OpenTech AI Summit Switzerland

Lecture / talk | -

OpenTech AI Summit Switzerland

Organized by

Susan Malaika - STSM: Open Tech for Data AI - NoSQL, Hadoop, ODPi, Blockchain

Romeo Kienzler - human being

Keynote: Abdel Labbi - IBM Distinguished Engineer, A.I. Systems, IBM Research Zurich

Please find more information including the latest agenda on the link below:

https://developer.ibm.com/opentech/2018/04/24/zurich-may-2018-open-tech-ai-workshop/

Tentative Flow Monday May 28th: 8:30-11:00 Registration

9:00-12:00 Tutorials

9:00-12:00 PowerAI and OpenPOWER Bootcamp - Ganesan Narayanasamy 9:00-10:15 Node-Red & Watson APIs 101 - Yamini Rao 10:45-noon Accelerate Decisions in a Data-First World - Margriet Groenendijk 10:00-noon Visual Recognition on the edge with iOS Core ML - Yacine Rezgui & Sam Couch 10:00-noon Visually modelling neural networks for greater portability – Sean Tracey & Arlemy Turpault

noon-13:00 Lunch

13:00-13:45 Welcome by Christian Keller, CEO IBM Switzerland; Keynote by Distinguished Engineer Abdel Labbi;

13:45-14:30 Panel 14:30-15:15 Lightning Talks

Snap.ml: Accelerate machine learning workloads with high-speed training of popular machine learning models on modern CPU/GPU, for large data sets and/or real-time or close-to-real-time applications, Dr. Robert Haas, Department Head, Cloud and Computing Infrastructure, IBM Research - Zurich

Crail: Accelerate data processing workloads with high-performance distributed ephemeral store (open-source Apache incubator project), Dr. Robert Haas, Department Head, Cloud and Computing Infrastructure, IBM Research - Zurich

Deep Learning for Computer Graphics, Muzahid Hussain, University of Stuttgart

Robust 3D Pose Estimation of Humans and Objects for Augmented Reality, Bugra Tekin, EPFL

From neurons to roads - machine learning for detection of curvilinear structures, Agata Mosinska, EPFL

Automatised Prediction of Convolutional Neural Networks Performances without training across multiple different datasets, Roxana Istrate, IBM Research

Learning to Find Good Correspondences, Eduard Trulls, EPFL

Geodesic Convolutional Shape Optimization, We train Geodesic Convolutional Neural Networks to emulate a fluidynamics simulator. This lets us introduce a new type of surrogate models to optimize aerodynamic shapes, which is more flexible, more powerful and more scalable than previous approaches, Pierre Baqué, EPFL

privacy-preserving ML ("Privacy-Preserving Classification with Secret Vector Machines"), Robert West, EPFL

Revisiting Arithmetic for AI, Babak Falsafi, ecocloud, EPFL

15:15-15:45 Break

15:45-16:30 Panel

16:30-17:00 Final Keynote & Next Steps - Romeo Kienzler

17:00-17:30 Refreshments and Networking

17:30-20:00 Meetup