Exposing Greenwashing: Satellite ML for Carbon Credit Verification

Neeraj Pandey

The carbon market is set to reach 1T dollars by 2030, yet 84% of offsets fail to deliver real climate benefits. Verification still relies on sparse site visits and self-reported data. This poster show...

Leading Through the Shift: What Engineering Leadership Actually Looks Like

Justinas Kuizinas, Aurimas Griciunas, Karolina Griciunė, Tomas Peluritis

Building great engineering teams has never been straightforward — but the rules keep changing. Three back-to-back panel discussions with CTOs and engineering leaders covering the full spectrum: scalin...

Stats Meets ML - What I learned from my Machine Learning Certification

James Donahue

Statisticians and machine learning specialists have a lot to learn from each other (even if they don't think so). This talk lightheartedly awards points to both classical statistics and machine learni...

Python for Data Quality in 2025: Why tests alone are no longer enough

Artsem

In 2025, classic data tests via Python are not enough. During 25-30 minutes talk I will show how Python powers modern Data Quality: from real-time freshness checks to anomaly detection and orchestrato...

From Sports Stats to AI Safety: The Ranking Renaissance

Gediminas Sadaunykas

In 1952, two statisticians proposed a simple model for comparing sports teams. In 1960, it became the foundation of chess ratings. Today, that same math powers everything from ChatGPT's alignment ...

Beyond the Static 2D Plot - Spatial Data Storytelling in 4D

Kęstutis Gadeikis

2D static plots are great, but they are static. Data isn't - it changes. So we turn a plot into an animation. But we don't live in planes - we live in space. And we want to send a message, not just sh...

Cloud Data Solutions Are Overrated: Building a Pan-European Business Database for Lunch Money

Antanas Baltrušaitis

We are told that modern data engineering requires expensive cloud warehouses and enterprise SaaS. This talk challenges that narrative. I will show how I built scoris.eu - aggregating business data fro...

Data versioning

Federico Marchesi

One of the core fundamental pieces of technology every software-related tech stack is heavily dependent on is Git. The ability to version code and control the flow of development is the only common fo...

Python, rust and arrow for data processing

Paulius Venclovas

Python struggles with heavy data loads. Rust offers speed, and PyO3 makes bridging the two seamless. This talk shows how to build a shared Rust core to avoid code duplication. I will also cover using ...

Creative Data Storytelling with Python

Purva

Python enables data professionals to move beyond analysis and transform information into clear, compelling stories. With various libraries, Python supports insightful exploration, expressive visualiza...

Lightning Talks

TBD

Master the Art of Schema Dissection: Operation Data Engineer

Antonino (Nino) Cangialosi

Have you ever faced an enormous, wide table? Sometimes you need to cope with it because it's faster in this form, and that's what your stakeholders need. Anyway, it’s hiding entities, metrics, and tim...

Airflow Lessons They Don't Put in the Docs

Tomas Peluritis

Airflow basics are well documented. Production Airflow is not. This talk covers the patterns, costs, and migration pitfalls that only show up after you've deployed: dynamic DAGs that scale, sensors th...

Quantum Machine Learning with Qiskit

Jonas Adomaitis

Unlock the power of Quantum Machine Learning (QML) with Python and Qiskit. You will explore the distinctions between classical and quantum machine learning and gain an understanding of data encoding, ...

How I mapped 10 000 illegal Airbnbs with Python

Juan Luis Cano Rodríguez

In the spring of 2024, a cry erupted across Spain: "The Canary Islands have reached their limit." Soon, massive demonstrations followed in other regions facing similar tensions: "Mallorca is not for s...

Designing Python APIs for Data You Don’t Control

Saurav Jain

The web isn’t an API, but Python developers often treat it like one. This talk explores how to design Python interfaces for unstable data sources, focusing on schema evolution, defensive parsing, and ...

Multi-Model LLM Orchestration in Python: A Case Study in Research Automation

Mauro Pelucchi

How do you turn thousands of PDFs into actionable insights? This talk shows how we built a Python-based AI assistant using LLMs and RAG to automate literature reviews: covering architecture, trade-of...

Beyond SHAP: Diagnosing Vector Embeddings with Visual Explainable AI

Valdas Druskinis

When your embedding-based classification model fails, should you collect more data or try a different approach? This talk shares a practical XAI workflow using UMAP visualization and prototype analysi...

Dataset Updates Without Losing Your Mind

Oleksii Liashuk

Many teams work with datasets that evolve over time. What starts as simple setup, quickly turns into chaos once updates become regular. In this talk, I share a practical workflow for managing dataset ...

And now for something completely different

Rodrigo Girão Serrão

In this talk we’ll go over two quintessential features of Python programming (generators and duck typing) and you’ll learn how to use them effectively. We’ll also look at branchless conditionals an...

Behind Every Instant Loan Is Data Science: How Python Scorecards Decide Credit Risk

Zafarzhon Irismetov

Modern digital lending demands instant decisions, and behind those decisions is a Data Science workflow powered by scorecard. This talk explains how scorecards calculates credit risk in a transparent ...