Robotics Engineer and Co-founder of Vicarious, Talentum, Ai Lab School, USA

Ivan Lozano is the founder and director of the Talentum.Space program where they help Mexicans work in the most innovative technology companies in the United States, as well as co-founder of the online school Ai Lab School. He also works as an engineer in Artificial Intelligence and robotics in Silicon Valley for the company Vicarious.com (Investors: Elon Musk, Jeff Bezos, Mark Zuckerberg, etc).

Co-founded IronDrone (500 Startups portfolio company). A platform to control drones over the internet, worked as a Software Engineer at Airspace in Silicon Valley being part of the Drone ai team to capture Drones. Ivan has been a speaker at technology conferences between Colombia, Europe, Mexico and the USA, in events such as PyCon, and Campus Party. In his spare time he likes to create and hack new things with Robots, VR and AI focused on solving social problems. As well as participating in hackathons and technology events (he is the first Latino to win the global Facebook hackathon F8 in 2019 at the Facebook Silicon Valley global event).

Session: Using a Drone to identify and rescue people in catastrophic situations

Using drones and neural networks to scan an affected area by a natural catastrophe (earthquake, hurricane, etc) may result in a powerful tool for rescue purposes, especially if the video could be analyzed by a trained neural network model, this talk is about how to use/implement this useful tool to: Scan affected area, stream video, identify people to be rescued, capture GPS location and create a logistic map for rescue.

Learning outcomes:

• Neural networks and object classificador with tensorflow.
• Drone control with Software API.
• Use and implementation of map features, waypoints, and GPS coordinates with interactive maps.
• Front end and back end development.

Additional information and programme of International Conference on Robotics, Automation & Artificial intelligence Systems – here

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Systems Engineer at SAS, Italy

With regard to the master’s degree obtained, I am particularly interested in decision-making statistics applied to real problems through data mining and the use of prediction models. During my internship period, I carried out a thesis on the treatment of missing data using parametric and Machine Learning algorithms. The bachelor and master’s degree allowed me strong knowledge of the areas of statistical application, highlighting the importance of quality and data management.

After graduation, I started working in SAS.

I work in the presale and consultancy teams that deal with advanced analytics issues.

In particular, my goal is to carry out statistical analyzes that cover the entire analytical life cycle for certain business problems dictated by the customers we follow.

Session: Image Analysis for Smart Cities

Use of Deep Learning algorithms that take real-time images from a camera as input to check the availability of parking in a certain area.

Additional information and programme of International Conference on Robotics, Automation & Artificial intelligence Systems – here

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Founder & CEO of beyond HMI//////, Germany

Peter Rössger is a professional keynote speaker in the area of technology, society, humans, and machines. This includes automotive human machine interfaces, user experience, and usability. Peter founder and owner of beyond HMI/////. We focus on creating knowledge on humans in autonomous driving, HMI concepts, usability and user experience for the automotive industry, the Industrial Internet, mobile machinery, and software applications. We perform studies on markets, cultures, usability and user experience. Our strategic market analysis gives deep insights into automotive markets, the future of mobility, usability and user experience trends and technologies. Target is to lift our clients to new levels of business, success, and satisfaction.

We use our knowledge to develop HMI concepts for our customers. This includes among others development of strategic options, team coaching, development of scenarios, user journeys, use case identification, interaction designs, and the roll out of specifications. Peter is Assistant Professor for Human Factors at the International School of Management, at the Hochschule Esslingen and the Joanneum Graz (Austria). In 2017 he received the certification as a Systemic Management Coach by the ICF.

Session: Who’s Leading? On the Relationship between Humans and Artificial Intelligence

Do artificial and intelligence go together? What is the relationship between us and humans and technology that is supposed to be intelligent? We are facing challenges in implementation, use, human-machine interface, and acceptance. The open issues will be discussed with a human centric view.

Learning outcomes:

• Put the human in focus for any technology including AI.
• AI does not exist, or does it?
• There are limits in application and realization.
• Apply professional knowledge on the human-machine relationship when using AI.

Additional information and programme of International Conference on Robotics, Automation & Artificial intelligence Systems – here

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Global AI Ethics and Regulatory Leader at EY (Ernst & Young), United Kingdom

Dr. Ansgar Koene is Global AI Ethics and Regulatory Leader at EY (Ernst & Young). He is also a Senior Research Fellow at the Horizon Digital Economy Research institute (University of Nottingham) where he contributes to the policy impact and public engagement activities of the institute and the ReEnTrust and UnBias projects As part of this work Ansgar has provided evidence to parliamentary inquiries, co-authored a report on Bias in Algorithmic Decision-Making for the Centre for Data Ethics and Innovation, and was lead author of a Science Technology Options Assessment report for the European Parliament on “a Governance Framework for Algorithmic Accountability and Transparency”.

Ansgar chairs the IEEE P7003 Standard for Algorithmic Bias Considerations working group, was the Bias Focus Group leader for the IEEE Ethics Certification Program for Autonomous and Intelligent Systems (ECPAIS), and participates in the IEEE standards P2089 “Age Appropriate Digital Services Framework” and IEEE P2863 “Governance of AI”. Other standards development work includes participation in the ISO/IEC JTC1 SC42 Artificial Intelligence activities and the CEN-Cenelec Focus Group for AI.

He is a trustee for the 5Rgiths foundation for the Rights of Young People Online and is part of the 5Rights Digital Futures Committee.

Ansgar has a multi-disciplinary research background, having worked and published on topics ranging from Policy and Governance of Algorithmic Systems (AI), data-privacy, AI Ethics, AI Standards, bio-inspired Robotics, AI and Computational Neuroscience to experimental Human Behaviour/Perception studies. He holds an MSc in Electrical Engineering and a PhD in Computational Neuroscience.

Session: Ethics and governance implications of AI

UA4DM an ideaation toolkit for AI ethics

In this session I will introduce the “UnBias AI For Decision Makers” (UA4DM) toolkit. A creative commons licensed critical systems thinking toolkit to help organizations explore how the introduction of AI systems fits with the ethos and values that the organization stands for. The toolkit can be used for planning, designing and developing an AI system, or to facilitate an assessment of compliance with ethical principles and regulatory requirements.

Learning outcomes:

• Lead a discussion with their colleagues about the strategy, governance and compliance implications of introducing AI systems into their organisation.
• Reflect on the organisational values and principles in relation to the practical impacts on AI on the use of Data, Technology and People within the organisation and beyond.
• Participants with gain a new, free to download, tool to help them plan through the requirements of future AI projects.
• Increase the ability of participants to confidently challenge AI working practices that are not compatible with the ethics and values of their organisation.

Additional information and programme of International Conference on Robotics, Automation & Artificial intelligence Systems – here

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Partner at 1D.works, Lithuania

Sarunas Simaitis started his career as a market research analyst and transitioned to artificial intelligence engineer which resulted in practical knowledge of a wide array of data techniques. While working with market research, he gained experience how to work with small amounts of data, simple metrics, extract and deliver insight to the clients. Moving into a data researcher tough how to work with large amounts of real-time user data. In his latest endeavour as an AI engineer, he is making the algorithms do the insight extraction and decisions in production.

Session: How to avoid pitfalls when deploying ML in production

A few things to keep in mind when deploying artificial intelligence in production

Deploying artificial intelligence-based solutions requires not only a change in tool stack but also a change in the business mindset. Just because machine learning software works in a specific case it does not necessarily mean that the result is meaningful. This talk is meant to elaborate on what tactical steps to take to make artificial intelligence work in real life.

Learning outcomes:

• See how we solved a real life problem with neural networks.
• Learn why and how to make the system transparent.
• Learn how to maintain an artificial intelligence system.
• Learn how to structure an artificial intelligence project.

Additional information and programme of International Conference on Robotics, Automation & Artificial intelligence Systems – here

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Robotics and AI Engineer, Switzerland

I am a Robotics and AI engineer with various experiences both in academia, tech companies and startup environments. These experiences allowed me to become proficient in transferring machine learning techniques from academia, where incredible state of the art methods are developed every day, into real world industrial and consumer applications.

Session: AI systems applied to industrial and consumer applications

In this talk I detail how advanced AI systems can be implemented in industrial and consumer applications, with concrete examples from my experience both in a B2B and B2C approach. I also talk in detail about the limitations of such systems with both speed, cost and energy consumption. Another innovative use case for machine learning systems is hardware reduction. This approach is a great way to cut costs while improving the performance of more conventional systems.

Learning outcomes:

• Learn how to link academia with industrial and consumer applications.
• Define advantages and limitations of AI systems.
• Learn the development process for production AI applications.
• Have real life examples of AI applied in industrial and consumer applications.

Additional information and programme of International Conference on Robotics, Automation & Artificial intelligence Systems – here

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Expert Business Consultant at KocDigital, Turkey

Session: International Conference on Robotics, Automation & Artificial Intelligent Systems

Creating value with demand planning in digital age

The rise of advanced analytics techniques providing insight about the future of complex systems creates a strong opportunity to manage supply chain management processes in a more data-driven and efficient way. By forecasting the future demand of customers, it is possible to optimize inventory and manage the replenishment process. In this presentation, we will explain the novel approaches in this field and share our field experience about the ways to create value in the supply chain by using advanced analytics techniques.

Learning outcomes:

• New techniques in demand forecasting.
• Inventory optimization.
• Advanced analytics in supply chain.
• How to apply machine learning in supply chain.

Additional information and programme of International Conference on Robotics, Automation & Artificial intelligence Systems – here

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Head of AI & Data Analytics at KocDigital, Turkey

Ozgur Akarsu is the head of AI & Data Analytics. He graduated from ITU Industrial Engineering and finished his PhD on HR Analytics in 2016. Ozgur has more than 15 years of experience in digital transformation and analytics in various industries. He also taught classes on machine learning, digital transformation and value chain management in several universities. He is specialized in machine learning and led several projects such as demand forecasting, HR analytics, predictive maintenance.

Session: International Conference on Robotics, Automation & Artificial Intelligent Systems

Creating value with demand planning in digital age

The rise of advanced analytics techniques providing insight about the future of complex systems creates a strong opportunity to manage supply chain management processes in a more data-driven and efficient way. By forecasting the future demand of customers, it is possible to optimize inventory and manage the replenishment process. In this presentation, we will explain the novel approaches in this field and share our field experience about the ways to create value in the supply chain by using advanced analytics techniques.

Learning outcomes:

• New techniques in demand forecasting.
• Inventory optimization.
• Advanced analytics in supply chain.
• How to apply machine learning in supply chain.

Additional information and programme of International Conference on Robotics, Automation & Artificial intelligence Systems – here

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CEO at Conversational Academy, Netherlands

Hans van Dam is co-founder and Dean of the Conversational Academy, world’s leading training

and certification institute for conversation designers. The Conversational Academy works with

brands like Walmart, JP Morgan, Google, ABN AMRO, and many others, to make their AI

Assistants more human-centric, helpful, and natural. Hans van Dam lectures at multiple

universities (VU, University of Nijmegen, Goldsmiths), and speaks often at conferences around

the world.

Session: Proven Conversation Design for Chatbots and Voice Assistants

Conversational Academy is world’s leading training institute for conversation design. In this session, you will learn a conversation design workflow that has proven itself around the world. This workflow is used by some of the world’s largest brands and it’s helping them unlock the potential of conversational AI technology. The workflow unifies an understanding of technology, psychology, and linguistics. It helps AI Assistants understand what people say and it helps people feel understood.

Learning outcomes:

• Understand the Conversation Design Workflow.
• Understand the role of the AI Trainer, Conversation Designer, and Conversational Expert.
• Learn Fundamental conversation design techniques.
• Learn advanced copywriting techniques.

Additional information and programme of International Conference on Robotics, Automation & Artificial intelligence Systems – here

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Future Phd Candidate at Université du Québec à Montréal (UQAM), Centre d’études sur l’intégration et la mondialisation de l’UQAM (CEIM), Canada

I hold a bachelor’s degree in public law, a master’s degree in international relations and another master’s degree in competitive intelligence. My specialization is international political economy which I analyse with a multidisciplinary approach: international law, international relations, competitive and strategic intelligence. International political economy studies the reciprocal and dynamic interaction in international relations between the accumulation of wealth and the pursuit of power. This discipline includes the study of new technologies, the internet and artificial intelligence in general and how these influence human and international relationships. I have written extensively on the development of private standards by private actors (companies, NGOs) individually, collectively or with the participation of state actors. Part of my work focused on the regulation of new technologies, the Internet and more particularly artificial intelligence.

Session: Regulations and test methods towards robot standards; Ethics of AI and autonomous technology; Human-Centred Social Robotics: Autonomy, Trust and Interaction Challenges

In our presentation, we will discuss about the different types of standards that are being established to regulate robots and IA. Next, we will describe and propose what should be the process of developing these standards and the actors involved in them. We will also present the issues related to the regulation of AI and robotics. Ultimately, successful regulation should reduce negative externalities and increase positive externalities. To do this, ethics must be at the heart of all efforts related to AI and robotics. This will be discussed in the presentation.

Learning outcomes:

• Know the different types of standards related to AI and robotics.
• Get an idea of what the process of developing these standards should be and who should be involved in it.
• Know the issues relating to the regulation of AI and robotics.
• Get an idea of the best practices to adopt to reduce negative externalities and increase positive externalities.

Additional information and programme of International Conference on Robotics, Automation & Artificial intelligence Systems – here

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