Ilan Aizelman
Seeking OpportunitiesFull-Time
Deep Learning & Computer Vision Engineer

• Over 3 years experience of real world AI product building.

• Over 10 courses and certifications in AI.

• Capable of building AI product from scratch or co-work with teams.

• Extensive problem solving experience for data science/engineering,transferringreal problem into requirements and solution planning.

• Analysis, Experiment, Debug, Improve AI system on large scale environment.

Expertise: 3D Imaging3D RecognitionBig DataComputer VisionData ScienceDeep Learning


AI Technologies: Computer Vision
ML Technologies: Supervised Learning
AI Tasks: Facial Recognition and ModellingImage ClassificationMedical Image SegmentationObject DetectionPerson Re-IdentificationPose EstimationSegmentation
AI Algorithms: A*AdaBoostClassification and RegressionCNNDecision ForestsDeep LearningEnsemble algorithmsGANs
AI Tools: DockerKeras
Coding: AndroidPythonTensorFlow
AI Hardware: CPUGPU

Academic Background

2015 -
Developed a fully autonomous RC Car from scratch, including simulations in Unity3D. Using the following tools: Raspberrypi, Arduino, SSH, Wifi & Bluetooth modules in real-time, Tensorflow, CNN, Supervised approach, Python.
2019 -
Auditor of Deep Learning, Computer VIsion and Math courses. Not an official student.

Work Experience

Computer Vision & Deep Learning Engineer
2019 -
• Built a fully customized end-to-end cycle of acquiring data, training and testing an object detector with python and Tensorflow. • Extensive data analysis & machine learning concepts to understand the structure of the data and increase model's performance in real time. • Research and training of state-of-the-art models to increase performance
Partner - AI Engineer
2019 -
• Built a proof-of-concept for the start-up from scratch. • Wrote requirements, starting from data acquirement, data analysis and data augmentation, including training of many different models for high performence. • Developed a mobile application in Android Studio with an AI classifier. • Integerated electronic devices, such as bluetooth modules, motors, servos, Arduino, and other devices to work in real-time with a mobile application.
Deep Learning Student
2018 -
• Used TensorFlow for various AI tasks. (Classification, Detection) • Using Ubuntu 18.04, Dockers, converting models from MXNET to TensorRT
Share on linkedin
Share on facebook
Share on twitter