Are you into artificial intelligence and tech?
Come and join us at TECHNOPARK® Zürich for the next AI Use-Case talk.
AI experts will share insightful use cases. Learn about the technical challenges they faced and their solutions. After the keynotes, we will venture into an in-depth technical discussion.
Marc Tesch, CEO from LearnBI will speak about Industry 4.0 and how Predictive Maintenance minimizes expensive downtimes, saves costs and increases product quality.
Keynote “Produktivsetzung von komplexen Predictive Maintenance am Fallbeispiel “Sortieranlage der Schweizer Post”
Prof. Dr. Kevin Schawinski, CEO & Co-Founder of Modulos AG will talk about Automated Machine Learning.
Keynote “Automated Machine Learning: from cows to galaxies”
Dr. Mortiz Platscher, Senior Machine Learning Engineer of Acodis AG will talk about vast amounts of technical documents such as manuals, drawings and building plans.
Keynote “Structuring Information in Technical Documents – Challenges and Solutions”
On-site spaces are limited. Book your space by contacting the organizer directly at firstname.lastname@example.org.
See also our FLYER for more information!
We look forward to seeing you at the Use-Case Talk Series 2021!
Nadine Furrer and the Aspaara Team
The Expert Group will come together in September at the following location:
Trivadis AG, room Zuse, Sägereistrasse 29, 8152 Glattbrugg
The topics of discussion are as follows:
Methods of Statistical Disclosure Control applied on Microdata
Simon Würsten, SBB
Simon will talk about how he applied methods of anonymization on microdata, his experiences and possible complications regarding big data.
Big Data and AI Technologies on Microsoft Azure Cloud
Gerald Reif, IPT
Modern cloud providers enable powerful AI and Big Data technologies, platforms and tools. We will have a look at the underlying concepts and specific implementations and services on Microsoft’s Azure Cloud.
Reproducible Data Science
Luca Furrer, Trivadis
Luca will discuss the different aspects of a reproducible data science process and explain why he thinks the question of reproducibility should be considered for every AI project. Furthermore, he will present a set of open source tools which can be useful achieve reproducibility.
Organized by the Smart Services Expert Group
Open Government Data has the power to transform how organizations engage citizens but we have to wonder how accessible, usable, and shareable open data for the majority of people truly is? «Visualize» is a self-service interface that empowers users to explore open data based on smart defaults and design best practices.
Please register at: https://ch.xing-events.com/OpenGovernmentData
Online by Microsoft Teams, Participants get an access link after registration.
You can also find all relevant information in the flyer!
Smart Services supporting the new-normal
Following on from the Summit in 2020, where the focus was on digital as an enabler for smart services, this year
we want to focus on how Smart Services have allowed firms to adapt in the COVID-19 pandemic. Examples of
remote and collaborative working have created new forms of co-delivery where customers are integrated into the
service processes. Such a change requires a mindset change for more traditional firms as the service model
migrates from ‘do it for you’ to ‘do it yourself’ or some mix of ‘do it together’. Considering service science, the
switch makes perfect sense as it means that the full set of resources within the ecosystem are now being used
rather than only a part. Services can be delivered faster and at lower costs with the support of new technologies
and when working with the customer in a co-delivery mode. The changes are leading to new value propositions
and business models today and will lead to an evolution in Smart Services in the future. The changes themselves
must be understood, and we may need to consider new or different implementation and delivery models for
Smart Services. These new working approaches may also requite use to re-evaluate both training and education.
The summit in 2021 aims to assess new and emerging services that are enabled by technology and where the
services are co-delivered to support the emerging new-normal. In doing so, we hope to answer some of these
… how is the service quality impacted through digital technologies?
… how can you transform the customer (or a third-party) into a service partner?
… how does collaborative working impact value co-creation?
… what is the impact of smart services on customer experience?
… how does the nature of the service delivery change?
The pre-COVID19 context and the challenges faced should, where possible, be described so that the initial state
can be clearly understood. Although the focus will be on COVID-19 and its impact on Smart Services, papers on
emerging research on the full lifecycle (e.g, pre-sales, sales, delivery etc.) of Smart Services remain appreciated.
As with previous years, we are looking for early-stage research and will again publish the proceedings with
Springer. Furthermore, we will use industry to set the scene and the context from their position and follow them
with impactful academic presentations. We will have a physical summit in Zürich!
Hotel Belvoir (LINK)
8803 Rüschlikon, Zürich
Covid certificate will be checked, please see HERE
Prof. Dr. Shaun West, Hochschule Luzern, email@example.com
Dr. Jürg Meierhofer, ZHAW School of Engineering, firstname.lastname@example.org
Utpal Mangla, VP and Senior Partner in IBM Services
Smart Services; Industry4.0; Product-Service Systems; Value Co-creation; Service Quality; COVID-19; Service
Science; Service Design.
i. Write a short abstract: https://bit.ly/3u73P8O
ii. Short abstract submission: 16 July, 2021 to https://bit.ly/2S8kJ9L
iii. Notification of acceptance: 16 July, 2021
iv. Full paper submission: 31 August, 2021
Acceptance of papers is based on the full paper (up to 8 pages). All papers will be peer reviewed.
Proceedings from 2020
The proceedings from 2020 will be published in June 2021 (https://www.springer.com/gp/book/9783030720896).
The meeting will be physical only!
Location: Bern, https://suedland.ch/angebot/forum/
Rare events – a real pain in Machine Learning. How to detect, classify or predict an event you have rarely seen before?
Let’s learn and discuss with experts from natural hazards: earthquake, lightning, flooding and stock market crash.
A great lineup of top experts:
followed by a real Apéro