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We invite Data Science experts to present and discuss topics relevant to the scope of Datalab. The seminar usually takes place every two weeks, on Wednesdays from 12:00-13:00 at the Winterthur Campus of ZHAW.

Future Events

Date Time&Place Speaker Title Abstract
Wed, 26.04. 12:00-13:00, TSO1.19 and Zoom Marcel Griesinger (ZHAW SML) Das neue Datenschutzrecht und seine Umsetzung in der Praxis, u.a. im Bereich KI Der Vortrag stellt die Entstehung und Inhalte des revidierten Datenschutzgesetzes (revDSG) vor und geht auf die spezifischen Umsetzungsanforderungen im Unternehmens- und Institutionsalltag ein. Zudem wird auf die aktuelle Praxis, u.a. auch im Bereich KI eingegangen.
Wed, 10.05. 11:00-12:00, TSO1.23 and Zoom Prof. Dr. Jan Dirk Wegner (UZH) Large-scale analysis of geospatial data with machine learning Worldwide analyses and estimates of vegetation parameters such as biomass or vegetation height are essential for modelling climate change and biodiversity. Traditional allometric approaches usually have to be adapted for specific ecosystems and regions. It is therefore very difficult to carry out homogeneous, global modelling with high spatial and temporal resolution and, at the same time, good accuracy. Data-driven approaches, especially modern deep learning methods, promise great potential here. In this talk, new research results on the large-scale determination of vegetation parameters will be presented.
Wed, 24.05. 11:00-12:00, TNE0.58 and Webex Dr. Cristiano Malossi (IBM Research) The Future of Visual Inspection for Civil Infrastructure We present an overview of our visual inspection technology that can be leveraged to conduct autonomous inspections of civil infrastructures, such as bridges, buildings, roads, and runways. We adapt existing AI models to work on high resolution images for detecting and segmenting very small defects in wide areas and with high precision. Further, we provide support to reliability engineers by additionally measuring these defects and by providing additional information that are required to assess their severity and required maintenance interventions. Throughout the talk we present a live DEMO of IBM One Click Learning (OCL). IBM OCL a research-industry platform that leverages deep learning and advanced computer vision methods to accelerate and improve accuracy in critical inspection tasks and aims at providing end-to-end support for the full data science process for inspectors and engineers.
Wed, 07.06. 11:00-12:00, TSO1.23 and Zoom Prof. Dr. Kurt Stockinger (ZHAW) Quantum Machine Learning – The Next Big Thing? Quantum computing is supposed to solve problems that were previously intractable with potential applications in machine learning, optimization, or drug design. Large companies such as Google, Microsoft or IBM are in the race to build the most powerful quantum computers. However, most questions concerning the potential of machine learning on quantum computers are still unanswered. Typical open questions are: How do we design and implement machine learning algorithms on a quantum computer? How well do current quantum machine learning algorithms work in practice? How do they compare with classical counterparts? In this talk we first give an overview of how quantum machine learning algorithms can be implemented on publicly available quantum computers. Next, we analyze how quantum machine learning can be used for solving small, yet practical problems. Afterwards, we perform an experimental analysis of kernel-based quantum support vector machines and quantum neural networks on five different datasets. Finally, we discuss the current limitations of quantum machine learning algorithms and how they could be tackled in the future.

Past Events (2023)

Date Speaker Title Slides
Wed, 12.04. Prof. Dr. Carolina Ruiz (Worcester Polytechnic Institute, USA) Predictive Deep Learning and Interpretation of Learned Representations for Human Sleep Modeling
Tue, 11.04. Dr Lilach Goren Huber (ZHAW IDP) Fault diagnostics in grid-scale solar plants: A playground for Physics-Informed machine learning
Wed, 01.03. Prof. Dr. Thomas Martinetz (Univ. Luebeck, D) Large deep neural networks do learn with small data sets  

Past Events (2022)


Speaker Title Slides

Wed, 23.11.

Prof. Dr. Benjamin Grewe (ETHZ/UZH) Why auto-encoding is not enough

Wed, 13.7.

Prof. Dr. Markus Melloh
(Victoria U of Wellington)
Work or study in New Zealand – Opportunities for ZHAW Data Scientists at Victoria University of Wellington PDF(PDF 10,6 MB)

Wed, 6.7.

Dr. Simon Bruderer
(Bruker BioSpin)
Deep learning for processing of nuclear magnetic resonance (NMR) data

Wed, 1.6.

Several 2nd International INODE EOSC Workshop

Wed, 2.3.

Sebastian Welter (IKEA) Scaling AI in Enterprises PDF(PDF 867,2 KB)

Wed, 16.2.

Prof. Dr. Volker Dellwo (UZH) Can speakers make themselves more recognisable?: Voice dynamics and its influence on voice recognition PDF(PDF 13,5 MB)

Wed 02.02.

Helmut Grabner (ZHAW) All Images are Equal but Some Images are More Equal than Others webcamaze.engineering.zhaw.ch

Past Events (2020)


Speaker Title Slides

Wed 02.12.

Pia Viviani
Citizen Science: What is it exactly and what are the challenges? PDF(PDF 3,4 MB)

Wed 21.10.

Daniel Neururer
On the Importance of time dependent features for Speaker Recognition PDF(PDF 10,1 MB)

Wed 09.09.

Raphael Weber, Mehmet Yesil, Prof. Dr. Ruedi Füchslin and Prof. Dr. Kurt Stockinger
Quantum Databases and Quantum Machine Learning – How Far Can We Go on a Publicly Available Quantum Computer? PDF(PDF 11,9 MB)

Wed 08.04.

Dr. Ricardo Chavarriaga
Presentation of the CLAIRE Office Switzerland PDF(PDF 8,9 MB)

Wed, 11.03.

Nicolas Schmid
Data-Driven Adaptive Controller Parameterisation: A Bayesian Optimization Approach PDF(PDF 4,5 MB)

Thu, 05.03.

Prof. Philipp Hungerländer
(Univ. Klagenfurt)
Propagation of vibroacoustic quality specifications in the automotive industry PDF(PDF 3,1 MB)

Wed, 26.02.

Ursin Brunner and Prof. Kurt Stockinger
Entity Matching with Transformer Architectures - A Step Forward in Data Integration Prezi

Wed, 29.01.

Prof. Kerrie Mengersen
(Queensland University of Technology QUT)
Bayesian Statistics in the Big Data Era  

Past Events (2019)


Speaker Title Slides

Wed, 18.12.

Prof. Dr. Luca Maria Gambardella
(Director of IDSIA, USI-SUPSI, Lugano)
Innovation through Artificial Intelligence PDF(PDF 4,3 MB)

Fri, 15.11.

PD Dr. Friedhelm Schwenker
(University of Ulm)
Artificial deep neural networks for multimodal emotion recognition PDF(PDF 17,3 MB)

Thu, 12.09.

Dr. Siavash Arjomand Bigdeli
Deep Density Approximation for Bayesian Image Restoration  

Fri, 09.08.

Prof. Haiwang Cao
(Zhengzhou University of Aeronautics, China)
AI application in safety support for civil airports  

Mon, 15.07.

Prof. Dr. Mark Sanderson
(RMIT University, Melbourne)
Conferences vs. journals in computer science  

Mon, 20.05.

Dr. Vasileios Trigonakis
(Oracle Labs Switzerland)
Introduction to Graph Processing (with PGX)