AI in the Sciences & Engineering

AI in the Sciences and Engineering

 

Navigating the frontiers of science and engineering, our research aims to seamlessly incorporate AI technologies to foster innovation and address emergent challenges. Drawing from a rich tapestry of fields including geospatial analytics and robotics, our goal is to build intelligent systems that harmonize with the intricate principles governing these domains. Through a data-driven approach, we aspire to enhance efficiency across various sectors, catalyzing a wave of progress characterized by precision and foresight.

In this endeavor, we have nurtured an intricate web of collaborations spanning numerous pivotal departments such as Civil, Environmental and Geomatic Engineering (D-BAUG), Biology (D-BIOL), Biosystems Science and Engineering (D-BSSE), Chemistry and Applied Biosciences (D-CHAB), Earth Sciences (D-ERDW), Humanities, Social and Political Sciences (D-GESS), Health Sciences and Technology (D-HEST), Computer Science (D-INFK), Information Technology and Electrical Engineering (D-ITET), Mathematics (D-MATH), Mechanical and Process Engineering (D-MAVT), and Physics (D-PHYS). This nexus of knowledge and innovation extends beyond ETH, fostering vibrant exchanges with professors from UZH, creating a thriving ecosystem that fuels the perpetual quest for knowledge and breakthrough innovations.

 

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Research topics include

  • Probabilistic Graphical Models
  • Spiking Neural Networks
  • Geospatial Computer Vision
  • Robotics and Control Systems
  • Neural Hardware Accelerators
  • Computational Fluid Dynamics
  • Data-Driven Solid Mechanics
  • Molecular Design with AI
  • Environmental Monitoring using Embedded Systems
  • Time Series Analysis and Prediction
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