Conferences / PyCon (national Python conferences)
PyCon Lithuania 2025
Apr 22–26, 2025 · SMK University of Applied Social Sciences, Vilnius, Lithuania
- Conference
- PyCon (national Python conferences) Data science & ML
- Dates
- Apr 22, 2025 – Apr 26, 2025
- Venue
- SMK University of Applied Social Sciences
- Place
- Vilnius, Lithuania
- Format
- In person
- Status
- Past
- Attendance
- —
- Website
- pycon.lt
- Recorded
- 17 sponsors · 70 speaker appearances
- Notes
- Main conference 23-25 Apr: Python Day, Data Day (dataframes, databases, orchestration) and AI/ML Day; pretalx event spans 22-26 Apr (pycon.lt history: 23-26 Apr). Keynotes include Gabor Szarnyas (DuckDB Labs) on Data Day. Speakers: all sessions with speakers from the pretalx schedule export (logistics slots such as welcomes, lightning-talk blocks, AGMs and sprints left out); affiliations parsed from pretalx bios where stated, otherwise null.
Ticket prices
| Ticket | Price | Valid until | Notes | Source |
|---|---|---|---|---|
| Individual, 3 days | €139 | — | incl. 21% VAT; 2 days €109; 1 day €76 | web.archive.org |
| Company, 3 days | €199 | — | incl. 21% VAT; 2 days €166; 1 day €119 | web.archive.org |
Sponsors 17
Speakers and talks 70
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Aurimas Griciunas | neptune.ai | Keynote | Challenges and Opportunities of Agentic Systems: Present and Future | — |
| Brandon Rhodes | — | Keynote | Skip the Design Patterns: Architecting with Nouns and Verbs | — |
| Gabor Szarnyas | DuckDB Labs | Keynote | The evolution of data management techniques | — |
| Kushal Das | — | Keynote | Ethics, Privacy and few other words | — |
| Merve Noyan | — | Keynote | Open-source Multimodal AI | — |
| Stefanie Molin | Bloomberg | Keynote | Build Your Own (Simple) Static Code Analyzer | — |
| Aleksejs Vesjolijs | Accenture | Talk | EGTL data-processing model prototype using Python | — |
| Alius Petraška | IBM | Talk | How We Outperformed Microsoft, Google, and OpenAI in Speech-to-Text | — |
| Andrii Soldatenko | — | Talk | Code review the right way | — |
| Antanas Baltrušaitis | Nordea | Talk | Leveraging Large Language Models for Automated Generation and Validation of Financial Descriptions for Lithuanian Companies | — |
| Antanas Daujotis | — | Talk | Code Generation in Regulated Industries: Opportunities and Challenges | — |
| Antonis Kalipetis | Platform.sh | Talk | Sync or async? Feel the magic of coroutines and the event loop in Django | — |
| Anwesha Das | — | Talk | Using Trusted Publishing to Ansible release | — |
| Ąžuolas Krušna | — | Talk | How I tracked my stocks with Python | — |
| Christian Heitzmann | — | Workshop | What We Can Learn from Exemplary Python Documentation | — |
| Christophe Bornet | — | Talk | Building multi-agent AI applications made easy with LangFlow | — |
| Daniel Hervás | Reckon Digital | Talk | Python Containers: Best Practices | — |
| Daniel Hervás | Reckon Digital | Talk | Inside the Black Box: The Anatomy of Virtual Environments | — |
| Daria Lashkevich | — | Talk | GenAI for Clients: No pain, no gain | — |
| Davi Nascimento de Paula | — | Talk | Transforming REST APIs with Protobuf: Unlocking Performance and Flexibility | — |
| David Andersson | — | Talk | I want to deploy my Flask app on Kubernetes, what are my options? | — |
| David Batista | — | Talk | Smarter Retrieval, Better Generation: Improving RAG Systems | — |
| David Masip | Glovo | Talk | cluster-experiments: A Python library for end-to-end A/B testing workflows | — |
| Donatas Rasiukevičius | — | Talk | Do Repeat Yourself | — |
| Ed Crewe | EDB | Talk | Cutting the price of Scraping Cloud Costs | — |
| Evaldas Kazlauskis | Vinted | Talk | When safety is non-negotiable - 3 stages of building safety using data & AI | — |
| Florian Stefan | — | Talk | Testable data pipelines | — |
| Florian Stefan | — | Talk | Accelerating privacy-enhancing data processing | — |
| Gediminas Sadaunykas | — | Talk | Pydantic: Crafting confidence in AI apps | — |
| Hanna Danilovich | Revolut | Talk | From Raw Transactions to Insights: The Power of Embeddings in Fintech | — |
| James Donahue | — | Talk | Variable Selection: What your model can't tell you | — |
| Javier de la Puente | Canonical | Talk | I want to deploy my Flask app on Kubernetes, what are my options? | — |
| Jonas Jarutis | — | Talk | Image deduplication using embeddings | — |
| Jurgis Zagorskas | — | Talk | Python in 3D computer graphics | — |
| Laurynas Stašys | — | Workshop | Using feature stores to deliver awesome models | — |
| Ludvig Wärnberg Gerdin | Isomorphic Labs | Talk | Automate Brag Document Writing with LLMs | — |
| Mantas Cepulkovskis | Cast AI | Workshop | Using feature stores to deliver awesome models | — |
| Mark Fukson | Revolut | Talk | Beyond Deployment: Continuously Adding Features to Drive Marginal Gains in Models | — |
| Matej Hamaš | Apify | Workshop | Build, Deploy, Monetize: The Future of the Developer Economy | — |
| Mauro Pelucchi | Lightcast | Talk | Data Warehouses Meet Data Lakes | — |
| Maxim Danilov | — | Workshop | Building pure Django REST API | — |
| Maxim Danilov | — | Talk | The art of yield | — |
| Maximilian Lattka | UL Solutions | Talk | Working for a Faster World: Accelerating Data Science with Less Resources | — |
| Megan Robertson | — | Talk | Top 5 Lessons from a Senior Data Scientist | — |
| Patricia Goldberg | — | Talk | From Chaos to Control: Automating BI Tools with Pydantic and Python | — |
| Patricia Goldberg | — | Talk | Organize your data stack using Dagster | — |
| Pietro Peterlongo | AgileLab | Talk | A Crash course in Time Series Forecasting from Naive to Foundational | — |
| Piotr Gryko | University College London | Talk | Anonymization of sensitive information in financial documents using, python, diffusion models and named entity recognition | — |
| piotr stepinski | Infinitii ai | Talk | 📂 Slow Productivity AI: Automating Knowledge & Task Management with Offline Hugging Face, n8n & Obsidian | — |
| Piti Champeethong | MongoDB | Talk | Migrating billions records from SQL to NoSQL using continuous migration technique with PySpark and DataProc. | — |
| Robert Dzisevič | IBM | Talk | The Emergence of Agentic Workflows in AI | — |
| Ruslan Korniichuk | — | Talk | Temporal: Bulletproof Workflows | — |
| Ruslan Korniichuk | — | Talk | Architecture as Code (AaC) with Python | — |
| Ruslan Korniichuk | — | Talk | Python on the Pitch: How Germany will win World Cup 2026 | — |
| Ruslan Korniichuk | — | Workshop | Investing: Technical Analysis libraries in Python | — |
| Sadeeq Akintola | Workshop | Orchestrating an end-to-end Data Engineering Workflow: Leveraging Python in Apache Beam and Airflow | — | |
| Sebastian Krauss | Bosch | Talk | How to evaluate fairness and safety in LLM applications? | — |
| Shiva Bhusal | — | Talk | Coding Aesthetics: PEP 8, Existing Conventions, and Beyond | — |
| Siddharth Gupta | University of Potsdam | Talk | Surprisal and the headache of tokenizer encodings in LLMs! | — |
| Siddharth Gupta | University of Potsdam | Workshop | Build & Deploy Apps like a (pro) Data Scientist using Streamlit | — |
| Stefan Dayneko | — | Talk | AI 360: From Theory to Transformation | — |
| Stefan Kraus | UL Solutions | Talk | Let the Robots Test: Acceptance Test-Driven Development (ATDD) with Robot Framework | — |
| Taisija Kozarina | — | Talk | Unlocking the Power of Python and PyTorch for Biomedical Image Segmentation | — |
| Tomas Peluritis | — | Talk | Beyond dbt: Modern SQL Transformation and Lineage with sqlglot and sqlmesh | — |
| Tuana Çelik | Weaviate | Talk | Knowledge Bases & Memory for Agentic AI | — |
| Tung Hoang | — | Talk | Real-Time Data Analytics at Scale: From Ingestion to Retrieval | — |
| Vidmantė Čižienė | — | Talk | The Power of Python for Data Management (or How You’ve Been Doing Data Management All Along Without Even Realizing It) | — |
| Viraj Sharma | — | Talk | Enhancing Model Context Protocol (MCP) with Dynamic Tool Discovery for Smarter AI | — |
| Vladas Tamošaitis | EPAM | Talk | Beyond the GIL: Python's Evolution and Future Directions | — |
| Zafarzhon Irismetov | Accenture | Talk | The Best of Both Worlds: A Hybrid Approach to Lightning-Fast Product Matching | — |