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Researcher
Marian Verhelst
- Disciplines:Nanotechnology, Sensors, biosensors and smart sensors, Other electrical and electronic engineering, Design theories and methods
Affiliations
- Electronic Circuits and Systems (ECS) (Division)
Member
From1 Aug 2020 → 30 Sep 2022 - ESAT - MICAS, Microelectronics and Sensors (Division)
Member
From1 Dec 2007 → 31 Jul 2020 - Department of Electrical Engineering (ESAT) (Department)
Member
From1 Oct 2003 → 30 Nov 2007
Projects
1 - 10 of 60
- Explore chiplet-based processors that can be easily integrated together / tiled in a heterogeneous wayFrom29 Apr 2024 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Bringing generative AI to edge devices through interoperable heterogeneous compute coresFrom5 Mar 2024 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Lifelong-Learning Electronic Systems: edge-devices that get smarter day-by-day [LifeLinES]From1 Jan 2024 → TodayFunding: BOF - Methusalem
- Digital in memory compute for low energy biomedical machine learning applicationsFrom23 Nov 2023 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Scalable large array nanopore readouts for proteomics and next-generation sequencingFrom2 Oct 2023 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Efficient scheduling and compilation of embedded multi-core AI platformsFrom1 Sep 2023 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Efficient multi-core processor design for heterogeneous AI workloadsFrom7 Aug 2023 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Outplaying the hardware lottery for embedded AIFrom1 Jun 2023 → TodayFunding: Horizon Europe - European Research Council (ERC)
- System-Technology Co-optimization for enablement of MRAM-based Machine LearningFrom25 May 2023 → 7 Mar 2024Funding: Own budget, for example: patrimony, inscription fees, gifts
- Design Automation and Exploration for Energy Efficient Machine Learning SoCs and ChipletsFrom31 Jan 2023 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
Publications
1 - 10 of 227
- Resource-Constrained Training of Deep Neural Networks for Industrial Computer Vision Applications(2023)
Authors: Robby Neven, Toon Goedemé, Marian Verhelst, Tinne Tuytelaars
- Microelectronics for Microbiology(2023)
Authors: Peishuo Li, Marian Verhelst
- The “Eagle” Approach To Train Electrical Engineers With Collaborative Problem-Solving Skills(2023)
Authors: Merijn Van Deyck, Martijn Deckers, Abdul Saboor, Pouya Mehrjouseresht, Zhenda Zhang, Arne Symons, Alexander Bodard, Marian Verhelst, Alexander Bertrand, Ruth Vazquez Sabariego, et al.
Number of pages: 14 - An Online-Spike-Sorting IC Using Unsupervised Geometry-Aware OSort Clustering for Efficient Embedded Neural-Signal Processing(2023)
Authors: Georges Gielen, Francky Catthoor, Marian Verhelst
- Design Space Exploration of Deep Learning Accelerators(2023)
Authors: Linyan Mei, Marian Verhelst
- Ultrasound In-Body Communication: Channels, Modems and Hardware for Ultrasound In-Body Communication Links(2023)
Authors: Thomas Bos, Wim Dehaene, Marian Verhelst
- An End-to-End Dual ASIC OFDM Transceiver for Ultrasound In-Body Communication(2023)
Authors: Marian Verhelst, Wim Dehaene
Pages: 664 - 673 - COAC: Cross-Layer Optimization of Accelerator Configurability for Efficient CNN Processing(2023)
Authors: Steven Colleman, Marian Verhelst
Pages: 945 - 958 - Towards Heterogeneous Multi-core Systems-on-Chip for Edge Machine Learning(2023)
Authors: Vikram Jain, Marian Verhelst, Peter Karsmakers
- CNN-based Robust Sound Source Localization with SRP-PHAT for the Extreme Edge(2023)
Authors: Marian Verhelst
Patents
1 - 3 of 3