make Digital Products More Human-Centric"
- Kristel Ots, UX/UI Designer at Illuminare OÜ, "How data shaped app design: a journey toward human-centered design"
- Elisabeth Raidma, Head of UX/UI at Bitweb, "Good UX Starts With Lies (aka Mock Data)"
The event is led and moderated by Kuldar Taveter, Professor in Information Systems at the University of Tartu.
Language models, such as Le Chat, EuroLLM, Llama, and ChatGPT, have turned the world of artificial intelligence on its head and are increasingly influencing the rest of the world. But they mostly process and generate only text.
The seminar "Text and What Next? AI Across Diverse Data Types" explored AI applications beyond purely textual data. For example: how successfully can AI automatically recognise and produce sign language? How far have we come in understanding speech? Could visual input, combined with language comprehension help robots navigate and behave in ways that make them genuinely useful? The event was led by Mark Fišel, Professor of Natural Language Processing at the University of Tartu Institute of Computer Science.
Speakers:
Amit Moryossef, Chief Technology Officer at sign.mt, "No Barriers, No Limits: The Future of Sign Language AI"
Joonas Kalda, PhD student at TalTech, "Towards understanding multi-talker speech"
Joonas Puura, Senior Machine Learning Engineer at Bolt, "Lessons from Automating Customer Support with LLMs at Bolt"
Risto Hinno, Data analyst and software developer at Feelingstream, "Lost in transcription"
Agnes Luhtaru, Visiting research scholar at the University of Texas at Austin, "Robots Facing an Ambiguous World"
The Data Science Seminar is supported by the Ministry of Education and Research Centres of Excellence grant TK213 (Estonian Centre of Excellence in Artificial Intelligence (EXAI)).
The Data Science Seminar "Triple-Helix Collaboration on Data" was an official side-event of sTARTUp Day 2025 and focused on the synergy between academia, industry, and government known as the "triple-helix" model.
Speakers:
- Ott Velsberg, Head of Artificial Intelligence and Data Service at the Ministry of Justice and Digital Affairs, "Government perspective on collaboration with academia and industry: Achieving the goals of the data and AI strategy"
Märt Ridala, CEO of Solita, ”Why companies sometimes spend time and money on co-operation with the universities and the state”
Kaido Paabusk, Statistics Estonia, Deputy Director General, "The role of Statistics Estonia in triple-helix: experience so far and unused potential"
Priit Kongo, CEO of NetGroup, "AI for Mental Health: A Collaborative Model between Net Group, Heba Clinic and University of Tartu"
Jaak Vilo, Head of the Chair of Data Science at the University of Tartu, "Collaboration models and opportunities"
Elena Sügis and Ardi Tampuu introduced the new data science textbook "Praktiline andmeteadus"
The Data Science Seminar is supported by the by the Ministry of Education and Research Centres of Excellence grant TK213 (Estonian Centre of Excellence in Artificial Intelligence (EXAI)).
The UT Institute of Computer Science and the Estonian Scientific Computing Infrastructure (ETAIS) introduced the exciting world of supercomputers, high-performance computing, and their possible uses.
High-performance computing allows researchers to solve the most complex challenges quickly and even explore areas where experiments are unthinkable. Successful companies apply supercomputers for innovative R&D activities, cost reduction, and competitive advantage. At the seminar, we heard inspiring presentations about how experts in various fields use supercomputers and what benefits they can get from it.
Speakers
Opening remarks by Ivar Koppel, Head of UT High Performance Computing Centre & Leading partner of Estonian Scientific Computing Infrastructure ETAIS, "ETAIS: Pioneering the Future of Technology and Innovation"
Rainer Türner, IT Architect of Bürokratt at the Estonian Information System Authority, “How Real-Time Government Data Will Disrupt AI Investments"
Priit Paluoja, Head of Data Management at Celvia CC, “Honey bulk DNA metagenomic analysis using University of Tartu High Performance Computing Centre”
Alena Kushniarevich, Researcher at the UT Institute of Genomics Estonian Biocentre, “Interdisciplinary studies of human past: a genomic data perspective”
Taido Purason, Junior Research Fellow at the UT Institute of Computer Science, “Training and Applying LLMs on LUMI Supercomputer”
Hardi Hakk, Head of Aerodynamics at Formula Student Team, “HPC usage in engineering practices for Formula Student”
The event was moderated by Martin Eessalu, Advisor at the UT High Performance Computing Centre.
Video recording of the seminar
Photo gallery from the seminar
The UT High Performance Computing Center is part of the Estonian Computing Infrastructure (ETAIS). The ETAIS consortium consists of the University of Tartu, Tallinn University of Technology, National Institute of Chemical Physics and Biophysics, and the Ministry of Education and Research.
The UT Institute of Computer Science and EXAI: Estonian Centre of Excellence in Artificial Intelligence hosted a Data Science Seminar on the topic of AI!
AI achieves impressive results, but the path to success is often not straightforward. How do we decide where and how AI should be applied, and what technical challenges arise along the way? At this seminar, several AI researchers and industry experts will present their insights and experiences.
Speakers:
Tanel Alumäe, Tallinn University of Technology, "Weakly supervised learning for training speaker identification models"
Paula Etti, Cybernetica AS, "The Role of Synthetic Data in AI Systems"
Kristjan Eljand, Andmeteadus OÜ, “How Estonian companies have implemented AI: Practical use cases from 2023-2024 projects“
Martti Praks, LHV, "AI in LHV"
Elena Sügis, University of Tartu, Nortal AS, "Think Tark! Leverage Retrieval-Augmented Generation for Enterprise Data."
Dmytro Fishman, University of Tartu, Better Medicine OÜ, "BetterMedicine: using AI to improve cancer diagnostics"
Meelis Kull, Associate Professor at the University of Tartu Institute of Computer Science and Head of the Estonian Centre of Excellence in Artificial Intelligence, moderated the event.
The seminar was supported by the Estonian Centre of Excellence in Artificial Intelligence (EXAI), financed by the Ministry of Education and Research. The members of the Estonian Centre of Excellence in Artificial Intelligence are the University of Tartu, Tallinn University of Technology, and Cybernetica AS.
Culture and Data was dedicated to Estonian culture data, what it looks like, how it is produced, and how it can be used. The seminar took place in Estonian.
Speakers:
- Indrek Ibrus
- Mari Sarv
- Anna Aljanaki
- Vahur Puik
- Jaan Naaber
On 19 March, we hosted a Data Science Seminar titled "Secondary use of health data in Estonia". The event was organised and moderated by Head of Chair of Data Science Jaak Vilo.
Modern medicine requires using all possible data to create insights and evidence about diseases and treatments. Secondary use of real world data (RWD) for evidence generation is needed and gaining traction. Our seminar will cover the aspects of secondary use of health data, the strategic plans in Estonia and Europe, research use cases for academic and private sector alike.
Speakers:
- Jaanika Merilo - Ministry of Social Affairs, Head of eHealth Strategy
- Liisa Loog - Metrosert, Head of Health Data
- Raivo Kolde - Assoc. Prof. of Health Informatics, University of Tartu
- Lenne-Triin Kõrgvee - MD, PhD, Cancer Centre, director, Tartu University Hospital
- Peter Rijnbeek - Prof., Chair of the Department of Medical Informatics of the Erasmus MC, The Netherlands
The event was supported by the Center of Excellence in Artificial Intelligence (EXAI), financed by the Ministry of Education and Research.
We hosted a Data Science Seminar titled Trustworthy and Responsible AI.
As recognized by all economic and regulatory frameworks, with a primary emphasis on the EU but also encompassing the US and China, artificial intelligence (AI) stands out as the pivotal focus for developing a trustworthy technology. New regulatory requirements to make AI trustworthy and responsible are transforming the role that humans play when interacting with AI, and consequently, AI is now not just creating new opportunities and markets, but it is doing it while preserving fundamental rights and liberties of individuals.
The academic organiser of the seminar was Huber Flores, the moderators were Abdul-Rasheed Ottun and M.M. Rasinthe Marasinghe.
Speakers
- Huber Flores, Associate Professor, University of Tartu, Estonia
- Michell Boerger, Research scientist, Fraunhofer Institute for Open Communications Systems FOKUS, Germany
- Sonia Sousa, Associate Professor, Tallinn University/Tallinn University of Technology, Estonia
- Manh Nguyen, Research Engineer, Montimage, France
- David Solans, Research scientist, Telefonica Research I + D, Spain
- Bart Siniarski, Senior researcher, UCD, Ireland
The seminar was partly supported by the European Union Horizon 2020 research and innovation programme under grant agreement No 101021808.
The Data Science Seminar took place as part of sTARTUp Day 2024. The event wass organised and moderated by Assoc. Prof. Jaan Aru from the UT Institute of Computer Science.
Big data and artificial intelligence will change education. But what kind of changes do we need? The event brings together the government side, academia and the EdTech sector. We will see what data is available, how EdTech companies are handling their data and what can artificial intelligence add.
The event also highlights that future education is not only about schools and universities, but also more and more about life-long learning.
Speakers:
- Margus Püüa, Head of the Personalised Learning Path initiative, TalTech
- Kairit Tammets, Professor of technology-enhanced learning, Tallinn University
- Kristjan-Julius Laak, University of Tartu
- Margus Pedaste, Professor of educational technology, University of Tartu
- Triin Kask, Founder and CEO of Metatellus
- Kadri Tuisk, Founder and CEO of Clanbeat and Sage OS
The topic of the seminar was Smart Sustainable Mobility and Communities. The seminar was organised and moderated by Assoc. Prof. Amnir Hadachi, Head of Chair of Distributed Systems at the Institute of Computer Science.
It featured the following speakers:
- Age Poom, Head of Mobility Lab and Associate Professor in Urban Environment, University of Tartu, Institute of Human Geography, “How can spatial data science support healthy and sustainable urban mobility?”
- Taavi Tammiste, Co-Founder & CTO of Fyma, “Practical usage of computer vision data in physical spaces”
- Peeter Vassiljev, Lecturer in Social Geography, Estonian University of Life Sciences, "How do Landscape Architects collect park usage data?"
- Naveed Muhammad, Associate Professor of Autonomous Driving, University of Tartu, Institute of Computer Science, "Autonomous driving: developments and challenges"
- Andres Sevtšuk, Head of the City Design and Development Group and Associate professor of Urban Science and Planning, Massachusetts Institute of Technology (MIT), "NYC Walks: A model of sidewalk-level pedestrian mobility for peak traffic periods."
The seminar focused on minimizing climate change through hi-tech solutions, accurate data collection and management, the advantage of optimized complicated energy systems, and getting the maximum benefits out of afforestation. The programme was curated by Prof. Jaak Vilo.
We will had the following distinguished speakers from the University and industry:
- Aveliina Helm, Professor of Restoration Ecology, University of Tartu, Institute of Ecology and Earth Sciences, “Data for nature conservation and restoration: new tools and opportunities“
- Kalev Pärna, Professor Emeritus, University of Tartu, Institute of Mathematics and Statistics, ”Uncertainty estimation in Estonian forest inventory”
- Kristjan Lepik, CEO & Co-Founder of Arbonics, “The new forest economy“
- Tauri Tampuu, Research and development manager, SAR expert, and Kaupo Voormansik, SAR expert, CEO of KappaZeta Ltd, "Wonderful Radar – Rich View Through Clouds"
- Kirill Grjaznov, Data Scientist, and Arko Kesküla, Data Scientist, STACC, "Personalized optimization in electric power system"
- Huber Flores, Associate Professor of Pervasive Computing, University of Tartu, Institute of Computer Science, "Low-cost sensing for environmental sustainability”
The IT Academy Research Summit was a two-day event packed with highlight talks, poster sessions, free discussions, and speed-dating opportunities. You can watch here the recording of the plenary sessions.
- Recording of Day 1
- Prof Jaak Vilo, Introduction, overview, and impact of the ITA programme
- Assoc Prof Jaan Aru, Natural and Artificial Intelligence Lab
- Assoc Prof Huber Flores, Distributed and Pervasive Systems Group
- Assoc Prof Raivo Kolde, Health Informatics Group
- Research Fellow Arnis Paršovs, Applied Cyber Security Group
- Recording of Day 2
- Assoc Prof Arun Kumar Singh, Collaborative Robotics and Robotic Computing Group
- Assoc Prof Eduard Ševtšenko, Digital Supply Chain Group
- Assoc Prof Naveed Muhammad, Autonomous Driving Group
- Mart Toots, Enterprise Estonia, formerly also ITL R&D Manager
- Dan Bogdanov, PhD, Cybernetica, Chief Scientific Officer, ITA Scientific Advisory Board member.
- Prof Petteri Nurmi, University of Helsinki, ITA Scientific Advisory Board member.
The seminar was moderated by Prof. Jaak Vilo. The event featured the following speakers:
- Liron Friend-Saadon, NVIDIA, Director of Developer Relations
- Kairit Sirts, University of Tartu, Associate Professor
- Zenodia Charpy, NVIDIA, Senior Deep Learning Data Scientist
- Fabian Weiss, NVIDIA, Senior Deep Learning SW Engineer
- Omar Ahmad, University of Iowa, Deputy Director, Driving Safety Research Institute
- Tambet Matiisen, University of Tartu Autonomous Driving Lab Lead Engineer
The seminar recording can be found here. The photos are available
The seminar was moderated by Marlon Dumas. The seminar featured the following speakers:
- Mohamad Gharib (UT) - Data/Information Quality Requirements– What is it and Why Does it Matter?
- Anastasija Nikiforova (UT) - Data lake or data warehouse? Data cleaning or data wrangling? How to ensure the quality of your data?
- Jürgen Koitsalu (Chief Product Owner, Swedbank Group Business Intelligence Product Management & Agile Guild)
- Igor Artemtšuk (Architect, Swedbank Group Business Intelligence Architecture Guild)
You can find the seminar recording here.
The seminar featured the following speakers:
- Taavi Tillmann, University of Tartu, Integrating big health and social data, to better predict heart attacks, and reduce its socioeconomic inequality.
- Abdulrahman Azab, University of Oslo, Towards federation of cross-border sensitive data access and processing
- Liina Kamm, Cybernetica AS, Is usable privacy-preserving data analysis an oxymoron?
- Raivo Kolde, University of Tartu, Adopting common data model for Estonian health data
- Stefan Negru, CSC, Finland, Developing Technologies And Standards for Enabling Sensitive Data Archiving, Sharing and Reuse
You can find the seminar recording here.
The speaker Raivo Kolde has been supported by European Social Fund via „ICT programme“ measure.
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:
- Dmytro Fishman, University of Tartu, Lecturer of Artificial Intelligence - Biomedical segmentation: holy grail and remaining mysteries
- Tanya Shtym, KappaZeta, Machine Learning Engineer - KappaMask: AI-Based Cloud Mask Processor for Sentinel 2
- Markus Kängsepp, University of Tartu, Autonomous Driving Lab, Junior Research Fellow - Calibration of Bird's-Eye-View Semantic Segmentation
- Kaupo Voormansik, KappaZeta, CEO - Data Science and Machine Learning in KappaZeta
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:
- Meelis Kull, Associate Professor in Machine Learning at UniTartuCS: Understanding the decisions of an AI system
- Radwa El Shawi, Associate Professor of Big Data at UniTartuCS: Towards automatic concept-based explanations
- Luca Traverso, Data Science Lead at Wise: Building robust and defensible machine learning systems in Fincrime
- Rain Vagel, Data Scientist at Wise: Why did the model decide X?
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:
- 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
You can find the seminar recording here.
Moderator: Ülar Allas from High Performance Computing Center of UniTartu
Speakers and presentations:
- Ott Oopkaup (UniTartu, High Performance Computing Center): High performance computing: A look into how large-scale data storage and processing is done
- Reedik Mägi (UniTartu, Estonian Genome Centre): Computational challenges in genomics: association studies, genetic risk scores and AI
- Kaur Alasoo (UniTartu, Institute of Computer Science): Automating the processing of terabyte-scale data with software containers and workflow engines
- Velle Toll (UniTartu, Institute of Physics): HPC for weather, climate and Earth system prediction
- Pekka Manninen (LUMI supercomputing facility): LUMI: the European flagship supercomputer of the North
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:
- Leopold Parts (UniTartu ICS): Introduction
- Raul Vicente (UniTartu ICS): Machine Learning in the Lab
- André Karpištšenko (Proekspert, PlanetOS): Machine Learning in Production
- Vladimir Šor (Plumbr): Java Performance Monitoring at Plumbr
- Mark Fišel (UniTartu ICS): Natural language Processing
- Taavi Tammiste (Mooncascade): Finding Real World Use-cases for Data Science
- Amnir Hadachi (UniTartu ICS): Urban Sensing: From Mobility to Localization
