Track / Overview

Presented posters:

AI & Cities

City Sense – Chidubem Iddianozie, University College Dublin

Automated Feature Detection From Property Imagery Data – Bailey Griswold, New York University, Center for Urban Science and Progress

Automated Detection of Street-Level Tobacco Advertising Displays – Isha Chaturvedi, New York University

Learning how to plan healthier cities with precise data – andrea salmi, CEAT EPFL

Supervised model for building occupancy prediction from electrical consumption data – Marina Dorokhova, EPFL STI IMT PV-LAB

AI & Computer Systems

MULDER: Unsupervised Anomaly Detection for Streaming Applications – Lewis Tunstall, SPOUD AG

Coordinate Descent with Bandit Sampling – Farnood Salehi, EPFL

AI & Environment

AEMS - energy management for SMEs – Nicola Thorn, AND Technology Research

Learning to Benefit from Flexible Energy Consumption on a Small Grid – Nicole Ludwig, Karlsruhe Institute of Technology

Reducing Food Waste with Computer Vision in 24 hours – Arnout Devos, EPFL

Learning to find Mountains – Rocio Nahime Torres, Politecnico di Milano

Building envelope and energy system retrofit via Artificial Neural Networks – Emmanouil Thrampoulidis, Urban Energy Systems Lab, Empa Dübendorf

Leveraging large-scale physics-based simulations to improve immediate response after earthquakes – Xavier Bellagamba, QuakeCoRE

Risk Estimation of Extreme Windstorms – Raphaël de Fondeville, EPFL

Image Segmentation for Solar Panel Placement – Philipp Jackmuth, dida Datenschmiede GmbH

AI & Health

Smartphone-based Acoustic Breath-phases Detection for Real-time Biofeedback Breathing Training – Chen-Hsuan (Iris) Shih, ETH Zürich | Center for Digital Health Intervention - HealthIS Lab

Stroke Classification Using Deep Learning – Lisa Herzog

Machine learning algorithms on multi-layer architecture to process hidden information for systems medicine applications – Adriana Haulica, Bioclinome

Deep Learning for Classification of Non-Small Cell Lung Cancer histologic subtypes – Elvis Murina, ZHAW

Open standards for deployment, storage and sharing of predictive models – Svetlana Levitan, IBM

Deep Learning-Based Human Activity Recognition for Continuous Activity and Gesture Monitoring for Schizophrenia Patients with Negative Symptoms – Florian Lipsmeier, F. Hoffmann-La Roche Ltd

Deep learning for outcome prediction in breast and colorectal cancer – Dmitrii Bychkov, University of Helsinki

BrainFlow: scalable processing, modelling, and inference for neuroimaging data – Mazen Fouad A-Wali Mahdi, Siemens Healthcare

Data Fusion in CNNs for Real-Time Pollen Particle Identification – Predrag Matavulj, BioSense Institute
Model (PHREND) for personalized prediction of treatment response in relapsing remitting multiple sclerosis (RRMS)
– Federica Lionetto, PwC Switzerland

Predicting thyroid dysfunction with machine learning – Opetunde Adepoju, Ladoke Akintola University of Technology

AI & Industry

WatchNet: Efficient and Depth-based Network for People Detection in Video Surveillance Systems – Michael Villamizar, Idiap Research Institute

Multi-Scale Sequential Network for Semantic Text Segmentation and Localization – Michael Villamizar, Idiap Research Institute

Trajectory Tracking Optimization with Gaussian Processes – Samuel Balula, ETHZ

Cogito Instruments – Örs Málnási-Csizmadia, Cogito Instruments

A smart Entity Resolution: empower unsupervised machine learning to harmonize customer data lakes – Marco Venturini, EY

Smart Manufacturing: Monitoring of Tool Wear using Machine Learning Methods – Markus Rokicki, L3S Research Center

A machine learning driven approach for reducing customer returns in the microelectronics industry : on-wafer anomaly detection – Amalia Spataru, Melexis

Prediction vs. understanding with Random Forest – Mireille Moser, Nestlé

Extracting Reliable Topics Using Topic Model Ensembles – Stephan Sahm, Data Reply GmbH

AI & Language

Easy Review Sentiment Analysis with pandas and scikit-learn – Arnout Devos, EPFL

Comparing Insights Derived Using Manual Inductive Qualitative Analysis Versus Automated NLP Algorithms for Analyzing Differences in User Feedback in Digital Randomized Experiments – Mary Hu, Microsoft

End-to-end accented speech recognition improvement through multi-task learning – Thibault Viglino, EPFL

A Comparison of Machine Learning Models to Predict the Outcome of Swiss Federal Votes Using the Text of the Official Voter Pamphlets – Daniel Müller, stellus.ch

Chinese Sentiment Analysis using Deep Learning Techniques – Vincent Lee, Logitech Europe

An Interface for Scientific Knowledge Retrieval, Adaptation and Citation – Nikola I. Nikolov, Amine M'Charrak, Onur Gökce, Jonathan Prada, Richard H. R. Hahnloser, ETH Zurich

Effects of Lombard Reflex on Deep-Learning-Based Audio-Visual Speech Enhancement Systems – Daniel Michelsanti, Aalborg University

Document-Level Neural Machine Translation with Hierarchical Attention Networks – Lesly Miculicich, Idiap

Asynchronous Training of Word Embeddings for Large Text Corpora – Jan-Hendrik Zab, L3S

AI & Networks

Three Degrees of Chess Domination – Eric Malmi, Google

varrank: an R package for variable ranking based on mutual information with applications to observed systems epidemiology – Gilles Kratzer, Zurich University

A Simple Algorithm for Scallable Monte Carlo Inference – Maksym Byshkin, Università della Svizzera italiana

AI & Society

Towards responsible AI – Eva Thelisson

AI & Transportation

Vision Based Baggage Property Extraction – Aljoscha Steffens, Filament Consultancy Group

AI & Trust

Asynchronous Byzantine Machine Learning (the case of SGD) – Georgios Damaskinos, EPFL

Gait recognition via deep learning of the center-of-pressure trajectory: A proof-of-concept study for biometric applications – Philippe Terrier, Hôpitaux Universitaires de Genève

General

A Day In The Life: A Realistic Dataset for Modeling Human Vision – Jenny Hamer, University of California, San Diego

CancelOut: Feature Selection & Models Interpretability in Deep Learning – Vadim Borisov, University of Tuebingen

Improving Information Extraction from Images with Learned Semantic Models – Stephan Baier, Data Reply

AI Watch – Blagoj Delipetrev, European Commission Joint Research Centere

Open-dict Keyword Spotting from Speech – Niccolo' Sacchi

High-Precision Privacy-Preserving Function Evaluation – Marius Vuille, inpher

The HyperBagGraph DataEdron: An Enriched Browsing Experience of Scientific Publications – Xavier Ouvrard, UniGe / CERN

Joint Localization and Classification of Multiple Sound Sources Using a Multi-task Neural Network – Weipeng He, Idiap Research Institute

AMLD EPFL 2019 / Tracks & talks

AI & Environment

Mikhail Kanevski, Vasily Demyanov, Sylvain Coutu, Maria Schönholzer, Walter Jetz, Grant van Horn, Saman Halgamuge, Antonino Marvuglia, Dan Assouline, Bojie Sheng, Sebastian Sippel, Alexis Berne, Michele Volpi, Maxim Samarin

13:30-17:00 January 2809:00-12:30 January 293BC

AI & Cities

Mohamed Kafsi, Cristina Kadar, Alex “Sandy” Pentland, Valentine Goddard, Daniel Gatica-Perez, Piotr Mirowski, Niklas Goby, Christopher Nowzohour, Stephen Goldsmith

13:30-17:00 January 284BC

AI & Computer Systems

Kevin Smeyers, Michael Papamichael, Andreas Moshovos, Hadi Esmaeilzadeh, Svetlana Levitan

09:00-12:30 January 294BC

AMLD / Global partners