Mehdi Tahoori

Professor and Chair

Karlsruher Institut für Technologie

Germany

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About

Professor Mehdi Tahoori serves as the Chair at the Karlsruher Institut für Technologie, Germany. His research areas focus on printed electronics, neural networks, and silicon lifecycle management, as evidenced by his recent publications. Notable works include advancements in electronic design, analog circuits, and innovative testing methods for deep neural networks.

Articles (20)

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2022

Collaborators (6)

Chenyun Pan

The University of Texas at Arlington

UNITED STATES

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Mahta Mayahinia

Karlsruhe Institute of Technology

GERMANY

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Lorena Anghel

Université Grenoble Alpes

FRANCE

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Kostas Siozios

Associate Professor

Aristotle University of Thessaloniki

GREECE

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Vincent Meyers

Karlsruhe Institute of Technology

GERMANY

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Dimitrios Soudris

Professor

National Technical University of Athens

GREECE

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Mehdi Tahoori

Research Interests

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About

Articles (20)

PRINT-SAFE: Printed Ultra-Low-Cost Electronic X-Design with Scalable Adaptive Fault Endurance

System Scenario-Based Design of the Last-Level Cache in Advanced Interconnect-Dominant Technology Nodes

Neural Evolutionary Architecture Search for Compact Printed Analog Neuromorphic Circuits

Enabling Printed Multilayer Perceptrons Realization via Area-Aware Neural Minimization

Silicon Lifecycle Management (SLM): Requirements, Trends, and Opportunities

Leveraging Neural Trojan Side-Channels for Output Exfiltration

Compressed Test Pattern Generation for Deep Neural Networks

Asymmetric and Adaptive Error Correction in STT-MRAM

Efficient Analog Error Correction for Printed Unary-Encoded Computing

Interconnect/Memory Co-Design and Co-Optimization Using Differential Transmission Lines

Co-Design of Approximate Multilayer Perceptron for Ultra-Resource Constrained Printed Circuits

Model-to-Circuit Cross-Approximation For Printed Machine Learning Classifiers

SpinBayes: Algorithm-Hardware Co-Design for Uncertainty Estimation Using Bayesian In-Memory Approximation on Spintronic-Based Architectures

Fault-Tolerant Neuromorphic Computing With Memristors Using Functional ATPG for Efficient Recalibration

NeuroScrub+: Mitigating Retention Faults Using Flexible Approximate Scrubbing in Neuromorphic Fabric Based on Resistive Memories

New Approaches of Side-Channel Attacks Based on Chip Testing Methods

SpinDrop: Dropout-Based Bayesian Binary Neural Networks With Spintronic Implementation

Graphene-Based Interconnect Exploration for Large SRAM Caches for Ultrascaled Technology Nodes

Active and Passive Physical Attacks on Neural Network Accelerators

A Spintronic 2M/7T Computation-in-Memory Cell

Collaborators (6)

Chenyun Pan

Mahta Mayahinia

Lorena Anghel

Kostas Siozios

Vincent Meyers

Dimitrios Soudris

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