05 - 06 October 2022

Deep Learning Summit Deep Learning Summit schedule

Berlin AI Summit



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  • 08:00

    REGISTRATION & LIGHT BREAKFAST

  • 09:00

    WELCOME NOTE & OPENING REMARKS

  • LATEST ADVANCEMENTS IN DL

  • 09:15
    Srayanta Mukherjee

    What Have We Learnt About Deep Learning in 2022?

    Srayanta Mukherjee - Director - Data Science & AI - Novartis

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    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

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  • 09:40
    Walid Yassine

    Self-Supervised Learning for Unstructured Data

    Walid Yassine - Info & Comm Sys. Development - Airbus

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    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®)

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  • 10:05
    Sheraz Ahmed

    Research into DL

    Sheraz Ahmed - Senior Researcher - DFKI

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    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

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  • 10:30

    COFFEE BREAK

  • DEEP LEARNING LANDSCAPES

  • 11:00
    Dzhuliana Nikolova

    Deep Learning Models for Building Trusted Relationships

    Dzhuliana Nikolova - Co-Founder and CTO - OneUpOneDown

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    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

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  • 11:25
    Ameya Divekar

    What to Visualize for Training Reinforcement Learning Agents

    Ameya Divekar - Principle Data Scientist - Michelin

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    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

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  • 11:50

    Improving Data Quality with Automated AI

  • 12:15
    Aleksandra Kovachev

    Latest Research in Deep Learning

    Aleksandra Kovachev - Data Science Manager - Delivery Hero

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    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.

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  • 12:40

    LUNCH

  • MODEL ARCHITECTURE

  • 13:40
    Arindam Ghosh

    Getting the Most out of Vision Transformers

    Arindam Ghosh - Data Science Team Lead - Oviva

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    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.

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  • 14:05

    Implementing Real Time Anomaly Detection

  • 14:30
    Christoph Spohr

    Preparing your Data for DL

    Christoph Spohr - Lead Architect - Volkswagen AG

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    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.

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  • 14:55

    Case Study: ING

  • 15:20

    COFFEE BREAK

  • DL CONSIDERATIONS

  • 15:50
    Özlem Gürses

    Ethical, Legal & Cultural Considerations in Deep Learning

    Özlem Gürses - Professor - Kings College London

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    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

  • 16:15

    Panel: What are the Deep Learning Trends you Should Be Aware of?

  • Prokopis Gryllos

    PANELLIST

    Prokopis Gryllos - Senior Data Scientist - Shopify

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    Prokopis is a product-minded Data Scientist who enjoys Economics, Finance, and Algorithms

    Skills: data science, programming, product development, distributed systems Academic: statistics, machine learning, economics, game theory, social network analysis

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  • Rosona Eldred

    PANELLIST:

    Rosona Eldred - Machine Learning Engineer - BASF

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    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.

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  • Fabian Seipel

    PANELLIST

    Fabian Seipel - Lecturer - Deep Learning for Audio Event Detection - Technische Universitat Berlin

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

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  • 17:00

    NETWORKING RECEPTION

  • 18:00

    END OF DAY ONE

  • 08:00

    REGISTRATION & LIGHT BREAKFAST

  • 09:00

    WELCOME NOTE & OPENING REMARKS

  • APPLICATIONS IN DEEP LEARNING

  • 09:15

    Case Study: Music Recommendations at Amazon

  • 09:40

    Creating World Class Applications with Convolutional Neural Networks

  • 09:55
    Hendrik Woerhle

    Deep Learning for Smart Living

    Hendrik Woerhle - Lecturer - University of Applied Sciences and Arts Dortmund

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    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.

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  • 10:20
    Nima Siboni

    Reinforcement Learning

    Nima Siboni - Team Lead Machine Learning - Max Planck Institute

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    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

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  • 10:45

    COFFEE BREAK

  • NATURAL LANGUAGE PROCESSING

  • 11:15
    Roshan Amasa

    NLP Case Study

    Roshan Amasa - Lead Solutions Architect - Data & AI - Munich Re

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    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.

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  • 11:40
    Bernhard Pflugfelder

    NLP for Context Awareness

    Bernhard Pflugfelder - Head of Product AI - BMW

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    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.

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  • TOOLS FOR DEEP LEARNING

  • 12:05
    Alisson Machado

    Accelerating Distributed Model Training

    Alisson Machado - Senior Big Data DevOps Engineer - Schaeffler

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    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.

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  • 12:30

    LUNCH

  • 13:40

    Post-Pandemic NLP for a Touchless Society

  • 13:55
    Sergei Bobrovskyi

    Real Time Supervised Anomaly Detection

    Sergei Bobrovskyi - Data Scientist - Airbus

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    Real Time Supervised Anomaly Detection

    Dr. Sergei Bobrovskyi is a Data Scientist within the Analytics Accelerator team of the Airbus Digital Transformation Office. His work focuses on applications of AI for anomaly detection in time series, spanning various use-cases across Airbus. Prior to Airbus he worked on automated fraud detection for one of the largest e-commerce companies in Germany. Before that he was engaged in various research related positions in the space industry.

    Sergei holds a PhD in theoretical physics as well as a physics Diploma from the University of Hamburg. Besides physics he also studied philosophy with an emphasis on the philosophy of mind.

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  • 14:20

    Panel: The ROI of DL

  • 15:00

    END OF SUMMIT

Berlin AI Summit

Berlin AI Summit

05 - 06 October 2022

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