Speakers
Oct 1st -Where are we with Automation - a reality check
Carl Lindberg
AI Innovation Sweden
Entrepreneur and an Associate Professor in Mathematical Statistics. He has co-founded Sigmastocks, a high-profile fintech company, and also runs a company which develops new approaches to teaching math. At present, Carl is designing and building the Data Factory of AI Innovation of Sweden, with the goal of turning it into a Netflix of AI. Carl has been working with developing the mathematics behind AI and Data Science for almost 20 years. PhD and Associate Professorship from Chalmers.
Shafiq Urréhman
CEVT
Senior Technical Expert and Tech lead AI/ML - He is Technical lead for all AI and machine learning related project at CEVT (China Euro Vehicle Technology AB). Has 15 years of experience as CTO for AI/ML/Technical projects in mining, automotive, forestry, communication, assistive and medicine. Been working as Associate Professor and Director of i2lab at Umeå University and and Associate Professor at Linköping University and founder/Team lead of intelligent systems group at UEL, UK
Henrik Lind
Smart Eye
Henrik has been working with sensing and the functions for advanced driver assistance systems in different sensor and functional roles at Volvo and Volvo Cars since 1997. It has been a long and successful journey from option systems to standard systems as of today. He is currently leading the research and AI Labs group at Smart Eye paving the way into AI land.
Sasko Cuklev
Volvo Trucks
Today Sasko is leading the commercial part of the Autonomous solutions development projects aiming at delivering unique customer experiences. He has an extensive experience within the automotive industry and the different mega processes (especially Product Development) and has actively worked with business development, innovation, business analysis, project management, process design, tool implementations, training, coaching and consulting assignments.
Harri Santamala
Sensible4
Harry has experience and expertise in international project launch and coordination related to automotive. Bringing together partners from different industry and cultural backgrounds. Financing and technical support. People person, networker, public speaker. Has skills in merging academic knowledge with practical appliance.
Mats Nordlund
Zenuity
Director Research. Has a unique background and network derived from executive positions in academia and industry in Europe, USA, and Russia. Spent 15y in industry, first as Director of Technology Strategy and Acquisition at Saab AB corporate technology, and later as Director of R&D for Emerson Process Management – Level and Marine. Has a background from MIT and served 3y as VP of Research Programs at Skoltech, Moscow Russia – a key component of the Russian Federal Economic Modernization Program.
Oct 2nd - Managing AI threats on business and society
Sofia Serafimovska
SAM Management
Sofia is a management Consultant with the Passion for management by means and technology with +10 years’ experience from truck & bus, semiconductor and production industry. By focusing on a common way of thinking and attention for work and people we challenge organizations to excellence.
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​The importance of Data Quality and Governance for DAIR (Data and AI Ready) enterprises
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Where to start?
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Where to gain most impact and how to gain sustainability by working upstream in small-scale improvement cycles?
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Holistic view of the cross-functional needs
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Data Governance Strategy Top-down vs Bottom-up
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2 steps forward, 1 step back – “failure” is always a part of winning
Lars Tornberg
Volvo Cars
Senior Machine Learning Engineer and Data Scientist at Volvo Car Group with demonstrated history of working in both industry and academia. Proficient in simulation, mathematical modelling, data- and numerical analysis with current focus on machine learning methods in the automotive industry. Strong operations professional with a PhD in quantum computing from Chalmers University of Technology.
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Machine Learning vs Software development –
Verification & validation challenges
Peter Nordin
Semcon
Peter Nordin has a Ph.D. in Computer Science at University of Dortmund (1997). His current research includes commercial robotic software. Nordin is well know for his many contributions to evolutionary computation, including its use for robots, induction of mathematical proofs, and speech and vision recognition.
Atif Kureishy
Teradata
VP – Global Emerging Practices | AI & Deep Learning at Teradata, a business outcome-led global analytics consultancy. Based in San Diego, Atif specializes in enabling clients across all major industry verticals, through strategic partnerships to deliver complex analytical solutions built on machine and deep learning. His teams are trusted advisors to the world’s most innovative companies to develop next-generation capabilities for strategic data-driven outcomes in areas of AI and deep learning.
Olle Häggström
Chalmers
Professor of mathematical statistics in 2000. He has more than 80 peer reviewed publications, mainly in probability theory. At present he serves on the Scientific council for natural and engineering sciences at VR (Swedish Research Council), and is head of the mathematical statistics division at Chalmers’ and University of Gothenburg’s joint Department of Mathematical Sciences.
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AI risk, AI safety, AI ethics
Oct 2nd - How to collaborate and exploit AI
Erik-Wilhelm Graef Behm
Business Region Göteborg
Mr Erik-Wilhelm Graef Behm MSc, Industrial Engineering & Management, Area & Investment Manager ICT at Business Region Göteborg Responsible for Inward Investment as well as cluster development in the area of ICT. Board member of cluster organizations related to Microwaves, Electronics, Broadband.
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AI in West Sweden and the Gothenburg Region – Overflow of the Ecosystem
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How does the Ecosystem of AI in the region look?
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Are there any players missing?
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What can we see next?
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Helena Iremo
Scania Group
Lead Mobile Design
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Connected safety - How can AI and fashion help the exposed profession of truck drivers become safer?
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What’s the problem we are facing?
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What’s the solution using AI?
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What’s the product?
Ola Boström
Veoneer
VP Research, Innovation and IPR. Ola with 24 years of experience in traffic safety research is passionate about creating trust in mobility, the purpose of the Autoliv spinoff Veoneer.
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​Vehicle and Infrastructure Collaboration Challenges and Opportunities considering:
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Traffic scenario edgecases (sudden ODD changes)
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Connectivity coverage (expected to not be full)
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Vulnerable Road Users (connected and not connected)
Edvard Brinck
Ericsson
Director Portfolio Development - Strategic portfolio development and key partner responsibility towards Ericsson´s key Automotive & Transport industry partners. Resulting in new portfolio assets in the areas of: Safety and Driver Assisted features for highly Automated & Autonomous Driving and AI, Human Machine Interaction and Connectivity are fields of innovatio.
​Vehicle and Infrastructure Collaboration Challenges and Opportunities considering:
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Traffic scenario edgecases (sudden ODD changes)
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Connectivity coverage (expected to not be full)
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Vulnerable Road Users (connected and not connected)
Erik Tengedal
Imagimob
VP Sales
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​Connected safety - How can AI and fashion help the exposed profession of truck drivers become safer?
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What’s the problem we are facing?
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What’s the solution using AI?
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What’s the product?
Robert Valton
Volvo Group
Director Advanced Analytics & Visualization. Robert is a passionate value creator, business builder and digital doer in the new technology space with focus on IoT/Connectivity, Advanced Analytics and AI. He has +20-years’ experience of delivering value in B2B and B2C- both as intrapreneur and entrepreneur. Proven ability to take an idea to commercial launch with focus on customer experienced value. Experience from building and managing highly skilled cross functional teams across globally.
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​The journey to unleash the value of data with AI!
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Every company sits on a data goldmine – waiting for the value to be unleashed!
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Data driven exploration in combination with cross-functional collaboration, domain knowledge and data science skills will accelerate the value
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Practical example how AI can transform data into insight and real value
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Daniel Reimhult
Volvo Group Connected Solutions
​The journey to unleash the value of data with AI!
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Every company sits on a data goldmine – waiting for the value to be unleashed!
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Data driven exploration in combination with cross-functional collaboration, domain knowledge and data science skills will accelerate the value
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Practical example how AI can transform data into insight and real value
Hans Salomsson
EmbeDL
Hans is the CEO of EmbeDL - a Chalmers AI spin-off focused on bringing AI from R&D to products. He has experience from both industry and academia developing Machine Learning and Deep Learning algorithms solving challenging problems - from Automated Trading to Sub-Nuclear Physics. Hans manages several EC H2020 and Vinnova financed research projects in the field of AI.
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​Creating a cost and time efficient development process for advanced AI in embedded systems. Good tooling and strategic collaborations are a necessity to deliver competitive AI products. In this talk we will cover:
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How does the AI development process look like for embedded AI systems?
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Where are the opportunities for tools and collaborations?
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What should be done in-house vs outsourced?
Ulrich Wurstbauer
Luxoft
Received his PhD in physics at the University of Regensburg. After a post-doc at the Columbia University in the City of New York, he continued in R&D in industries focusing on closing the gap between software- and hardware-driven developments in automotive and space industries. He and his teams have been working on projects around the topic digital and real twin of products which are already or in the near-future embedded in cyber-physical systems.
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Developing environmental model with ML from the ground truth data and scaling it in the cloud
Significant and challenging transformation activities are necessary when it comes to development of next generation of ADAS and autonomous use-cases. Based on a number of long-lasting customer engagements, we will share our experiences and use-cases in the area of environmental model development with ML, starting with the ground truth data. We will review different approaches to handling required large amounts of data in the cloud, as well as agile and data-driven processes that need to be established.