Our mission

Our mission is to develop state-of-the-art machine learning models that can scale to real-world problems while being energy-efficient. These models will be based on core design principles of sparsity and asynchrony and take inspiration from biology/neuroscience.

Research projects

• EVENTS (Energy-efficient distributed sensor-systems for machine vision: event-based distributed AI algorithms) started in October 2022 as part of the funding program "BMBF - OCTOPUS - Electronic systems for trustworthy and energy-efficient decentralised dataprocessing in edge-computing". The grant aims to develop efficient general-purpose AI algorithms that can be adapted for deployment on energy-efficient neuromorphic systems for computer vision. The project consortium led by TU Dresden will implement and test the algorithms developed at INI, RUB on innovative neuromorphic hardware in various pilot applications. For more information see: the EVENTS project website.
• ESCADE (Energy-Efficient Large-Scale Artificial Intelligence for Sustainable Data Centers) started in May 2023. The aim of the project is to develop state-of-the art large, distributed and energy-efficient machine learning models for complex applications such as natural language processing.

We are hiring!

We are looking for excellent and highly motivated PhD students to join the group.  If you are interested please hand in inqueries at: https://anandsubramoney.com/apply.html