Sessions

Kacper Łukawski

k-NN on steroids – an introduction to approximate nearest neighbours

Kacper Łukawski, Qdrant

Athan Reines

Machine Learning in a Browser

Athan Reines, Quansight

Prof. Subramanyam Chandrasekhar

Company valuation using deep learning

Prof. Subramanyam Chandrasekhar, Jagdish Sheth School of Management

Benjamin McCulloch

Have you really embraced audio?

Benjamin McCulloch, Conversation Designer

Dr. Raul Rodríguez

Future of HR from 2021: Reimagining the Future.

Dr. Raul Rodríguez, Woxsen University

Alex Polyakov

Threat modeling and security assessment for ML models

Alex Polyakov, Adversa.AI

Andreas Bühlmeier

How Machine Learning is (becoming) creative

Andreas Bühlmeier, DBC Enterprice Intelligence

Dr. René Brunner

Practical Experiences from setting up the complete MLOps pipeline

Dr. René Brunner, Datamics / Professor an der Hochschule Macromedia

Aditya Gulgani

State-of-the-art in large scale recommender systems

Aditya Gulgani, Meta

Athan Reines

Case Studies: Machine Learning in Web Applications

Athan Reines, Quansight

Jesus Rodriguez

Doing More with Less: Building Machine Learning Solutions without Large Labeled Datasets

Jesus Rodriguez, Invector Labs

Andreas Eberle

Playing Doom with TF-Agents and TensorFlow 2.0

Andreas Eberle, arconsis IT-Solutions GmbH

Christoph Henkelmann

Using Neural Networks for Natural Language Processing

Christoph Henkelmann, DIVISIO

Carmine Paolino

Scaling Machine Learning Systems up to Billions of Predictions per Day

Carmine Paolino, Alan Turing Institute

Jon Bratseth

Applying machine learning online at scale

Jon Bratseth, Yahoo

Vadim Markovtsev

Towards a Convenient ML Infra

Vadim Markovtsev, source{d}

Oliver Zeigermann

Understanding how Neural Networks work by looking at the Low Level API of TensorFlow 2

Oliver Zeigermann, OPEN KNOWLEDGE GmbH

Sam Vanhoutte

Streamlining your Machine Learning Projects using MLOps with Azure Machine Learning

Sam Vanhoutte, Codit

Dr. Tim Frey

Stopping Public Transport Coronavirus Infections with Big Data

Dr. Tim Frey, iunera GmbH & Co. KG

Juha Kiili

Asynchronous and version-controlled data science with Jupyter notebooks

Juha Kiili, Valohai

Dr. Rachid Kherrazi

Why Security is Important in ML and How to Secure your ML-based Solutions

Dr. Rachid Kherrazi, AKKA Netherlands B.V.

Jens Beyer

Dockerize, Standardize, Deploy and Scale your own Machine Learning Model

Jens Beyer, LAVRIO.solutions GmbH

Christoph Stockhammer

Leveraging Reinforcement Learning for Improvement of Traditional Controllers for a Vehicle Model – A Case Study

Christoph Stockhammer, The MathWorks GmbH

Jesus Rodriguez

Some Things I Wish I Had Known about Scaling Machine Learning Solutions

Jesus Rodriguez, Invector Labs

Håkan Silfvernagel

Machine Learning on the Edge using TensorFlow Lite

Håkan Silfvernagel, Miles Oslo AS

Daniel Schruhl

Christoph Windheuser

Continuous Delivery for Machine Learning Applications with Open Source Tools

Daniel Schruhl, ThoughtWorks Germany

Christoph Windheuser, ThoughtWorks Germany

Christian Dedié

Dr. Katsiaryna Stalpouskaya

Pre-Moderation – The Safe Sandbox for your Community

Christian Dedié, gutefrage.net GmbH

Dr. Katsiaryna Stalpouskaya, gutefrage.net GmbH

Jon Bratseth

Vector embedding AI in production systems

Jon Bratseth, Yahoo

Nicolas Kuhaupt

Privacy-preserving Machine Learning

Nicolas Kuhaupt, Fraunhofer IEE

Christoph Henkelmann

Efficient Transformers

Christoph Henkelmann, DIVISIO

Mathias Burger

Client-side Artificial Intelligence in JavaScript using Tensorflow.js

Mathias Burger, TNG Technology GmbH

Dieter Jordens

Enhancing Page Visits by Topic Prediction

Dieter Jordens, Dieter Jordens IT Consulting BV

Dr. Tim Frey

How We Covered Concept Drifts In Time Series Forecasting For Public Transport

Dr. Tim Frey, iunera GmbH & Co. KG

Dr. Maximilian Junker

The Bigger the Better for NLP – or not?

Dr. Maximilian Junker, Qualicen

Hauke Brammer

Kotlin? For Machine Learning?

Hauke Brammer, DeepUp GmbH

Andreas Bühlmeier

All You Need to Know now about (Deep) Reinforcement Learning

Andreas Bühlmeier, DBC Enterprice Intelligence

Askhat Urazbaev

Lean Data Science: Tailoring Agile Practices for Data Science Projects

Askhat Urazbaev, ScrumTrek

Thomas Chen

Unsupervised Category-Specific Mesh Reconstruction: A Future ML Opportunity

Thomas Chen, Academy for Mathematics, Science, and Engineering

Dr. Pieter Buteneers

Machine Learning Sucks

Dr. Pieter Buteneers, Sinch

Vladimir Rybakov

Case Study: Making the Most out of a Doomed Project

Vladimir Rybakov, WaveAccess

Prof. Debjyoti Paul

Federated Learning: The Next Generation Machine Learning for Regulated Domains – Healthcare and Banking

Prof. Debjyoti Paul, Amazon

Prof. Debjyoti Paul

Data Centric AI vs Model Centric AI – The “right” data vs “best” model culture

Prof. Debjyoti Paul, Amazon

Hauke Brammer

MLOps: DevOps for Machine Learning

Hauke Brammer, DeepUp GmbH

Dr. Rachid Kherrazi

How are AI and ML helping to boost our agile development process

Dr. Rachid Kherrazi, AKKA Netherlands B.V.

Yonah Walker

Algorithmic Diversity & Nonbinarity. How to Reimagine Ability, Tech & Ethics

Yonah Walker, Yonah Fund

Michael Osterrieder

Dataset design for technically and legally clean ML development

Michael Osterrieder, vAIsual Inc

Christoph Henkelmann

From Paper to Product – How we implemented BERT

Christoph Henkelmann, DIVISIO

Maksym Tatariants

3D Human Pose Estimation: How To Use It in AI Coach Apps

Maksym Tatariants, MobiDev

Laura Kölbl

Nature inspired optimization algorithms / Algorithm-based Staffing with Ant Colony Optimization

Laura Kölbl, MATHEMA GmbH

Anastasiia Vynychenko

Increasing Business Efficiency through NLP Integration: Text Summarization and Sentiment Analysis

Anastasiia Vynychenko, MobiDev

Samar Singla

Speeding up Last-Mile Delivery with AI

Samar Singla, Jungleworks

Jeff Blankenburg

The Future of People

Jeff Blankenburg, Amazon Alexa

Håkan Silfvernagel

Affective Computing – bringing humans and machines closer through emotions

Håkan Silfvernagel, Miles Oslo AS

Jochen Emig

Leonard Füchsel

Voice assistants with the Fraunhofer SPEAKER project

Jochen Emig, ONSEI GmbH

Leonard Füchsel, ONSEI GmbH

Liudmyla Taranenko

No prejudice. No remorse. Unsupervised ML

Liudmyla Taranenko, MobiDev

Jochen Emig

Voice Development with modern AI Tools

Jochen Emig, ONSEI GmbH

Kumar Rangarajan

The Rise of Voice Commerce in India

Kumar Rangarajan, Slang Labs

Jo Jaquinta

Thinking outside the box: Insights From the Visually-Impaired Community into Audio Games Development

Jo Jaquinta, TsaTsaTzu

Dr. Patricia Scanlon

What about the Kids? How Speech Technology transforms Digital Experiences for Kids

Dr. Patricia Scanlon, SoapBox Labs

John Campbell

How Voice Search is Evolving: Using Insights from Alexa Voice Search

John Campbell, Rabbit & Pork

Dr. Darshita Chaturvedi

Creating a testing workbench for ML teams using just Python

Dr. Darshita Chaturvedi, Atri Labs

Grishma Jena

Demystifying Data Science

Grishma Jena, IBM

Christoph Henkelmann

How to write a good Training Script?

Christoph Henkelmann, DIVISIO

Sven Haiges

Brewing Beer with the Help of IoT: Building a DIY Fermentation Sensor

Sven Haiges, SAP Hybris

Fekete Csongor

Leveraging Earth Observation Satellite images for Financial Indsutry

Fekete Csongor, HolistiCRM Kft.

Dominik Meißner

Holistic Voice Application Monitoring: How to sleep well every night

Dominik Meißner, 169 Labs GmbH

Dr. Tobias Brambach

IoT and eSports – Learning for the industry in your spare time

Dr. Tobias Brambach, Point 8 GmbH

Mihailo Joksimovic

Let’s learn R by debugging the Currywurst!

Mihailo Joksimovic, JAGGAER

Jannik Fischbach

How to use Natural Language Processing for automatic test case design?

Jannik Fischbach, Qualicen Gmbh

Mihailo Joksimovic

So, what exactly is MLOps?

Mihailo Joksimovic, JAGGAER

Sebastian Meyen

Welcome & Introduction

Sebastian Meyen, Software & Support Media

Thomas Abend

Voice Assistants for Customer Support based on Deep Learning

Thomas Abend, VITAS.ai

Hauke Brammer

Delivering Rocketfuel – Pipelines für Deep Learning mit Small Data

Hauke Brammer, DeepUp GmbH

Victoriya Kalmanovich

Predictive Maintenance – How Does Data Science Revolutionize the World of Machines?

Victoriya Kalmanovich, Navy

Christoph Börner

Bots testing Bots: From manual to automated testing for conversational AI

Christoph Börner, Botium GmbH

Oleksandr Honchar

Deep Learning: the final Frontier for Time Series Analysis?

Oleksandr Honchar, Neurons Lab / Mawi Solutions

Stefano Tempesta

AI-powered content moderation

Stefano Tempesta, Microsoft

Christoph Henkelmann

An Introduction to Transformers

Christoph Henkelmann, DIVISIO

Håkan Silfvernagel

Machine learning in the browser with TensorFlow.js

Håkan Silfvernagel, Miles Oslo AS

Ward Van Laer

MLOps – from ML model to cloud-service: challenges and pitfalls of scalable document processing

Ward Van Laer, Ixor

Markovtsev Vadim

Kubeflow on a Bare-Metal GPU Cluster from Scratch

Markovtsev Vadim, Athenian

Daniel Wrigley

Keyword Search is Dead! And so are Solr and Elasticsearch?

Daniel Wrigley, SHI GmbH

Bence Faludi

Architectures that power Machine Learning

Bence Faludi, dataleio

Gabrielle Fournet

NLP for career progression: connecting people with jobs and courses

Gabrielle Fournet, Boostrs

Dr. Christian Winkler

Oliver Zeigermann

Natural Language Processing (NLP): The Transformer Zoo

Dr. Christian Winkler, datanizing GmbH

Oliver Zeigermann, OPEN KNOWLEDGE GmbH

Dr. Danish Rafique

Production nightmare of building AI systems at scale – The last mile

Dr. Danish Rafique, Bayer AG

Robbe Sneyders

Evaluating machine learning solutions for subjective problems

Robbe Sneyders, ML6

Hauke Brammer

Keep an eye on AI — Monitor ML models in production

Hauke Brammer, DeepUp GmbH

Andreas Bühlmeier

Advances in Machine Learning Systems – from GPUs to Quantum

Andreas Bühlmeier, DBC Enterprice Intelligence

Dr. Pieter Buteneers

Self-supervised Learning: Teaching AI common sense

Dr. Pieter Buteneers, Sinch

Ritchie Vink

Polars: Blazingly fast DataFrames

Ritchie Vink, Xomnia BV

Dr. Neda Navidi

Human and Multi-agent systems

Dr. Neda Navidi, ETS

Anja Pilz

Natural language processing for medical data

Anja Pilz, damedic

Johannes Hötter

Greenfield and Brownfield Data Labeling – from Idea to Production with data-centric AI

Johannes Hötter, onetask.ai // kern.ai

David Monzel

Dr. Dirk Slama

AIoT – Die Verbindung zwischen AI und IoT beherrschen!

David Monzel, mm1

Dr. Dirk Slama, Bosch Software Innovations

Ioannis Tsamardinos

How AutoML can give companies, with few data scientists, a key advantage

Ioannis Tsamardinos, JADBio

Mohamed Sayed

Robo programmers? Competent minions? Or just sensational demos and hype?

Mohamed Sayed, Heuro Labs GmbH

Adrian Boguszewski

Optimize your network inference time as a data scientist, not as a web developer

Adrian Boguszewski, Intel

Oliver Zeigermann

Image Recognition: Past, Present and Future

Oliver Zeigermann, OPEN KNOWLEDGE GmbH

Markus Ehrenmüller-Jensen

Practical ML with Power BI Desktop

Markus Ehrenmüller-Jensen, Savory Data

Nikolay Manchev

Underspecified pipelines: Why good models underperform in production

Nikolay Manchev, Domino Data Lab

Danilo Dresen

IoT Analytics at Scale – Customer based product development

Danilo Dresen, taod Consulting GmbH

Dr. Rudolf Felix

Understanding Artificial Intelligence: Explainable AI with Interpretable KPI Labels

Dr. Rudolf Felix, PSI FLS Fuzzy Logik & Neuro Systeme GmbH

Thiago de Faria

AI with a devops mindset – experimentation, sharing and easier ML deployment

Thiago de Faria, LINKIT

Jan Mulkens

MLOps, Automated Machine Learning Made Easy

Jan Mulkens, Ahead with Data

Piotr Czajka

Łukasz Gebel

Machine Learning: The Bare Math Behind Libraries

Piotr Czajka, TomTom

Łukasz Gebel, TomTom

Radu Dan

On-device machine learning – Core ML vs Create ML

Radu Dan, Deloitte Digital Romania

Matthias Hofmaier

How We Used Machine Learning to Detect Stress among our Berlin Colleagues

Matthias Hofmaier, Novatec Consulting GmbH

Prof. Adam Blum

AI is eating Software – how Second Generation AutoML will replace Software Development

Prof. Adam Blum, Auger.AI

Laurent Picard

Building smarter solutions with no expertise in machine learning

Laurent Picard, Google

Alex Polyakov

AI Red Teaming: a facial recognition case study

Alex Polyakov, Adversa.AI

Jan Mulkens

AutoML, the Good, the Bad and the Why

Jan Mulkens, Ahead with Data

Sameer Paradkar

Data Analytics Platform

Sameer Paradkar, AtoS

Vladimir Rybakov

Real Machine Learning challenges that you’ve never faced at Kaggle

Vladimir Rybakov, WaveAccess

Prof. Debjyoti Paul

Interpretable Machine Learning – Application to Finance and Banks

Prof. Debjyoti Paul, Amazon

Michael Grogan

Predicting Hotel Cancellations With Machine Learning: Classification and Time Series Analysis

Michael Grogan, MGCodesandStats

Gunjan Dewan

Developing a Match-Making Algorithm Between Customers and Go-Jek Products!

Gunjan Dewan, Go-Jek

Dr. Luca Marchesotti

Real, Fake and Deepfake: How Deep Learning Messed up Customer (Re)Identification and How It Will Fix It

Dr. Luca Marchesotti, Sparkd

Dorra Nouira

Using A.I to make recommendations for career progression

Dorra Nouira, Boostrs

Alexey Grigorev

Automatic Image Cropping for Online Classifieds: a Journey from a Master Thesis to Production

Alexey Grigorev, OLX Group

Alex Polyakov

Protecting AI Solutions From Attacks

Alex Polyakov, Adversa.AI

Steven Bourke

Building Human-in-the-Loop Machine Learning Systems – Fashion 2.0

Steven Bourke, Outfittery

Dagmar Schuller

Next generation AI: Emotional Artificial Intelligence based on audio

Dagmar Schuller, audEERING GmbH

Hans-Peter Kuessner

Jens Polster

How to raise intelligent Chatbots, keep them smart and make them useful

Hans-Peter Kuessner, adesso AG

Jens Polster, adesso AG

Ming Yong

MediaPipe: Building real-time cross-platform (mobile, web, edge, desktop) Video Audio ML Pipelines

Ming Yong, Goolge Inc

Julien Schuermans

The unreasonable effectiveness of simple models

Julien Schuermans, ML6

Lisa Becker

The importance and pitfalls of pseudonymization

Lisa Becker, ML6

Liubov Zatolokina

Building AI startups with minimum risks

Liubov Zatolokina, MobiDev

Prof. Debjyoti Paul

Multi Tasking Deep Learning for Natural Language Processing – Transfer Learning

Prof. Debjyoti Paul, Amazon

Dr. Tatyana Goldberg

Dr. Guy Yachdav

Transforming Business with AI – From Vision to Strategy to Execution

Dr. Tatyana Goldberg, Allianz

Dr. Guy Yachdav, Aiola

Michael Inden

Battle of the Languages: Java and Python compete to solve programming challenges

Michael Inden, Freelancer

Thomas Chen

From 2D to 3D: Unsupervised Reconstruction in Computer Vision using U-CMR

Thomas Chen, Academy for Mathematics, Science, and Engineering

Thiago da Silva Alves

Honey Bee Conservation using Deep Learning

Thiago da Silva Alves, JArchitects

Lars Gregori

Honey, I shrunk the TinyML

Lars Gregori, SAP CX

Christoph Henkelmann

#An Introduction to Clustering Algorithms

Christoph Henkelmann, DIVISIO

Ilia Lorin

Smaller, Faster, Cheaper: CNN Optimisation Techniques in Object Detection

Ilia Lorin, MobiDev

Mihailo Joksimovic

Let’s talk about Recommendation Systems!

Mihailo Joksimovic, JAGGAER

Stefano Tempesta

Preserve data privacy in Machine Learning with Confidential Computing

Stefano Tempesta, Microsoft

Jan Schilt

The Phoenix Project, how simulations can create high performing teams

Jan Schilt, GamingWorks

Pia Eggert

Real time Covid-19 detection with Audio AI

Pia Eggert, Freelancer

Christoph Henkelmann

Unsupervised Learning with Autoencoders

Christoph Henkelmann, DIVISIO

Surendran Selvaraju

Artificial Intelligence and Machine Learning

Surendran Selvaraju, AINQA Healthcare

Dr. Maximilian Junker

A Few Million Words Later – Text Analytics for Software Quality Assurance in Practice

Dr. Maximilian Junker, Qualicen

Dr. Raul Rodriguez

Coded Leadership: Developing Scalable Management in an AI-induced Quantum World

Dr. Raul Rodriguez, Woxsen University

Amit Bendor

Warning: this is not another MLOps best practices talk

Amit Bendor, Artlist

Dr. Beauty Pandey

Machine Learning Techniques for Estimating Science and Properties of Materials

Dr. Beauty Pandey, WOXSEN University Hyderabad

Dr. Christian Winkler

Introduction to Sentence Embeddings

Dr. Christian Winkler, datanizing GmbH

Burak Aytan

Dr. Ilknur Durgar

Muhammed Güre

Designing Conversational Chatbot for Digital Operators

Burak Aytan, TURKCELL

Dr. Ilknur Durgar, TURKCELL

Muhammed Güre, TURKCELL

Jon Bratseth

Vector embedding AI in practice

Jon Bratseth, Yahoo

Burak Isikli

NLU in Other Languages

Burak Isikli, Akbank

Vladimir Rybakov

Satellite imagery analysis: Machine Learning to prevent environmental crisis

Vladimir Rybakov, WaveAccess

Juantomás Garcia

AbadIA: How to build an AI from zero to learn to play and solve a tough game

Juantomás Garcia, Sngular People S.L

Christoph Henkelmann

An Introduction to Natural Language Generation

Christoph Henkelmann, DIVISIO

Sergey Maximenko

Fast and accurate: AI-based video processing

Sergey Maximenko, MobiDev

All Sessions

Kacper Łukawski

k-NN on steroids – an introduction to approximate nearest neighbours

Kacper Łukawski, Qdrant

Athan Reines

Machine Learning in a Browser

Athan Reines, Quansight

Prof. Subramanyam Chandrasekhar

Company valuation using deep learning

Prof. Subramanyam Chandrasekhar, Jagdish Sheth School of Management

Benjamin McCulloch

Have you really embraced audio?

Benjamin McCulloch, Conversation Designer

Dr. Raul Rodríguez

Future of HR from 2021: Reimagining the Future.

Dr. Raul Rodríguez, Woxsen University

Alex Polyakov

Threat modeling and security assessment for ML models

Alex Polyakov, Adversa.AI

Andreas Bühlmeier

How Machine Learning is (becoming) creative

Andreas Bühlmeier, DBC Enterprice Intelligence

Dr. René Brunner

Practical Experiences from setting up the complete MLOps pipeline

Dr. René Brunner, Datamics / Professor an der Hochschule Macromedia

Aditya Gulgani

State-of-the-art in large scale recommender systems

Aditya Gulgani, Meta

Athan Reines

Case Studies: Machine Learning in Web Applications

Athan Reines, Quansight

Jesus Rodriguez

Doing More with Less: Building Machine Learning Solutions without Large Labeled Datasets

Jesus Rodriguez, Invector Labs

Andreas Eberle

Playing Doom with TF-Agents and TensorFlow 2.0

Andreas Eberle, arconsis IT-Solutions GmbH

Christoph Henkelmann

Using Neural Networks for Natural Language Processing

Christoph Henkelmann, DIVISIO

Carmine Paolino

Scaling Machine Learning Systems up to Billions of Predictions per Day

Carmine Paolino, Alan Turing Institute

Jon Bratseth

Applying machine learning online at scale

Jon Bratseth, Yahoo

Vadim Markovtsev

Towards a Convenient ML Infra

Vadim Markovtsev, source{d}

Oliver Zeigermann

Understanding how Neural Networks work by looking at the Low Level API of TensorFlow 2

Oliver Zeigermann, OPEN KNOWLEDGE GmbH

Sam Vanhoutte

Streamlining your Machine Learning Projects using MLOps with Azure Machine Learning

Sam Vanhoutte, Codit

Dr. Tim Frey

Stopping Public Transport Coronavirus Infections with Big Data

Dr. Tim Frey, iunera GmbH & Co. KG

Juha Kiili

Asynchronous and version-controlled data science with Jupyter notebooks

Juha Kiili, Valohai

Dr. Rachid Kherrazi

Why Security is Important in ML and How to Secure your ML-based Solutions

Dr. Rachid Kherrazi, AKKA Netherlands B.V.

Jens Beyer

Dockerize, Standardize, Deploy and Scale your own Machine Learning Model

Jens Beyer, LAVRIO.solutions GmbH

Christoph Stockhammer

Leveraging Reinforcement Learning for Improvement of Traditional Controllers for a Vehicle Model – A Case Study

Christoph Stockhammer, The MathWorks GmbH

Jesus Rodriguez

Some Things I Wish I Had Known about Scaling Machine Learning Solutions

Jesus Rodriguez, Invector Labs

Håkan Silfvernagel

Machine Learning on the Edge using TensorFlow Lite

Håkan Silfvernagel, Miles Oslo AS

Daniel Schruhl

Christoph Windheuser

Continuous Delivery for Machine Learning Applications with Open Source Tools

Daniel Schruhl, ThoughtWorks Germany

Christoph Windheuser, ThoughtWorks Germany

Christian Dedié

Dr. Katsiaryna Stalpouskaya

Pre-Moderation – The Safe Sandbox for your Community

Christian Dedié, gutefrage.net GmbH

Dr. Katsiaryna Stalpouskaya, gutefrage.net GmbH

Jon Bratseth

Vector embedding AI in production systems

Jon Bratseth, Yahoo

Nicolas Kuhaupt

Privacy-preserving Machine Learning

Nicolas Kuhaupt, Fraunhofer IEE

Christoph Henkelmann

Efficient Transformers

Christoph Henkelmann, DIVISIO

Mathias Burger

Client-side Artificial Intelligence in JavaScript using Tensorflow.js

Mathias Burger, TNG Technology GmbH

Dieter Jordens

Enhancing Page Visits by Topic Prediction

Dieter Jordens, Dieter Jordens IT Consulting BV

Dr. Tim Frey

How We Covered Concept Drifts In Time Series Forecasting For Public Transport

Dr. Tim Frey, iunera GmbH & Co. KG

Dr. Maximilian Junker

The Bigger the Better for NLP – or not?

Dr. Maximilian Junker, Qualicen

Hauke Brammer

Kotlin? For Machine Learning?

Hauke Brammer, DeepUp GmbH

Andreas Bühlmeier

All You Need to Know now about (Deep) Reinforcement Learning

Andreas Bühlmeier, DBC Enterprice Intelligence

Askhat Urazbaev

Lean Data Science: Tailoring Agile Practices for Data Science Projects

Askhat Urazbaev, ScrumTrek

Thomas Chen

Unsupervised Category-Specific Mesh Reconstruction: A Future ML Opportunity

Thomas Chen, Academy for Mathematics, Science, and Engineering

Dr. Pieter Buteneers

Machine Learning Sucks

Dr. Pieter Buteneers, Sinch

Vladimir Rybakov

Case Study: Making the Most out of a Doomed Project

Vladimir Rybakov, WaveAccess

Prof. Debjyoti Paul

Federated Learning: The Next Generation Machine Learning for Regulated Domains – Healthcare and Banking

Prof. Debjyoti Paul, Amazon

Prof. Debjyoti Paul

Data Centric AI vs Model Centric AI – The “right” data vs “best” model culture

Prof. Debjyoti Paul, Amazon

Hauke Brammer

MLOps: DevOps for Machine Learning

Hauke Brammer, DeepUp GmbH

Dr. Rachid Kherrazi

How are AI and ML helping to boost our agile development process

Dr. Rachid Kherrazi, AKKA Netherlands B.V.

Yonah Walker

Algorithmic Diversity & Nonbinarity. How to Reimagine Ability, Tech & Ethics

Yonah Walker, Yonah Fund

Michael Osterrieder

Dataset design for technically and legally clean ML development

Michael Osterrieder, vAIsual Inc

Christoph Henkelmann

From Paper to Product – How we implemented BERT

Christoph Henkelmann, DIVISIO

Maksym Tatariants

3D Human Pose Estimation: How To Use It in AI Coach Apps

Maksym Tatariants, MobiDev

Laura Kölbl

Nature inspired optimization algorithms / Algorithm-based Staffing with Ant Colony Optimization

Laura Kölbl, MATHEMA GmbH

Anastasiia Vynychenko

Increasing Business Efficiency through NLP Integration: Text Summarization and Sentiment Analysis

Anastasiia Vynychenko, MobiDev

Samar Singla

Speeding up Last-Mile Delivery with AI

Samar Singla, Jungleworks

Jeff Blankenburg

The Future of People

Jeff Blankenburg, Amazon Alexa

Håkan Silfvernagel

Affective Computing – bringing humans and machines closer through emotions

Håkan Silfvernagel, Miles Oslo AS

Jochen Emig

Leonard Füchsel

Voice assistants with the Fraunhofer SPEAKER project

Jochen Emig, ONSEI GmbH

Leonard Füchsel, ONSEI GmbH

Liudmyla Taranenko

No prejudice. No remorse. Unsupervised ML

Liudmyla Taranenko, MobiDev

Jochen Emig

Voice Development with modern AI Tools

Jochen Emig, ONSEI GmbH

Kumar Rangarajan

The Rise of Voice Commerce in India

Kumar Rangarajan, Slang Labs

Jo Jaquinta

Thinking outside the box: Insights From the Visually-Impaired Community into Audio Games Development

Jo Jaquinta, TsaTsaTzu

Dr. Patricia Scanlon

What about the Kids? How Speech Technology transforms Digital Experiences for Kids

Dr. Patricia Scanlon, SoapBox Labs

John Campbell

How Voice Search is Evolving: Using Insights from Alexa Voice Search

John Campbell, Rabbit & Pork

Dr. Darshita Chaturvedi

Creating a testing workbench for ML teams using just Python

Dr. Darshita Chaturvedi, Atri Labs

Grishma Jena

Demystifying Data Science

Grishma Jena, IBM

Christoph Henkelmann

How to write a good Training Script?

Christoph Henkelmann, DIVISIO

Sven Haiges

Brewing Beer with the Help of IoT: Building a DIY Fermentation Sensor

Sven Haiges, SAP Hybris

Fekete Csongor

Leveraging Earth Observation Satellite images for Financial Indsutry

Fekete Csongor, HolistiCRM Kft.

Dominik Meißner

Holistic Voice Application Monitoring: How to sleep well every night

Dominik Meißner, 169 Labs GmbH

Dr. Tobias Brambach

IoT and eSports – Learning for the industry in your spare time

Dr. Tobias Brambach, Point 8 GmbH

Mihailo Joksimovic

Let’s learn R by debugging the Currywurst!

Mihailo Joksimovic, JAGGAER

Jannik Fischbach

How to use Natural Language Processing for automatic test case design?

Jannik Fischbach, Qualicen Gmbh

Mihailo Joksimovic

So, what exactly is MLOps?

Mihailo Joksimovic, JAGGAER

Sebastian Meyen

Welcome & Introduction

Sebastian Meyen, Software & Support Media

Thomas Abend

Voice Assistants for Customer Support based on Deep Learning

Thomas Abend, VITAS.ai

Hauke Brammer

Delivering Rocketfuel – Pipelines für Deep Learning mit Small Data

Hauke Brammer, DeepUp GmbH

Victoriya Kalmanovich

Predictive Maintenance – How Does Data Science Revolutionize the World of Machines?

Victoriya Kalmanovich, Navy

Christoph Börner

Bots testing Bots: From manual to automated testing for conversational AI

Christoph Börner, Botium GmbH

Oleksandr Honchar

Deep Learning: the final Frontier for Time Series Analysis?

Oleksandr Honchar, Neurons Lab / Mawi Solutions

Stefano Tempesta

AI-powered content moderation

Stefano Tempesta, Microsoft

Christoph Henkelmann

An Introduction to Transformers

Christoph Henkelmann, DIVISIO

Håkan Silfvernagel

Machine learning in the browser with TensorFlow.js

Håkan Silfvernagel, Miles Oslo AS

Ward Van Laer

MLOps – from ML model to cloud-service: challenges and pitfalls of scalable document processing

Ward Van Laer, Ixor

Markovtsev Vadim

Kubeflow on a Bare-Metal GPU Cluster from Scratch

Markovtsev Vadim, Athenian

Daniel Wrigley

Keyword Search is Dead! And so are Solr and Elasticsearch?

Daniel Wrigley, SHI GmbH

Bence Faludi

Architectures that power Machine Learning

Bence Faludi, dataleio

Gabrielle Fournet

NLP for career progression: connecting people with jobs and courses

Gabrielle Fournet, Boostrs

Dr. Christian Winkler

Oliver Zeigermann

Natural Language Processing (NLP): The Transformer Zoo

Dr. Christian Winkler, datanizing GmbH

Oliver Zeigermann, OPEN KNOWLEDGE GmbH

Dr. Danish Rafique

Production nightmare of building AI systems at scale – The last mile

Dr. Danish Rafique, Bayer AG

Robbe Sneyders

Evaluating machine learning solutions for subjective problems

Robbe Sneyders, ML6

Hauke Brammer

Keep an eye on AI — Monitor ML models in production

Hauke Brammer, DeepUp GmbH

Andreas Bühlmeier

Advances in Machine Learning Systems – from GPUs to Quantum

Andreas Bühlmeier, DBC Enterprice Intelligence

Dr. Pieter Buteneers

Self-supervised Learning: Teaching AI common sense

Dr. Pieter Buteneers, Sinch

Ritchie Vink

Polars: Blazingly fast DataFrames

Ritchie Vink, Xomnia BV

Dr. Neda Navidi

Human and Multi-agent systems

Dr. Neda Navidi, ETS

Anja Pilz

Natural language processing for medical data

Anja Pilz, damedic

Johannes Hötter

Greenfield and Brownfield Data Labeling – from Idea to Production with data-centric AI

Johannes Hötter, onetask.ai // kern.ai

David Monzel

Dr. Dirk Slama

AIoT – Die Verbindung zwischen AI und IoT beherrschen!

David Monzel, mm1

Dr. Dirk Slama, Bosch Software Innovations

Ioannis Tsamardinos

How AutoML can give companies, with few data scientists, a key advantage

Ioannis Tsamardinos, JADBio

Mohamed Sayed

Robo programmers? Competent minions? Or just sensational demos and hype?

Mohamed Sayed, Heuro Labs GmbH

Adrian Boguszewski

Optimize your network inference time as a data scientist, not as a web developer

Adrian Boguszewski, Intel

Oliver Zeigermann

Image Recognition: Past, Present and Future

Oliver Zeigermann, OPEN KNOWLEDGE GmbH

Markus Ehrenmüller-Jensen

Practical ML with Power BI Desktop

Markus Ehrenmüller-Jensen, Savory Data

Nikolay Manchev

Underspecified pipelines: Why good models underperform in production

Nikolay Manchev, Domino Data Lab

Danilo Dresen

IoT Analytics at Scale – Customer based product development

Danilo Dresen, taod Consulting GmbH

Dr. Rudolf Felix

Understanding Artificial Intelligence: Explainable AI with Interpretable KPI Labels

Dr. Rudolf Felix, PSI FLS Fuzzy Logik & Neuro Systeme GmbH

Thiago de Faria

AI with a devops mindset – experimentation, sharing and easier ML deployment

Thiago de Faria, LINKIT

Jan Mulkens

MLOps, Automated Machine Learning Made Easy

Jan Mulkens, Ahead with Data

Piotr Czajka

Łukasz Gebel

Machine Learning: The Bare Math Behind Libraries

Piotr Czajka, TomTom

Łukasz Gebel, TomTom

Radu Dan

On-device machine learning – Core ML vs Create ML

Radu Dan, Deloitte Digital Romania

Matthias Hofmaier

How We Used Machine Learning to Detect Stress among our Berlin Colleagues

Matthias Hofmaier, Novatec Consulting GmbH

Prof. Adam Blum

AI is eating Software – how Second Generation AutoML will replace Software Development

Prof. Adam Blum, Auger.AI

Laurent Picard

Building smarter solutions with no expertise in machine learning

Laurent Picard, Google

Alex Polyakov

AI Red Teaming: a facial recognition case study

Alex Polyakov, Adversa.AI

Jan Mulkens

AutoML, the Good, the Bad and the Why

Jan Mulkens, Ahead with Data

Sameer Paradkar

Data Analytics Platform

Sameer Paradkar, AtoS

Vladimir Rybakov

Real Machine Learning challenges that you’ve never faced at Kaggle

Vladimir Rybakov, WaveAccess

Prof. Debjyoti Paul

Interpretable Machine Learning – Application to Finance and Banks

Prof. Debjyoti Paul, Amazon

Michael Grogan

Predicting Hotel Cancellations With Machine Learning: Classification and Time Series Analysis

Michael Grogan, MGCodesandStats

Gunjan Dewan

Developing a Match-Making Algorithm Between Customers and Go-Jek Products!

Gunjan Dewan, Go-Jek

Dr. Luca Marchesotti

Real, Fake and Deepfake: How Deep Learning Messed up Customer (Re)Identification and How It Will Fix It

Dr. Luca Marchesotti, Sparkd

Dorra Nouira

Using A.I to make recommendations for career progression

Dorra Nouira, Boostrs

Alexey Grigorev

Automatic Image Cropping for Online Classifieds: a Journey from a Master Thesis to Production

Alexey Grigorev, OLX Group

Alex Polyakov

Protecting AI Solutions From Attacks

Alex Polyakov, Adversa.AI

Steven Bourke

Building Human-in-the-Loop Machine Learning Systems – Fashion 2.0

Steven Bourke, Outfittery

Dagmar Schuller

Next generation AI: Emotional Artificial Intelligence based on audio

Dagmar Schuller, audEERING GmbH

Hans-Peter Kuessner

Jens Polster

How to raise intelligent Chatbots, keep them smart and make them useful

Hans-Peter Kuessner, adesso AG

Jens Polster, adesso AG

Ming Yong

MediaPipe: Building real-time cross-platform (mobile, web, edge, desktop) Video Audio ML Pipelines

Ming Yong, Goolge Inc

Julien Schuermans

The unreasonable effectiveness of simple models

Julien Schuermans, ML6

Lisa Becker

The importance and pitfalls of pseudonymization

Lisa Becker, ML6

Liubov Zatolokina

Building AI startups with minimum risks

Liubov Zatolokina, MobiDev

Prof. Debjyoti Paul

Multi Tasking Deep Learning for Natural Language Processing – Transfer Learning

Prof. Debjyoti Paul, Amazon

Dr. Tatyana Goldberg

Dr. Guy Yachdav

Transforming Business with AI – From Vision to Strategy to Execution

Dr. Tatyana Goldberg, Allianz

Dr. Guy Yachdav, Aiola

Michael Inden

Battle of the Languages: Java and Python compete to solve programming challenges

Michael Inden, Freelancer

Thomas Chen

From 2D to 3D: Unsupervised Reconstruction in Computer Vision using U-CMR

Thomas Chen, Academy for Mathematics, Science, and Engineering

Thiago da Silva Alves

Honey Bee Conservation using Deep Learning

Thiago da Silva Alves, JArchitects

Lars Gregori

Honey, I shrunk the TinyML

Lars Gregori, SAP CX

Christoph Henkelmann

#An Introduction to Clustering Algorithms

Christoph Henkelmann, DIVISIO

Ilia Lorin

Smaller, Faster, Cheaper: CNN Optimisation Techniques in Object Detection

Ilia Lorin, MobiDev

Mihailo Joksimovic

Let’s talk about Recommendation Systems!

Mihailo Joksimovic, JAGGAER

Stefano Tempesta

Preserve data privacy in Machine Learning with Confidential Computing

Stefano Tempesta, Microsoft

Jan Schilt

The Phoenix Project, how simulations can create high performing teams

Jan Schilt, GamingWorks

Pia Eggert

Real time Covid-19 detection with Audio AI

Pia Eggert, Freelancer

Christoph Henkelmann

Unsupervised Learning with Autoencoders

Christoph Henkelmann, DIVISIO

Surendran Selvaraju

Artificial Intelligence and Machine Learning

Surendran Selvaraju, AINQA Healthcare

Dr. Maximilian Junker

A Few Million Words Later – Text Analytics for Software Quality Assurance in Practice

Dr. Maximilian Junker, Qualicen

Dr. Raul Rodriguez

Coded Leadership: Developing Scalable Management in an AI-induced Quantum World

Dr. Raul Rodriguez, Woxsen University

Amit Bendor

Warning: this is not another MLOps best practices talk

Amit Bendor, Artlist

Dr. Beauty Pandey

Machine Learning Techniques for Estimating Science and Properties of Materials

Dr. Beauty Pandey, WOXSEN University Hyderabad

Dr. Christian Winkler

Introduction to Sentence Embeddings

Dr. Christian Winkler, datanizing GmbH

Burak Aytan

Dr. Ilknur Durgar

Muhammed Güre

Designing Conversational Chatbot for Digital Operators

Burak Aytan, TURKCELL

Dr. Ilknur Durgar, TURKCELL

Muhammed Güre, TURKCELL

Jon Bratseth

Vector embedding AI in practice

Jon Bratseth, Yahoo

Burak Isikli

NLU in Other Languages

Burak Isikli, Akbank

Vladimir Rybakov

Satellite imagery analysis: Machine Learning to prevent environmental crisis

Vladimir Rybakov, WaveAccess

Juantomás Garcia

AbadIA: How to build an AI from zero to learn to play and solve a tough game

Juantomás Garcia, Sngular People S.L

Christoph Henkelmann

An Introduction to Natural Language Generation

Christoph Henkelmann, DIVISIO

Sergey Maximenko

Fast and accurate: AI-based video processing

Sergey Maximenko, MobiDev

Sessions Berlin 2022

Dr. René Brunner

Practical Experiences from setting up the complete MLOps pipeline

Dr. René Brunner, Datamics / Professor an der Hochschule Macromedia

Jon Bratseth

Vector embedding AI in production systems

Jon Bratseth, Yahoo

Prof. Debjyoti Paul

Data Centric AI vs Model Centric AI – The “right” data vs “best” model culture

Prof. Debjyoti Paul, Amazon

Dr. Darshita Chaturvedi

Creating a testing workbench for ML teams using just Python

Dr. Darshita Chaturvedi, Atri Labs

Grishma Jena

Demystifying Data Science

Grishma Jena, IBM

Christoph Henkelmann

How to write a good Training Script?

Christoph Henkelmann, DIVISIO

Fekete Csongor

Leveraging Earth Observation Satellite images for Financial Indsutry

Fekete Csongor, HolistiCRM Kft.

Dominik Meißner

Holistic Voice Application Monitoring: How to sleep well every night

Dominik Meißner, 169 Labs GmbH

Mihailo Joksimovic

Let’s learn R by debugging the Currywurst!

Mihailo Joksimovic, JAGGAER

Mihailo Joksimovic

So, what exactly is MLOps?

Mihailo Joksimovic, JAGGAER

Ward Van Laer

MLOps – from ML model to cloud-service: challenges and pitfalls of scalable document processing

Ward Van Laer, Ixor

Ioannis Tsamardinos

How AutoML can give companies, with few data scientists, a key advantage

Ioannis Tsamardinos, JADBio

Mohamed Sayed

Robo programmers? Competent minions? Or just sensational demos and hype?

Mohamed Sayed, Heuro Labs GmbH

Oliver Zeigermann

Image Recognition: Past, Present and Future

Oliver Zeigermann, OPEN KNOWLEDGE GmbH

Lisa Becker

The importance and pitfalls of pseudonymization

Lisa Becker, ML6

Amit Bendor

Warning: this is not another MLOps best practices talk

Amit Bendor, Artlist

Dr. Beauty Pandey

Machine Learning Techniques for Estimating Science and Properties of Materials

Dr. Beauty Pandey, WOXSEN University Hyderabad

Sessions Singapore 2022

Dr. Tim Frey

How We Covered Concept Drifts In Time Series Forecasting For Public Transport

Dr. Tim Frey, iunera GmbH & Co. KG

Dr. Pieter Buteneers

Machine Learning Sucks

Dr. Pieter Buteneers, Sinch

Prof. Debjyoti Paul

Data Centric AI vs Model Centric AI – The “right” data vs “best” model culture

Prof. Debjyoti Paul, Amazon

Dr. Rachid Kherrazi

How are AI and ML helping to boost our agile development process

Dr. Rachid Kherrazi, AKKA Netherlands B.V.

Håkan Silfvernagel

Affective Computing – bringing humans and machines closer through emotions

Håkan Silfvernagel, Miles Oslo AS

Stefano Tempesta

AI-powered content moderation

Stefano Tempesta, Microsoft

Håkan Silfvernagel

Machine learning in the browser with TensorFlow.js

Håkan Silfvernagel, Miles Oslo AS

Ioannis Tsamardinos

How AutoML can give companies, with few data scientists, a key advantage

Ioannis Tsamardinos, JADBio

Sameer Paradkar

Data Analytics Platform

Sameer Paradkar, AtoS

Lisa Becker

The importance and pitfalls of pseudonymization

Lisa Becker, ML6

Christoph Henkelmann

#An Introduction to Clustering Algorithms

Christoph Henkelmann, DIVISIO

Mihailo Joksimovic

Let’s talk about Recommendation Systems!

Mihailo Joksimovic, JAGGAER

Stefano Tempesta

Preserve data privacy in Machine Learning with Confidential Computing

Stefano Tempesta, Microsoft

Jan Schilt

The Phoenix Project, how simulations can create high performing teams

Jan Schilt, GamingWorks

Surendran Selvaraju

Artificial Intelligence and Machine Learning

Surendran Selvaraju, AINQA Healthcare

Dr. Raul Rodriguez

Coded Leadership: Developing Scalable Management in an AI-induced Quantum World

Dr. Raul Rodriguez, Woxsen University

Amit Bendor

Warning: this is not another MLOps best practices talk

Amit Bendor, Artlist

Dr. Beauty Pandey

Machine Learning Techniques for Estimating Science and Properties of Materials

Dr. Beauty Pandey, WOXSEN University Hyderabad

Sessions Munich 2022

Kacper Łukawski

k-NN on steroids – an introduction to approximate nearest neighbours

Kacper Łukawski, Qdrant

Alex Polyakov

Threat modeling and security assessment for ML models

Alex Polyakov, Adversa.AI

Andreas Bühlmeier

How Machine Learning is (becoming) creative

Andreas Bühlmeier, DBC Enterprice Intelligence

Aditya Gulgani

State-of-the-art in large scale recommender systems

Aditya Gulgani, Meta

Dr. Rachid Kherrazi

Why Security is Important in ML and How to Secure your ML-based Solutions

Dr. Rachid Kherrazi, AKKA Netherlands B.V.

Håkan Silfvernagel

Machine Learning on the Edge using TensorFlow Lite

Håkan Silfvernagel, Miles Oslo AS

Jon Bratseth

Vector embedding AI in production systems

Jon Bratseth, Yahoo

Dr. Tim Frey

How We Covered Concept Drifts In Time Series Forecasting For Public Transport

Dr. Tim Frey, iunera GmbH & Co. KG

Hauke Brammer

Kotlin? For Machine Learning?

Hauke Brammer, DeepUp GmbH

Michael Osterrieder

Dataset design for technically and legally clean ML development

Michael Osterrieder, vAIsual Inc

Laura Kölbl

Nature inspired optimization algorithms / Algorithm-based Staffing with Ant Colony Optimization

Laura Kölbl, MATHEMA GmbH

Hauke Brammer

Keep an eye on AI — Monitor ML models in production

Hauke Brammer, DeepUp GmbH

Dr. Pieter Buteneers

Self-supervised Learning: Teaching AI common sense

Dr. Pieter Buteneers, Sinch

Johannes Hötter

Greenfield and Brownfield Data Labeling – from Idea to Production with data-centric AI

Johannes Hötter, onetask.ai // kern.ai

Ioannis Tsamardinos

How AutoML can give companies, with few data scientists, a key advantage

Ioannis Tsamardinos, JADBio

Adrian Boguszewski

Optimize your network inference time as a data scientist, not as a web developer

Adrian Boguszewski, Intel

Nikolay Manchev

Underspecified pipelines: Why good models underperform in production

Nikolay Manchev, Domino Data Lab

Danilo Dresen

IoT Analytics at Scale – Customer based product development

Danilo Dresen, taod Consulting GmbH

Dorra Nouira

Using A.I to make recommendations for career progression

Dorra Nouira, Boostrs

Julien Schuermans

The unreasonable effectiveness of simple models

Julien Schuermans, ML6

Lisa Becker

The importance and pitfalls of pseudonymization

Lisa Becker, ML6

Lars Gregori

Honey, I shrunk the TinyML

Lars Gregori, SAP CX

Amit Bendor

Warning: this is not another MLOps best practices talk

Amit Bendor, Artlist

Dr. Christian Winkler

Introduction to Sentence Embeddings

Dr. Christian Winkler, datanizing GmbH

Sessions

MLCON The Event for ML Technologies & Innovations November 28 – December 2, 2022 | Berlin or Online

Sessions

MLCON
The Event for ML Technologies & Innovations
November 28 – December 2, 2022 | Berlin or Online