A representative list of research projects of our group.
IAI is an Innosuisse project, funded under the joint call in which partners from South Korea and Switzerland are invited to collaborate. At the Swiss side of the consortium, our team collaborates with ABB, a pioneering technology leader with a vivid interest and a profound knowledge in predictive maintenance. The South Korean side of the ... Read more
- RAWFIE (Road-, Air-, and Water- based Future Internet Experimentation) is a project funded by the European Commission (Horizon H2020 program) under the Future Internet Research Experimentation (FIRE+) initiative that aims at providing research facilities for Internet of Things (IoT) devices. The DMML team has been involved in the RAWFIE project since early 2015 and delivered ... Read more
- MEDInA is an Innosuisse project, enabling the creation of low cost IoT self-adaptive Machine Learning based applications by developing an Artificial-Intelligence-as-a-Service (AIaaS) framework. Current work by the DMML team includes partnering with SixSq in order to develop an AI solution that runs on edge devices such as a Raspberry Pi 4, providing traffic volume information ... Read more
- Within this project we seek to develop machine learning methods for the modelling of pathological human locomotion. This is a collaborative Sinergia project funded by the Swiss National Science Foundation.
- OrbiLoc is an Innosuisse project in which the Data Mining and Machine Learning (DMML) group collaborates with the company Orbiwise. The goal of this project is to improve the localization accuracy achieved by IoT devices utilizing the LoRa network of Orbiwise. In the context of this project, DMML introduces machine learning techniques for localization, achieving ... Read more
- SMELL is an Innosuisse project undertaken with collabration with the company Firmenich. The goal of the project is to develop a data-driven methodology which will allow us to uncover the olfactory perception mechanisms related to perfume creation and exploit them to build rational solutions that improve product performance and differentiation. We designed and developed novel ... Read more
We proudly present our partners, with whom we have collaborated in numerous research projects, offering an applied machine learning approach in solving real world problems. If you are interested in a collaboration, do not hesitate to contact our team.
The members of our group have been to various prestigious institutions for internships, during which they've sharpened their skills and expertise.
Magda Gregorova, IBM Research, June - September 2015
Jason Ramapuram, Apple AI research, June - September 2017, January - March 2019
Amina Mollaysa, Alan Touring Institute, August - September 2018, September - October 2019
Lionel Blonde, Apple AI research, June - September 2019
Jason Ramapuram, Deep Mind, December 2019 - March 2020