Artificial Intelligence & Machine Learning Conference 2022 takes place in the Norwegian capital Oslo.
Industrial companies are currently in a tight squeeze between emissions requirements, efficiency gains, and also the ever-higher production costs. With digital solutions, we seek answers to the challenges, but the amount of data also increases with increased digitization. We know the insights are there in a mountain of data, but finding them can be like looking for a needle in a haystack.
How companies can use AI to gain insight, and how we can scale from proof of concept to operations is the theme of this year’s Artificial Intelligence & Machine Learning Conference.
We will focus on practical operational use of a potential high-flying technical opportunity, which is on everybody’s lips nowadays.
The conference is not only a meeting place, most importantly, you will also catch inspiring talks. We will cover the development of AI-applications with emphasis on use cases from our industries. We are just as eager to learn about the less effective use-cases as we are to hear the success stories.
A lot of our large industrial players will share their experiences, and they will also inform us on their way forward. What is for instance the answer to the question: How can Artificial Intelligence & Machine Learning bring their business further?
AI with purpose – scalable, sustainable & industrial-grade
Bernd «Benno» Blumoser | Head of AI Lab | Siemens AG
How Yara implement energy optimization tool and scale across their ammonia plants
Yongyos Kaewpitakkun | Yara International ASA
Factory to the cloud - our experience with utilizing AI
Torbjørn Saltkjelvik | GC Rieber VivoMega AS
Cloud-based virtual flow metering system powered by a hybrid physics-data approach for water production monitoring
Roberto Iberra | Cognite AS
From WWTP to WRRF - Can the water service fee be reduced with machine learning?
Hilde Johansen | Veas AS
Bad Data Analytics - examples of how you can overcome the challenges of real-world data
Eivind R. Eide | Kongsberg Digital AS
Operationalizing ML & AI models at Borregaard
Martin Forsberg Lie | Borregaard AS
Panel discussion: «Data Scientist vs. Data Citizens»
Chair: Bertil Helseth, Intelecy | Benno Blumoser, Siemens AG | Alexander Østebø Høiby, Yara International ASA | Martin Forsberg Lie, Borregaard AS
End of the Day
Conference dinner at the restaurant Lorry
Data-centric AI with Industrial Knowledge Graphs: How Semantics-oriented Data Readiness enhances AI at Siemens
Veronika Haderlein-Høgberg | Siemens AG
How a pragmatic approach to MLOps put machine learning models into everyday use at Aker BP
Peder Aursand | Aker BP
Deep Learning/AI (Velux case)
Marcus Glifford | SICK AS
COGNITWIN - Cognitive plants through proactive self-learning hybrid digital twins
Adriaen Verheyleweghen | Cybernetica AS
Lessons Learned from Implementing Machine Learning in an Industrial Context – Case study of carbon anode core temperature measurements
Andreas Simskar Wulvik | Idletechs AS
Experience from AI in the Control Room, A Case study
Bjarne André Asheim | Kairos Technology AS
Scaling predictive maintenance in heavy asset industries
Karan Rajagopalan | Cognite AS
Deep Learning on point clouds for infrastructure inspection
Ahmed Mohammed | SINTEF
Benno Blumoser | Head of AI Lab | Siemens AG
Bernd «Benno» Blumoser is Co-founder and Head of the Siemens AI Lab, which serves as co-creation platform for exploration of Industrial AI. Being organizationally embedded in Siemens’ Munich-based Technology division, where around 100 experts drive its «Data Analytics & AI» research hub, it acts as Open Innovation platform where business stakeholder and domain experts are matched with AI researchers to jointly gain further orientation in the vast field of AI opportunities.
Veronika Haderlein-Høgberg | Senior Researcher | Siemens AG
Veronika Haderlein-Høgberg is Senior Researcher with the Semantics & Reasoning (SMR) Team at Siemens AG. The SMR-team serves as a strategic consulting and sounding board for the various Siemens Business Units and their respective CTO-offices regarding the development of end2end-services in Data Management, Data Architecture, Data Readiness and Machine Learning. In this role, the SMR works on projects, tools and infrastructure to help the Siemens Business Units enable their customers in leveraging their data for increased automation and efficiency.
Yongyos Kaewpitakkun | Senior Data Scientist | Yara International
Yongyos Kaewpitakkun is a senior data scientist in the Digital production team at Yara International. He has a Ph.D. in AI / Machine learning and many years of hands-on experience leveraging machine learning, computer vision, and natural language processing models to solve challenging business problems.
Alexander Høiby | VP Digital Production | Yara International ASA
Alexander leads the Digital Production unit in Yara International ASA. Yara established the unit to further improve the operations across Yara’s global production site network. Today, Digital Production is building an industry leading enterprise data platform (on AWS). On top of the platform, the team develops or buys & integrates digital products in close collaboration with production sites – always focused on solving real operational problems.
Andreas Simskar Wulvik | Managing Director | Idletechs AS
Andreas works as Managing Director of the software company Idletechs AS that specializes in solutions for the process industry that combine data-rich sensors, such as IR cameras, with transparent machine learning and domain knowledge. By combining these three it is possible to gain a much deeper understanding of process states and product quality than before, and thus these solutions support near real time information that can be used for better control and optimization.
Peder Aursand | Senior Data Scientist | AkerBP
Peder Aursand is a senior data scientist who leads a multi-disciplinary team developing, deploying and maintaining machine learning models for interpreting subsurface data as part of Aker BPs digital umbrella EurekaX. In this role he is responsible for the full life cycle of machine learning from prototype to everyday use, including implementing and executing a pragmatic but effective approach to MLOps.
Adriaen Verheyleweghen | Senior Control Engineer | Cybernetica AS
Studied MSc (siv.ing.) in Chemical Engineering at NTNU 2010-2015, with specialization in Process Systems Engineering.
Master thesis on the topic of “Modelling and Optimization of a Two-Stage Refrigeration Cycle” with Prof. Johannes Jäschke as supervisor
PhD in the same group at NTNU 2015-2020
PhD thesis: “Control Degrees of Freedom for Optimal Operation and Extending Remaining Useful Life”
Work in Cybernetica AS as Senior Control Engineer from 2019-present, developing model-predictive control applications
Mostly worked with various applications for AkerBP and NMPC installations on their Ivar Aasen platform
Karan Rajagopalan | Senior Data Scientist | Cognite AS
I’m a senior data scientist at Cognite AS, Oslo. I’m a part of the Strategic Customer Services organization responsible for delivering value to the customers through our trademark product cognite data fusion (CDF). I’ve background in communication systems & signal processing and possess rich experience over a decade in analyzing data and generating insights from various industrial domains such as wind, aviation and manufacturing.
19.10.22 - 20.10.22
Thon Hotel Slottsparken Wergelandsveien 5 0167 Oslo
Thon Hotel Slottsparken, phone number: 23 25 66 00
Exhibition / logo
Logo in the program:
Members kr. 6 000,-
Non members kr. 8 500,-
Exhibition is not available at this conference!
Bernt Eldor | Kairos Technology AS (Chair) David Anisi | NMBU Bertil Helseth | Intelecy AS Frank Rørtvedt | Siemens AS Marianne Ytterbø | Yara Norge AS Karin Sundsvik | NFEA Tonje Olsen | NFEA
HERE you will find NFEAs Terms for cancellation and refund
Language: If possible prepare the written presentations in English. Each individual speaker may decide whether they wish to speak Norwegian or English, however the preferred language is English.
DOWNLOAD THE NFEA MULTI-EVENT APP
The app is available in Appstore and Googleplay and it is named NFEA. Use the same email as you used to register for the conference to log in. In the App you`ll find list of participants, program, sponsors and eventually also PDF version of those lectures we are permitted to share. PS: The same app will also apply if you participate at other NFEA conferences. List of participants: each participant can choose to hide their identity in the app. The app for this event will be available aprox. 2 weeks before the event starts
Comments from the evaluation of last years conference:
Overall good event. Really interesting lectures about AI in the industry.
Amazing list of speakers and lecture. Well planned and enjoyed the dinner and lunch session.
Nice event with interesting topics. Good food.
Everything was very good
In general, how satisfied are you with the event? Average score: