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Merge pull request #274 from neural-loop/profile-formatting
Profile formatting - internal linking
2 parents a4241e0 + 66c8126 commit b80be4c

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content/contributors/alexander-henkes/index.md

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His current research focuses on spiking neural networks (SNN). Recently, he published a preprint on nonlinear history-dependent regression using SNN. This enables SNN to be used in the context of applied mathematics and computational engineering.
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He is a contributor of [snnTorch](https://github.com/jeshraghian/snntorch).
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He is a contributor of [snnTorch](/neuromorphic-computing/software/snn-frameworks/snntorch/).

content/contributors/bernhard-vogginger/index.md

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social: []
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Bernhard Vogginger is a research associate at TU Dresden working on neuromorphic computing software and applications in the lab of Prof. Christian Mayr. He currently leads the software development for the SpiNNaker2 neuromorphic system and has co-authored the [Neuromorphic Intermediate Representation](https://github.com/neuromorphs/nir). Further research interests include radar processing and sustainability of AI and data centers.
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Bernhard Vogginger is a research associate at TU Dresden working on neuromorphic computing software and applications in the lab of Prof. Christian Mayr. He currently leads the software development for the [SpiNNaker2](/neuromorphic-computing/hardware/spinnaker-2-university-of-dresden/) neuromorphic system and has co-authored the [Neuromorphic Intermediate Representation (NIR)](/workshops/neuromorphic-intermediate-representation/). Further research interests include radar processing and sustainability of AI and data centers.

content/contributors/carlos-ortega-otero/index.md

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Dr. Carlos Ortega-Otero is an Sr. Research Staff Member at IBM driven by a passion in Circuit Design, Neuromorphic Chip Architectures, Low-Power Circuits and Physical Design optimizations. He earned his Ph.D. from Cornell University under the guidance of Prof. Rajit Manohar.
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Throughout his career, he has worked in groundbreaking projects, including Ultra-Low Power Asynchronous Sensor Network nodes, Medical Implantable Wireless Sensors, The TrueNorth Brain-Inspired Chip, and the NorthPole Project. At IBM, Carlos works under the leadership of Dr. Dharmendra Modha in the Brain-Inspired Computing Group.
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Throughout his career, he has worked in groundbreaking projects, including Ultra-Low Power Asynchronous Sensor Network nodes, Medical Implantable Wireless Sensors, The [TrueNorth](/neuromorphic-computing/hardware/truenorth-ibm/) Brain-Inspired Chip, and the [NorthPole Project](/blog/northpole-ibm-neuromorphic-ai-hardware/). At IBM, Carlos works under the leadership of Dr. Dharmendra Modha in the Brain-Inspired Computing Group.
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He plays key roles in Architecture, Specification, Digital Implementation, Physical Design, Timing Signoff, and Manufacturing teams of the NorthPole Project. Carlos is proud to be part of the Brain-Inspired Computing Group at IBM that continues to shape the future of Integrated Circuits and AI.

content/contributors/charlotte-frenkel/index.md

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To achieve these goals, she is investigating both the bottom-up and the top-down design approaches, as well as their synergies.
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She is the designer of the [ODIN](https://github.com/ChFrenkel/ODIN) and [ReckOn](https://github.com/ChFrenkel/ReckOn) open-source online-learning digital neuromorphic processors.
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She is the designer of the [ODIN](/neuromorphic-computing/hardware/odin-frenkel/) and [ReckOn](/neuromorphic-computing/hardware/reckon-frenkel/) open-source online-learning digital neuromorphic processors.

content/contributors/fabrizio-ottati/index.md

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His main interests are event-based cameras, digital hardware design and automation, deep learning and piedmontese red wine.
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He is the maintainer of two open source projects in the field of neuromorphic computing, [Tonic](https://tonic.readthedocs.io) and [Expelliarmus](https://expelliarmus.readthedocs.io).
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He is the maintainer of two open source projects in the field of neuromorphic computing, [Tonic](/neuromorphic-computing/software/data-tools/tonic/) and [Expelliarmus](/neuromorphic-computing/software/data-tools/expelliarmus/).

content/contributors/felix-bauer/index.md

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title: "github"
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Felix Bauer is a neuromorphic engineer working on cutting-edge algorithms and chips at [SynSense](https://www.synsense.ai/). He co-authored the [Neuromorphic Intermediate Representation](https://github.com/neuromorphs/nir) and has published work on GPU-accelerated spiking neural networks via the [Sinabs](https://sinabs.readthedocs.io/) simulator, neuromorphic control and brain-machine interfaces.
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Felix Bauer is a neuromorphic engineer working on cutting-edge algorithms and chips at [SynSense](https://www.synsense.ai/). He co-authored the [Neuromorphic Intermediate Representation (NIR)](/workshops/neuromorphic-intermediate-representation/) and has published work on GPU-accelerated spiking neural networks via the [Sinabs](/neuromorphic-computing/software/snn-frameworks/sinabs/) simulator, neuromorphic control and brain-machine interfaces.

content/contributors/gregor-lenz/index.md

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His main interests are event cameras that are inspired by the human retina and spiking neural networks that mimic human brain in an effort to teach machines to compute a bit more like humans do. At the very least there are some power efficiency gains to be made, but hopefully more! Also he loves to build open source software for spike-based machine learning.
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He is the maintainer of two open source projects in the field of neuromorphic computing, [Tonic](https://github.com/neuromorphs/tonic) and [expelliarmus](https://github.com/open-neuromorphic/expelliarmus).
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He is the maintainer of two open source projects in the field of neuromorphic computing, [Tonic](/neuromorphic-computing/software/data-tools/tonic/) and [expelliarmus](/neuromorphic-computing/software/data-tools/expelliarmus/).

content/contributors/jason-eshraghian/index.md

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His research focuses on brain-inspired circuit design to accelerate AI algorithms and spiking neural networks.
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He is the maintainer of [snnTorch](https://github.com/jeshraghian/snntorch).
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He is the maintainer of [snnTorch](/neuromorphic-computing/software/snn-frameworks/snntorch/).
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title: "Kade Heckel"
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description: "Researcher focusing on high-performance computing for neural networks (JAX, Pallas). Creator of Spyx, a JAX-based spiking neural network library."
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image: "kade-heckel.jpeg" # To be replaced with "kade-heckel.jpg" or similar
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image: "" # To be replaced with "kade-heckel.jpg" or similar
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- icon: "fa-brands fa-github"
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link: "https://github.com/kmheckel"
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title: "github"
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Kade Heckel is a researcher and developer focusing on high-performance computing for neural networks, with expertise in JAX and related optimization tools like Pallas. He is the creator of Spyx, a JAX-based spiking neural network library.
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Kade Heckel is a researcher and developer focusing on high-performance computing for neural networks, with expertise in JAX and related optimization tools like Pallas. He is the creator of [Spyx](/neuromorphic-computing/software/snn-frameworks/spyx/), a JAX-based spiking neural network library.

content/contributors/luuk-van-keeken/index.md

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Luuk van Keeken is a researcher/PhD student at KTH Royal Institute of Technology, focusing on neuromorphic computing, specifically related to the Neuromorphic Intermediate Representation (NIR) and its applications with frameworks like PyTorch.
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Luuk van Keeken is a researcher/PhD student at KTH Royal Institute of Technology, focusing on neuromorphic computing, specifically related to the [Neuromorphic Intermediate Representation (NIR)](/workshops/neuromorphic-intermediate-representation/) and its applications with frameworks like PyTorch.

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