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Hello world 👋

My name is Michel, and I am a machine learning engineer / research scientist living in the UK. 🇎🇧 💂‍♂ïļ ☔

I thought that I could introduce myself using some Python code below 🧑‍ðŸ’ŧ ðŸĪŠ

Favorite weird food combo: avocado, mango, and shrimp salad ðŸĨ‘ ðŸĨ­ ðŸĪ

class FrogInOxford:

    def __init__(self):
        self.name = "Michel"
        self.location = "Oxford"
        self.previous_location = "Tokyo"
        self.eager_to_help = True
        self.joke_success_rate = 0.5

        self.current_project = {}
        self.side_project = {}

    def work(self):
        self.current_project["name"] = "AI for interstitial lung disease detection and treatment"
        self.current_project["organization"] = "Brainomix"
        self.current_project["tools"] = ["Machine learning", "Python", "Scikit-learn", "Pandas", "Docker"]
        self.current_project["start"] = datetime(year=2022, month=12, day=12)

        self.side_project["name"] = "MRI chest image prediction for radiotherapy"
        self.side_project["tools"] = ["Online learning of neural networks", "Video prediction", "Matlab"]

Some of my previous open-source works:

Deformable 3D image registration with Lucas-Kanade pyramidal optical flow Time series forecasting with online learning of recurrent neural networks
Calculation of the motion of a lung tumor due to breathing using optical flow. Prediction of the position of external markers on the chest to guide the radiation beam during lung radiotherapy. This will help compensate the latency of treatment systems and reduce irradiation to healthy tissues.

Michel Pohl's Projects

3d-image-warping-using-nadaraya-watson-non-linear-regression icon 3d-image-warping-using-nadaraya-watson-non-linear-regression

Deforming a 3D image according to a given deformation vector field with Nadaraya-Watson regression; 3rd repo in a series of 3 repos associated with the research article "Prediction of the motion of chest internal points using an RNN trained with RTRL for latency compensation in lung cancer radiotherapy" (Pohl et al, Comput Med Imaging Graph, 2021)

lucas-kanade-pyramidal-optical-flow-for-3d-image-sequences icon lucas-kanade-pyramidal-optical-flow-for-3d-image-sequences

Implementation of the Lucas-Kanade pyramidal optical flow algorithm to register 3D medical images; 1st repo in a series of 3 repos associated with the research article "Prediction of the motion of chest internal points using an RNN trained with RTRL for latency compensation in lung cancer radiotherapy" (Pohl et al, Comput Med Imaging Graph, 2021)

time-series-forecasting-with-uoro-rtrl-lms-and-linear-regression icon time-series-forecasting-with-uoro-rtrl-lms-and-linear-regression

Prediction of multidimensional time-series data using a recurrent neural network (RNN) trained by real-time recurrent learning (RTRL), unbiased online recurrent optimization (UORO), least mean squares (LMS), or multivariate linear regression. The optimal hyper-parameters are selected using grid search with parallel processing.

time-series-prediction-with-an-rnn-trained-with-rtrl icon time-series-prediction-with-an-rnn-trained-with-rtrl

Multidimensional time-series data prediction with a recurrent neural network (RNN) trained by RTRL; 2nd repo in a series of 3 repos associated with the research article "Prediction of the motion of chest internal points using an RNN trained with RTRL for latency compensation in lung cancer radiotherapy" (Pohl et al, Comput Med Imaging Graph, 2021)

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