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Confirmed Talks

Barr Moses

CEO & Co-Founder of Data/Analytics startup backed by top Silicon Valley investors

USA, Monte Carlo

Making Data Downtime a Pillar of Your Data Strategy

Barr will introduce the concept of “data downtime” — periods of time when data is partial, erroneous, missing or otherwise inaccurate. Data downtime is highly costly for organizations, yet is often addressed ad hoc. She’ll discuss why data downtime matters to the data industry and tactics best-in-class organizations use to address it — including org structure, culture, and technology.

Session Keywords
🔑 Data Reliability
🔑 Data Quality
🔑 Data Strategy

Yiannis Kanellopoulos

Technology Startup Founder

Greece, Code4Thought

Trust and Quality in the Era of Software 2.0

In his talk Yiannis Kanellopoulos will present an approach on how an ML model can be evaluated in terms of its Fairness, Accountability and Transparency. Using examples of case studies (from industrial and publicly available datasets) Yiannis will share insights and the benefits one can get by making a ML model accountable, transparent and trying to mitigate its biases.

Session Keywords
🔑 AI Accountability
🔑 AI Fairness
🔑 AI Transparency

Kane Wu

Co-Founder and CEO

Hong Kong, ThinkCol

Data Science Case Studies and Formulation of AI Roadmap

From discussing what is AI to practical case studies of AI, Kane will discuss how companies in Hong Kong and world wide uses AI to create business values.

Session Keywords
🔑 Machine Learning
🔑 Data Science

Verdan Mahmood

Senior Software Engineer

The Netherlands, ING Bank

Towards Enterprise-Grade Data Discovery at ING with Apache Atlas and Amundsen

In the presentation Verdan will share our experience from designing and implementing a data discovery product powered by open-source technologies such as Apache Atlas and Amundsen (initially created by Lyft, and then moved to Linux Foundation).

Session Keywords
🔑 Data Discovery
🔑 Metadata Governance
🔑 Atlas
🔑 Amundsen

Abhishek Malik

Data Scientist

Germany, Hawk:AI 

Exoplanet Detection Using Machine Learning

Speaker will introduce a new machine learning based technique to detect exoplanets using the transit method. Machine learning and deep learning techniques have proven to be broadly applicable in various scientific research areas. He aims to exploit some of these methods to improve the conventional algorithm based approach used in astrophysics today to detect exoplanets.

Session Keywords
🔑 AI
🔑 Time Series
🔑 Planet Detection

Bas Geerdink

Programmer, Scientist, and IT Manager

The Netherlands, Aizonic

Streaming Processing – an Overview of the Concepts, Architecture and Technology of Doing Data Science on Real-Time Data

In this talk, Bas will present an architecture for streaming analytics solutions that covers many use cases that follow this pattern: actionable insights, fraud detection, log parsing, traffic analysis, factory data, the IoT, and others.

Session Keywords
🔑 Streaming
🔑 AI

Cristian Randieri

Founder & CEO

Italy, Intellisystem Technologies

Covid-19: Big Data Analytics and Artificial Intelligence

With the COVID-19 pandemic spreading across the globe, it’s becoming clear that few can avoid its reach, posing severe challenges to health services and having a range of related social and economic impacts.
This session will focus on the response to COVID-19 data analytics.

Session Keywords
🔑 Analytics
🔑 AI
🔑 Coronavirus

Cristian Randieri

Founder & CEO

Italy, Intellisystem Technologies

The application of Machine Learning to the Modelling of Time-Series of Atmospheric Pollution Data

The possibility of using neuro-fuzzy networks also allows the features of neural networks to be combined with fuzzy logic, thus providing automatic extraction of rule bases in the usual ‘if…then…’ form.

Mario A Vinasco

Director BI and Analytics

USA, Credit Sesame

The Intuition Behind the Use of M.L. in Marketing Analytics

This talk presents the key insights that make AI/ML useful for marketing and demystifies the core technology and illustrates case studies where my team applied the technology.

Session Keywords
🔑 Marketing Analytics
🔑 Targeting
🔑 ML

Tim Frey


Germany,  iunera GmbH & Co. KG 

Stopping Public Transport Coronavirus Infections with Big Data

 We discuss how Big Data, analytics and forecasting help to limit infections. We give insights of our journey from idea development to the actual situation and share our learnings.

Session Keywords
🔑 Forecasting
🔑 Coronavirus
🔑 Public Transport

Tomer Levi

Senior Data Engineer on the DataOps Team

Israel, Fundbox

Orchestrating Data Workflows Using a Fully Serverless Architecture

Tomer Levi explains how the data engineering team at Fundbox uses AWS StepFunctions, Docker containers, and Spark to build a live serverless data orchestration platform, focusing on their decision to build a user-freindly yet powerful and scalable solution.

Session Keywords
🔑 Serverless
🔑 Docker
🔑 Spark
🔑 Fintech

Pasha Finkelshteyn

Software Engineer

Russia, JetBrains

Kotlin for Apache Spark: Love to Frankenstein’s Monster

In this session Pasha would like to tell the story of creation of Kotlin for Apache Spark library. Root of idea, some details of Apache Spark implementation and so on.

Session Keywords
🔑 Data Engineering
🔑 Kotlin
🔑 Spark