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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
21 - 30 of 60
- Intelligent Ultra Low-Power Signal Processing for AutomotiveFrom1 Nov 2020 → TodayFunding: H2020 - Skills and Career Development (Marie Skłodowska-Curie) actions
- System Architecture exploration for AI accelerator platformsFrom2 Sep 2020 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Enabling autonomous learning and decisioning in tiny devicesFrom2 Sep 2020 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Adaptive hardware for conditional neural networks with emerging technologiesFrom23 Sep 2019 → 23 Sep 2023Funding: Own budget, for example: patrimony, inscription fees, gifts
- Resource-Constrained Training of Deep Neural Networks for Industrial Computer Vision ApplicationsFrom30 Aug 2019 → 5 Dec 2023Funding: Own budget, for example: patrimony, inscription fees, gifts
- Algorithm-Hardware Co-Design for Adaptive Embedded Anomaly DetectionFrom1 Apr 2019 → 15 Mar 2023Funding: Own budget, for example: patrimony, inscription fees, gifts
- Modeling and Analysis for Efficient Hardware Mapping of Neural Network AlgorithmsFrom1 Oct 2018 → 10 Jan 2024Funding: Own budget, for example: patrimony, inscription fees, gifts
- Time is money : integrated circuit and system design towards low latency for real-time applicationsFrom1 Oct 2018 → 30 Sep 2022Funding: Fund Recuperation Fiscal Exemption, IOF - Industrial Research Fund
- Intelligent sensors for anomaly detection in harsh environments (ISAAC)From1 Oct 2018 → 31 Jan 2022Funding: Ministery of Economical Affairs
- Towards Heterogeneous Multi-core Systems-on-Chip for Edge Machine LearningFrom4 Sep 2018 → 2 May 2023Funding: Own budget, for example: patrimony, inscription fees, gifts
Publications
1 - 10 of 231
- Modeling and Analysis for Efficient Hardware Mapping of Neural Network Algorithms(2024)
Authors: Steven Colleman, Marian Verhelst
- 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
Patents
1 - 3 of 3