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Bing Li

Researcher at Technische Universität München

Publications -  120
Citations -  1233

Bing Li is an academic researcher from Technische Universität München. The author has contributed to research in topics: Computer science & Biochip. The author has an hindex of 19, co-authored 99 publications receiving 871 citations. Previous affiliations of Bing Li include National Tsing Hua University.

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Proceedings ArticleDOI

Aging-aware Lifetime Enhancement for Memristor-based Neuromorphic Computing

TL;DR: Experimental results demonstrate that the proposed co-optimization framework can extend the lifetime of memristor-based crossbars up to 11 times, while the expected accuracy of classification is maintained.
Proceedings ArticleDOI

TimingCamouflage: Improving circuit security against counterfeiting by unconventional timing

TL;DR: This paper proposes a method to invalidate the assumption that a netlist completely represents the function of a circuit, and forces attackers to capture delay information from manufactured chips, which is a very challenging task because it also introduces false paths.
Journal ArticleDOI

Columba 2.0: A Co-Layout Synthesis Tool for Continuous-Flow Microfluidic Biochips

TL;DR: In this paper, a module model library is proposed to accurately model microfluidic components involving layer interactions; and a co-layout synthesis tool, Columba, which generates AutoCAD-compatible designs that fulfill all designs rules and can be directly used for mask fabrication.
Proceedings ArticleDOI

Columba: co-layout synthesis for continuous-flow microfluidic biochips

TL;DR: This work proposes the first planarity-guaranteed architectural model, and the first physical-design module models for important microfluidic components, which have modelled the interactions between both control and flow layers, while reducing the design difficulty.
Proceedings ArticleDOI

Testing microfluidic Fully Programmable Valve Arrays (FPVAs)

TL;DR: A novel formulation using the concept of flow paths and cut-sets is presented, and an ILP-based hierarchical strategy for generating compact test sets that can detect multiple faults in FPVAs is described, demonstrating the efficacy of the proposed method in detecting manufacturing faults with only a small number of test vectors.