Collaborations

Projects

A representative list of research projects of our group.

• Automated Bridge Defect Recognition

  Infrastructure assets, such as bridges, need to be inspected regularly. Our objective is to reduce the need for human involvement, minimize risks to health and safety, decrease the impact of subjective engineering assessments, digitize asset management, and promote sustainable inspection practices. By achieving these goals, we aim to develop optimal maintenance strategies for infrastructure assets, ... Read more

• MIGRATE – A Multidisciplinary and InteGRated Approach for geoThermal Exploration

  To mitigate climate change, our society must reduce its carbon footprint coming from fossil fuel energies and favor green energy solutions instead. Geothermal energy is a resource this available in abundance. However, the development of this sector is hindered by the insufficient subsurface information, resulting in high exploration risks. To overcome these obstacles and enrich ... Read more

• Interpretable Condition Monitoring for Complex Engineering Systems

  Just as it is important for us to monitor our own body in order to maintain good health, we should have an accurate understanding of the state of engineering systems in order to prevent failures. In this project, entitled "Interpretable Condition Monitoring for Complex Engineering Systems", we investigate machine learning methods to build a condition ... Read more

• EO4EU: AI-augmented ecosystem for Earth Observation data accessibility with Extended reality User Interfaces for Service and data exploitation

  A vast amount of Earth Observation (EO) data is produced daily and made available through online services and repositories. Contemporary and historical data can be retrieved and used to power existing applications, to foster innovation and finally improve the EU citizens’ lives. However, an undersized audience follows this activity, leaving huge volumes of valuable information ... Read more

• LiBertaS: Enhancing Location Based Services by tackling the market barrier of costly data collection requirements of fingerprinting positioning systems

  LiBertaS aims to liberate the access of Location Based Services (LBS) to the highly accurate fingerprinting methods in business practice, by greatly downscaling the data volume needed for their operation. Location Based Services (LBS) have recently undergone a tremendous increase in popularity. Despite the proven superiority of the fingerprinting methods in terms of localization accuracy, ... Read more

• Eratosthenes: Deep generative modeling for indoor and outdoor positioning with fingerprinting methods

  Eratosthenes is a research project funded under the Spark funding scheme of the Swiss National Science Foundation (SNSF). The aim of the Spark is to fund postdoctoral researchers to implement "projects that show unconventional thinking and introduce a unique approach". The relevant criteria for the award of Spark grants are the originality/novelty of the idea, the unconventionality of the proposed research project, the ... Read more

• IAI: Industrial Artificial Intelligence for intelligent machines and manufacturing digitalization

  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

  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: sMart EDge fabric for Iot Applications

  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

• SimGait: Modeling pathological gait resulting from motor impairments

  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. Read more

• 1
• 2
• >>

---

Partners

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.

---

Internships

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