Projects

The architecture of the Sensor-Kinesis product, supported by Olmait technology, will allow patients to perform tests remotely (possibly at a temporary testing facility) and share results instantaneously with their primary care provider for diagnosis and treatment prescription. The revolutionary testing kit can be used not only for COVID19 but also cardiac life-threatening conditions, as well as various other physiological diseases. The cheap, user-friendly new device would yield results in a matter of minutes and would enable to mass-test millions of people around the world.

The mobile app enables the maternity department staff and breastfeeding consultants to support the mothers in the months after returning home. This ongoing connection is expected to increase breastfeeding duration and reduce postpartum depression. A survey system was set up to collect data from the participants, as part of a research conducted by the hospital. We are always proud to build products that make the world a better place. In the media (Hebrew): https://www.mako.co.il/women-women_news/Article-8cc90f28896fe61026.htm?fbclid=IwAR2n5Ly21Joba1iUZntXlZtka_BEyo-GxYDLx5lHOjSoXsySb7P3cQ2AckM

Created and designed a question-answer system to sell products to an insurance company’s customers. Worked on intent detection and trained a custom model to develop an incredibly smart chatbot storing statistics on each user. Used the intend detection algorithm implementation, Python, Flask, MongoDB and - last but not least - React for the admin panel.

Using Microsoft’s one million celebrity face open dataset to train the Neural Network, creating a full-proof face recognition and user identification search. The face identification software created has more than 90% accuracy. Used Convolutional neural networks, Recurrent Neural Networks, trained a set preparation from MS-Celeb-1M, worked on Neural Networks - PyTorch, and Computer Vision - OpenCV.

Developed a neural network to predict car damage from an image, what the car make is, and determine from which point of view the picture was taken. By collecting a major training set and label it correctly, created a state-of-the-art model for predictions. The insurance company then used the Neural Network model to create an app for its users, enabling them to insure their cars without any help of an insurance agent. Used Convolutional neural networks, trained a set preparation from various sources, and worked with Tensorflow, OpenCV, Scikit-learn, and Scrapy.