Karthik Ganesan

Bio: Karthik Ganesan is an academic researcher from Stanford University. The author has contributed to research in topics: Decoding methods & Low-density parity-check code. The author has an hindex of 12, co-authored 24 publications receiving 519 citations. Previous affiliations of Karthik Ganesan include Central Salt and Marine Chemicals Research Institute & University of California, Berkeley.

Factors affecting household satisfaction with electricity supply in rural India

Abstract: Electricity is an important component of socio-economic development, but most studies of household electricity access focus exclusively on the presence or absence of a connection Here we reach beyond connectivity by examining the relationship between various dimensions of the quality of electricity supply and a household’s subjective satisfaction with their electricity or lighting situation Studying the results from a survey of 8,568 households in six large, energy-poor states from northern, central and eastern India, we find that household satisfaction responds strongly to the average hours of electricity available on a typical day The positive effect of increasing the number of hours per day by one standard deviation on satisfaction is almost as large as that of electrifying a non-electrified household These findings underscore the importance of moving from counting electricity connections to enhancing the quality of electricity supply Electricity is a fundamental aspect of socio-economic development Urpelainen et al survey 8,568 households in rural India and find that the average hours of available electricity is an important factor in household satisfaction with supply, whereas reliability and voltage stability are less important

TPAD: Hardware Trojan Prevention and Detection for Trusted Integrated Circuits

Abstract: There are increasing concerns about possible malicious modifications of integrated circuits (ICs) used in critical applications. Such attacks are often referred to as hardware Trojans. While many techniques focus on hardware Trojan detection during IC testing, it is still possible for attacks to go undetected. Using a combination of new design techniques and new memory technologies, we present a new approach that detects a wide variety of hardware Trojans during IC testing and also during system operation in the field. Our approach can also prevent a wide variety of attacks during synthesis, place-and-route, and fabrication of ICs. It can be applied to any digital system, and can be tuned for both traditional and split-manufacturing methods. We demonstrate its applicability for both application-specified integrated circuits and field-programmable gate arrays. Using fabricated test chips with Trojan emulation capabilities and also using simulations, we demonstrate: 1) the area and power costs of our approach can range between 7.4%–165% and 7%–60%, respectively, depending on the design and the attacks targeted; 2) the speed impact can be minimal (close to 0%); 3) our approach can detect 99.998% of Trojans (emulated using test chips) that do not require detailed knowledge of the design being attacked; 4) our approach can prevent 99.98% of specific attacks (simulated) that utilize detailed knowledge of the design being attacked (e.g., through reverse engineering); and 5) our approach never produces any false positives, i.e., it does not report attacks when the IC operates correctly.

Activation of ganglion cells and axon bundles using epiretinal electrical stimulation

Abstract: Large-scale multielectrode recording and stimulation were used to test how selectively retinal ganglion cells can be electrically activated without activating axon bundles A novel method was devel

QVZ: lossy compression of quality values

Abstract: MOTIVATION Recent advancements in sequencing technology have led to a drastic reduction in the cost of sequencing a genome. This has generated an unprecedented amount of genomic data that must be stored, processed and transmitted. To facilitate this effort, we propose a new lossy compressor for the quality values presented in genomic data files (e.g. FASTQ and SAM files), which comprise roughly half of the storage space (in the uncompressed domain). Lossy compression allows for compression of data beyond its lossless limit. RESULTS The proposed algorithm QVZ exhibits better rate-distortion performance than the previously proposed algorithms, for several distortion metrics and for the lossless case. Moreover, it allows the user to define any quasi-convex distortion function to be minimized, a feature not supported by the previous algorithms. Finally, we show that QVZ-compressed data exhibit better performance in the genotyping than data compressed with previously proposed algorithms, in the sense that for a similar rate, a genotyping closer to that achieved with the original quality values is obtained. AVAILABILITY AND IMPLEMENTATION QVZ is written in C and can be downloaded from https://github.com/mikelhernaez/qvz. CONTACT mhernaez@stanford.edu or gmalysa@stanford.edu or iochoa@stanford.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Energy Harvesting Wireless Communications: A Review of Recent Advances

Abstract: This paper summarizes recent contributions in the broad area of energy harvesting wireless communications. In particular, we provide the current state of the art for wireless networks composed of energy harvesting nodes, starting from the information-theoretic performance limits to transmission scheduling policies and resource allocation, medium access, and networking issues. The emerging related area of energy transfer for self-sustaining energy harvesting wireless networks is considered in detail covering both energy cooperation aspects and simultaneous energy and information transfer. Various potential models with energy harvesting nodes at different network scales are reviewed, as well as models for energy consumption at the nodes.

Towards precision medicine

Abstract: Precision medicine is a strategy for tailoring clinical decision making to the underlying genetic causes of disease. This Review describes how, despite the straightforward overall principles of precision medicine, adopting it responsibly into clinical practice will require many technical and conceptual hurdles to be overcome. Such challenges include optimized sequencing strategies, clinically focused bioinformatics pipelines and reliable metrics for the disease causality of genetic variants.