Considerations When Building Your ML Teams

Because I believe in the untapped potential in each and every one of us, I develop AI products to automate intelligent processes, offering people more space to unfold their greatest potential. With every AI solution I deploy, someone is given the opportunity to step up to their true potential.

Deena is a Lead Data Scientist at Bayer. Having received her MsC in Life Science Informatics at the University of Bonn, Deena worked as a Teaching and Research Assistant before joining Recogizer as a Data Scientist.

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.

Conversational AI Considerations

Dr. Carmen Martinez is a Conversation Analyst and Ethnographer of Communication working in Conversational Artificial Intelligence at FlixBus. As an expert in human-to-human conversation, she contributes to a cross-disciplinary team by automating customer service interactions, modelling both text- and voice-based human-to-machine conversations, and developing visual solutions for graphical and multimodal conversational agents. Carmen holds a PhD in Conversation Analysis and is the author of “Conversar en español: un enfoque desde el Análisis de la Conversación” published by Peter Lang Berlin.

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

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.

Building Blocks for Scalable AI Platforms

Programming with data since 1996. Focused on solving data driven problems. Generating insights by squeezing data sources. Loves IT and tools in the field of data analytics and data science.