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Alisson Machado

Senior Big Data DevOps Engineer


Accelerated Distributed Model Training

Alisson is the Senior Big Data DevOps Engineer at Schaeffler. An IT Specialist with over 9 years of experience in Linux Environments and Development.

Ameya Divekar

Principle Data Scientist


What to Visualize for Training Reinforcement Learning Agents

Leveraging reinforcement learning over continuous action spaces for autonomous system control. Leading Moonshots program for innovation bringing step change in value created at enterprise level using cutting edge AI technologies like NLP, Computer Vision and Deep Learning.

Expertise areas: Reinforcement Learning , GANs, Computer Vision, Natural Language Processing, Deploying ML Models, Amazon Web Services - S3, Lambda, EC2, Sagemaker, Azure ML

Patented technologies(applied) include : Staggered Pattern(CATIA), Semantic Painter (CATIA), Automatic Mate of Components using Machine Learning(Solidworks - filed), AI Driven Drawing Checker

Walid Yassine

Info & Comm Sys. Development


Self Supervised Learning For Unstructured Data

Walid is a Data Scientist at Airbus, and a techie turned AI/ML Engineer based in Germany. He brings a unique combination of technical expertise, active communication and natural critical thinking. He is currently working in three of the most critical areas of AI - Conversational, Computer Vision and Time Series Forecasting. He is also a Certified ScrumMaster® (CSM®)

Nima Siboni

Team Lead Machine Learning

Max Planck Institute

Reinforcement Learning

Nima in the Team Lead for Machine Learning at Max Planck Institute and AI-practitioner and experienced Simulation Scientist with focus on Complex Systems


Arindam Ghosh

Data Science Team Lead


Getting to Most out of Vision Transformers

Arindam Ghosh is a Data Science Lead at Oviva, a healthcare company who combine personalised care from a healthcare professional with unique digital tools to manage longterm health plans. He previously was a post-doctoral researcher at the University of Trento.

Roshan Amasa

Lead Solutions Architect - Data & AI

Munich Re

NLP Case Study: Munich Re

Roshan Amasa is the Lead Solution Architect of Data & AI at Munich Re, following previously working as a Data Science & Big Data Advisor for BMW Group.

Özlem Gürses


Kings College London

Ethical, Legal & Cultural Considerations in Deep Learning

Özlem Gürses is Professor of Commercial Law at King’s College London. She specialises in insurance and reinsurance law. Özlem is the author of Reinsuring Clauses (Informa), Marine Insurance Law (Routledge), Insurance of Commercial Risks (Sweet and Maxwell), and The Compulsory Motor Vehicle Insurance (Informa) as well as numerous articles published on insurance and reinsurance related topics. Özlem sits in the British Insurance Law Association Committee and the Presidential Council of the International Insurance Law Association (AIDA). She is Vice-Chair of the Reinsurance Working Party of AIDA. Özlem teaches insurance and reinsurance law at King’s College London and abroad, including National University of Singapore, University of Hamburg and World Maritime University, Malmö

Hendrik Woerhle


University of Applied Sciences and Arts Dortmund

Deep Learning for Smart Living

Hendrik is a Professor of Information Technology at the University of Applied Sciences and Art, and an expert in the application of artificial intelligence methods in embedded systems.


Sheraz Ahmed

Senior Researcher


Sheraz Ahmed is a Senior Researcher at Deutsches Forschungszentrum fur Kunstliche Intelligenz.

He has worked for a variety of different research institutes including the University of Western Australia, Osaka Prefecture University and Fraunhofer ITWM


Rosona Eldred

Machine Learning Engineer


Rosona is a Data Professional with 5 years of industry experience following an academic career in Mathematics culminating in a Max Planck research fellowship. Excels in collaborative teams with proactive independent contributors. Having worked with all parts of the ML life-cycle from requirements engineering to productionization, she is especially motivated by structural solutions to problems, by translating business potential to business value, getting promising prototypes effectively into production.

Fabian Seipel

Lecturer - Deep Learning for Audio Event Detection

Technische Universitat Berlin

Fabian is interested in audio related research fields such as virtual acoustics, spatial audio, music information retrieval, digital signal processing and machine learning.

Dzhuliana Nikolova

Co-Founder and CTO


Deep Learning Models for Building Trusted Relationships

Dzhuliana's primary focus and strengths are education and self-development which is how she ended up being a Co-founder and CTO at OneUpOneDown - a highly scalable AI mentor matching platform and framework that connects women worldwide with their perfect match

Srayanta Mukherjee

Director - Data Science & AI


What Have We Learnt About Deep Learning in 2022?

Srayanta is a Data Scientist and computational biologist with 10 years research experience, having worked a diverse spectrum of problems including predictive modeling and operations research.

He has extensive experience in machine learning methods and is a specialist in stochastic simulations, deep learning and decision trees.

His roles have included leading his team towards end-to-end data science solutions, achieved strategic milestones and drove adoption

Jesse Lehrke

Former Researcher

Freie Universitat Berlin

Jesse was previously a researcher at Freie Universitat Berlin, where he did project work for VW funded grant on state-business relations and Artificial Intelligence. Since then he has worked as a Digital Democracy Research Coordinator where he monitored the social media of elections and data science to counter disinformation and hate.

Samantha Edds

Senior Data Scientist


Sam Edds is a passionate leader with a successful track record in using statistics and data modeling to help organizations uncover insights and tell a story to grow their business. Her unique background spanning corporation, start-up, and non-profit settings has shown me the importance of supporting the people, products, and places that make up a community. As a Statistician with roots in International Studies and Development, she firmly believes in harnessing the power of big data to improve the livelihood of all through making more informed, data-driven decisions. While there is more analysis than ever before in the world, something endlessly important to business success, and which remains her focus, is using big data to tell a story and a vision all can grasp. She loves designing and building models to solve problems, and thrives on using her analysis to create a story that all clients (data focused or otherwise) can understand.

Kamel Nebhi

Applied Research Scientist ML/NLP

EF English First

Data Science professional with over 10+ years experience in Machine Learning and Natural Language Processing, delivering results in education, energy, finance and publishing industries.

Aleksandra Kovachev

Data Science Manager

Delivery Hero

Latest Research in Deep Learning

Aleksandra did her PhD in the area of complex networks with the goal of knowledge extraction by combining multiple data sources and diverse algorithms. She has passion in bioinformatics and improving health trough food and nutrition data. Currently she works as ML Engineer for the global food delivery service, Delivery Hero.

Bernhard Pflugfelder

Head of Product AI


NLP for Context Awareness

Bernhard Pflugfelder has 10+ experience in the in the fields of information retrieval, natural language processing (NLP), Big Data and AI. He worked across various businesses such as Information Services, Media and Automotive in very different setups and roles with startups, IT consultancy and industry companies.

After entering the Automotive with the Volkswagen Data:Lab, he is now already working over 5 years in Automotive. Currently, he is leading a NLP group in the BMW Group IT.

Bernhard's skills are quite diverse and focusing both technological and methodological solutions. He collected experience with Big Data, Advanced Analytics and Data Science as well as NLP and AI. He enjoys new challenges and is eager to learn more.

The most favorite area of Bernhard is NLP. Current development and dynamics in research and industry on NLP like for example Conversational AI or Neural Language Models are amazing and inspiring. Bringing those new technological and methodological opportunities into businesses is an important task of Bernhard in BMW Group.

Christoph Spohr

Lead Architect

Volkswagen AG

Preparing your Data for DL

Christoph Spohr is the Lead Architect of Big Data Platforms at Volkswagen following roles at both EPAM Systems and DATEV eG.