Gal Moore

Built fully automatic deep neural network optimisation solutions and end to end products at previous employees (see cv)

Built fully automatic deep neural network optimisation solutions and end to end products at previous employees (see cv)

Use and setup of S3 for multiple projects - see CV

Demonstrated through database expertise and extensive data projects (see CV)

Demonstrated through database expertise and extensive data projects (see CV)

Worked on IoT-related robotics projects at Cogniteam including Autonomous vehicles, radar, Lidar, camera and IMU based. https://youtu.be/pxpq5a0irYo

Developed End to End AI solutions in healthcare, robotics, telecoms and finance - see CV

Created a chatbot using ROS, Linux and muiltiple sensors for an Intel project https://youtu.be/n81bAgLAbtg

Worked on autonomous systems and IoT-related robotics for MAFAT, Intel and others at Cogniteam https://www.youtube.com/watch?v=CkXNGR9ayZk

Extensive experience, notably as a ML engineer and data scienist at Thetaray, Healthy.io, Huawei and Cogniteam (See CV)

Specialized in deep neural network based convolutional techniques (segmentation & detection), dataset development, training and fine tuning models and use of OpenCV.

Specialized in deep neural network based convolutional techniques (segmentation & detection), dataset development, training and fine tuning models and use of OpenCV.

Deep neural network architecture experience at Healthy.io and Cogniteam with extensive experience analysing, modifying and optimizing deep convolutional networks at Huawei

Created a chatbot using ROS, Linux and muiltiple sensors for an Intel project https://youtu.be/n81bAgLAbtg

Deep neural network architecture experience at Healthy.io and Cogniteam with extensive experience analysing, modifying and optimizing deep convolutional networks at Huawei - see CV

Worked on autonomous systems and IoT-related robotics for MAFAT, Intel and others at Cogniteam

Built end to end image segmentation and detection solution based on neural networks in a GCP environment

Experience with Regex, NLTK, Gensim, Huggingface in transformers (BERT, GPT), LSTM, and embeddings for use in classification, summarization, POS tagging etc..