Deep Learning Summit Deep Learning Summit schedule

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

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®)

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

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

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

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.

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.

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.

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

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

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