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Group of Computer Architecture / AGRA | Computer Science | Faculty 03 | University of Bremen

Timo Laudi, M.Sc.


The goal of my research is to enable informed design-phase decisions that improve the energy efficiency and performance of machine learning models across different hardware platforms. By analyzing potential bottlenecks early on, applications can be made more resource-efficient from the start.

Research Staff

+49 421 218-63942

MZH 4220

tlaudi@uni-bremen.de

Hardware Agnostic Energy Benchmarking For Machine Learning
Author: Timo Laudi, Rolf Drechsler
Workshop: Methoden und Beschreibungssprachen zur Modellierung und Verifikation von Schaltungen und Systemen (MBMV)
Pdf | Reference: Würzburg, Germany, 2026

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