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Datalab-Seminar

Introduction

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, 1.6. 10:00-12:15 Online (Zoom) Register Several 2nd International INODE EOSC Workshop “Intelligent Open Data Exploration” (INODE) is an EU project, funded under Horizon 2020 (http://www.inodeproject.eu/). The mission of INODE is to develop a unified, effective platform that provides extensive access to open datasets through natural language queries for a wide range of users from larger scientific communities to the public. The INODE solution is demonstrated in three significant use cases in the fields of Cancer Biomarker Research, Research and Innovation Policy Making, and Astrophysics. Motivation: This workshop aims at bringing EOSC members to provide an insight into the INODE system, while integration and exploitation of INODE services will be promoted by EOSC-Future. Structure of the workshop: The workshop will provide a comprehensive view on the current research status of INODE and how the INODE consortium is getting ready for the challenges ahead, till the completion of the INODE project in April 2023. Short presentations from the INODE use case providers will be intertwined with short demos from technical teams.

Past Events (2022)

Date Speaker Title Slides
Wed, 2.3. Sebastian Welter (IKEA) Scaling AI in Enterprises PDF
Wed, 16.2. Prof. Dr. Volker Dellwo (UZH) Can speakers make themselves more recognisable?: Voice dynamics and its influence on voice recognition PDF
Wed 02.02. Helmut Grabner (ZHAW) All Images are Equal but Some Images are More Equal than Others webcamaze.engineering.zhaw.ch

Past Events (2021)

Date Speaker Title Slides
Wed, 17.11. Prof. Dr. Christoph von der Malsburg How can kids learn so much faster than transformers? Recording PDF
Wed, 8.9. Prof. Nicolaj Stache (HS Heilbronn) From Simulation to Reality using Reinforcement Learning PDF
Wed, 25.8. Prof. Macro Gori (U Siena) Learning to See by Motion Invariance PDF
Wed, 23.6. Lukas Tuggener (ZHAW CAI) Is it Enough to Optimize CNN Architectures on ImageNet? PDF

Past Events (2020)

Date Speaker Title Slides
Wed 02.12. Pia Viviani
(catta.ch)
Citizen Science: What is it exactly and what are the challenges? PDF
Wed 21.10. Daniel Neururer
(ZHAW)
On the Importance of time dependent features for Speaker Recognition PDF
Wed 09.09. Raphael Weber, Mehmet Yesil, Prof. Dr. Ruedi Füchslin and Prof. Dr. Kurt Stockinger
(ZHAW)
Quantum Databases and Quantum Machine Learning – How Far Can We Go on a Publicly Available Quantum Computer? PDF
Wed 08.04. Dr. Ricardo Chavarriaga
(ZHAW InIT)
Presentation of the CLAIRE Office Switzerland PDF
Wed, 11.03. Nicolas Schmid
(ZHAW IAMP)
Data-Driven Adaptive Controller Parameterisation: A Bayesian Optimization Approach PDF
Thu, 05.03. Prof. Philipp Hungerländer
(Univ. Klagenfurt)
Propagation of vibroacoustic quality specifications in the automotive industry PDF
Wed, 26.02. Ursin Brunner and Prof. Kurt Stockinger
(ZHAW InIT)
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)

Date Speaker Title Slides
Wed, 18.12. Prof. Dr. Luca Maria Gambardella
(Director of IDSIA, USI-SUPSI, Lugano)
Innovation through Artificial Intelligence PDF
Fri, 15.11. PD Dr. Friedhelm Schwenker
(University of Ulm)
Artificial deep neural networks for multimodal emotion recognition PDF
Thu, 12.09. Dr. Siavash Arjomand Bigdeli
(CSEM)
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)