𝐕𝐢𝐝𝐞𝐨 𝐌𝐨𝐭𝐢𝐨𝐧 𝐃𝐞𝐭𝐞𝐜𝐭𝐢𝐨𝐧:• Created an object detection algorithm using classical computer vision techniques such as image homography warping, and object classification using YOLO implemented in Python.• Transitioned the code from Python to C++ for faster execution.• Optimized the detection algorithm with CUDA to enhance performance.• Utilized CUDA programming on GPUs to accelerate processing on both Linux and Windows operating systems.• Achieved significant speed improvements, increasing processing efficiency to enable real-time detection capabilities.• Benefited applications that require immediate response.𝟑𝐃 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐌𝐚𝐩𝐩𝐢𝐧𝐠:• Developed and implemented a system for 3D projection of drone images.• Aligned aerial images with existing maps to accurately extract pixel-to-geographical coordinates (longitude and latitude).• Utilized the Segment Anything Model (SAM) for sophisticated object segmentation tasks.• Published demonstrations of SAM applications with detailed explanations on my LinkedIn profile, contributing to community knowledge.• Evaluated D2-Net: A Trainable CNN for Joint Detection and Description of Local Features. Compared D2-Net's performance against classical feature extraction and matching methods in computer vision.• Assessed aspects like detection accuracy, computational efficiency, and robustness to variations.𝐎𝐭𝐡𝐞𝐫 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬:• Leveraged NVIDIA technology for optimizing artificial intelligence usage and employed their edge devices (NVIDIA Jetson).• Worked on an object detection model based on transformers (TAO DINO) and compared it to traditional CNNs such as YOLO.• Developed algorithms for drone detection using YOLO-based trained neural networks to detect drones and distinguish them from birds, outperforming competing networks.• Used a custom ChatGPT assistant AI to develop an application providing process records from literature articles, specifically in chemistry.

𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 𝐚𝐧𝐝 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧:• Led end-to-end development of algorithmic solutions in machine vision, combining classical methods and deep learning techniques, which enhanced product capabilities and increased customer satisfaction.𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐝𝐯𝐞𝐫𝐬𝐚𝐫𝐢𝐚𝐥 𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐬 (𝐆𝐀𝐍𝐬) 𝐚𝐧𝐝 𝐒𝐮𝐩𝐞𝐫-𝐑𝐞𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧:• Developed a deep learning project for super-resolution using Generative Adversarial Networks (GANs), resulting in a pending patent. This innovation positioned the company at the forefront of technology and provided a competitive market advantage.𝐂𝐨𝐬𝐭 𝐒𝐚𝐯𝐢𝐧𝐠𝐬 𝐚𝐧𝐝 𝐈𝐦𝐚𝐠𝐞 𝐄𝐧𝐡𝐚𝐧𝐜𝐞𝐦𝐞𝐧𝐭:• Enhanced image resolution from low-resolution cameras, enabling the company to offer higher-quality imaging solutions without additional hardware costs, leading to significant cost savings.𝐃𝐚𝐭𝐚 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐚𝐧𝐝 𝐏𝐫𝐨𝐜𝐞𝐬𝐬 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧:• Managed ETL processes and validation, ensuring data integrity and reliability, to streamlined operations and reduce time-to-market for new features.𝐂𝐫𝐨𝐬𝐬-𝐃𝐞𝐩𝐚𝐫𝐭𝐦𝐞𝐧𝐭 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧:• Collaborated across departments, aligning algorithm development with business objectives, which improved project efficiency and contributed to potential revenue growth.

𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 𝐢𝐧 𝐎𝐩𝐭𝐢𝐜𝐚𝐥 𝐌𝐞𝐭𝐫𝐨𝐥𝐨𝐠𝐲:• Developed advanced algorithms for the next-generation Optical Metrology of Semiconductor devices, resulting in more efficient and cost-saving features, enhancing measurement accuracy and efficiency, which directly contributed to improved product quality for clients.𝐂𝐚𝐦𝐞𝐫𝐚 𝐜𝐚𝐥𝐢𝐛𝐫𝐚𝐭𝐢𝐨𝐧:• Responsible for the camera calibration and day-to-day operation and troubleshooting of the overlay metrology system, which provides accurate on-product overlay error feedback for fast technology ramps and stable production of leading-edge memory and logic devices.𝐀𝐈 𝐚𝐧𝐝 𝐒𝐞𝐥𝐟-𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭:• Pursued self-improvement in ML practices and audited an ML course in Tel Aviv University, as part of the company program, bringing cutting-edge techniques into the company to enhance brainstorming and collaboration.

𝐈𝐧𝐭𝐞𝐫𝐧𝐬𝐡𝐢𝐩 𝐰𝐢𝐭𝐡 𝐍𝐕𝐈𝐃𝐈𝐀 𝐚𝐧𝐝 𝐈𝐬𝐫𝐚𝐞𝐥 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧 𝐀𝐮𝐭𝐡𝐨𝐫𝐢𝐭𝐲:• Participated in an internship with NVIDIA and the Israel Innovation Authority, where I trained at the NVIDIA Deep Learning Institute on using NVIDIA GPUs and Jetson devices to implement optimized deep neural network applications focused on deep learning for medical imaging and automotive computer vision.𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐟𝐨𝐫 𝐦𝐞𝐝𝐢𝐜𝐚𝐥 𝐢𝐦𝐚𝐠𝐢𝐧𝐠:• Optimized deep learning networks for medical imaging, enhancing diagnostic capabilities, which could lead to better patient outcomes.𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧 𝐟𝐨𝐫 𝐀𝐮𝐭𝐨𝐦𝐨𝐭𝐢𝐯𝐞: • Developed algorithms for semantic segmentation and object detection and classic CV for autonomous UAV runway detection.2023-present Alter Learning𝐀𝐈 𝐜𝐨𝐧𝐬𝐮𝐥𝐭𝐚𝐧𝐭:• Provide professional Software Engineering, Data Science, and related Infrastructure Services, specializing in the use of voice and facial data for authentication and emotion recognition. Developed algorithms for educational games aimed at early detection of learning disabilities such as dyscalculia. 𝐕𝐨𝐢𝐜𝐞 𝐚𝐧𝐝 𝐟𝐚𝐜𝐞 𝐫𝐞𝐜𝐨𝐠𝐧𝐢𝐭𝐢𝐨𝐧:• Algorithms and deep learning techniques to authenticate users through biometric voice and facial recognition. Specifically, applications that analyze facial expressions and vocal patterns to detect and interpret emotional states, enhancing user experience and engagement.

𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐥𝐞𝐚𝐝: • Optical systems in a startup - specializing in the development of an endoscope. Oversaw the design specifications (camera, lens tube, sensor), logistics (domestic and global suppliers), prototypes research. • Demonstrated exceptional teamwork and communication skills: leading a cross-functional team to develop the world's thinnest endoscope that significantly improved medical diagnostics. • Multi-disciplinary: Optics, mechanics, algorithms, and outsourcing coordination. Fulfilled FDA and ISO regulatory requirements.𝐎𝐩𝐭𝐢𝐜𝐚𝐥 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡: • Conducted simulations, Hardware testing, documentation, and lab experiments, achieving an optimized in-vivo medical-oriented light source. • White Light Illumination beam shaping and transmission optimization. Enhanced light source power, spectrum, and stability.𝐀𝐩𝐩𝐥𝐢𝐞𝐝 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡𝐞𝐫:• Conducted literature research, simulations, and laboratory implementations in areas such as: Fourier plane transmission, Laser speckle analysis, Optical fiber illumination and coupling. Specifically, laser speckle analysis for illumination and Fourier plane in multi-core data fibers imaging and spectrum transmission under the CTO. • Simulated optical fiber coupling behavior. Performed testing on both glass and plastic fibers.𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐯𝐢𝐬𝐢𝐨𝐧 𝐚𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭:• Image processing for enhanced image clarity and sharpness with sophisticated methods using MATLAB and Imatest software.𝐌𝐢𝐜𝐫𝐨𝐬𝐜𝐨𝐩𝐞 𝐃𝐞𝐬𝐢𝐠𝐧 (𝐟𝐢𝐛𝐞𝐫 𝐭𝐨 𝐬𝐞𝐧𝐬𝐨𝐫 𝐢𝐦𝐚𝐠𝐢𝐧𝐠) 𝐚𝐧𝐝 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧:• Collaborated with optical designers to design and assemble microscopes. Integrated data fibers with microscopes and cameras. 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐏𝐫𝐨𝐛𝐥𝐞𝐦 𝐒𝐨𝐥𝐯𝐢𝐧𝐠: • Proposed creative ideas for product improvements and problem-solving, including ring illumination techniques, optical diffusers, and use of optical fibers.

𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦 𝐓𝐡𝐞𝐨𝐫𝐲 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭:• Developed foundational algorithms from basics using MATLAB and C++.• Conducted laboratory experiments to validate algorithm performance.𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐚𝐧𝐝 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 (𝐑&𝐃):• Investigated plasma dispersion effect-based all-optical modulators.• Explored super-resolution techniques in silicon.𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧𝐬 𝐚𝐧𝐝 𝐄𝐱𝐩𝐞𝐫𝐢𝐦𝐞𝐧𝐭𝐚𝐥 𝐂𝐡𝐚𝐫𝐚𝐜𝐭𝐞𝐫𝐢𝐳𝐚𝐭𝐢𝐨𝐧:• Performed simulations using MATLAB and COMSOL for electro-optical applications in silicon.• Conducted experimental characterization of silicon materials.• Processed images of optical beam Point Spread Function (PSF).𝐎𝐩𝐭𝐢𝐜𝐚𝐥 𝐃𝐞𝐬𝐢𝐠𝐧 𝐚𝐧𝐝 𝐄𝐱𝐩𝐞𝐫𝐢𝐦𝐞𝐧𝐭𝐬: • Designed optical systems and conducted experiments for Directorate of Defense, Research, & Development. • Developed lens-less imaging methods for X-ray imaging.𝐓𝐞𝐚𝐜𝐡𝐢𝐧𝐠 𝐀𝐬𝐬𝐢𝐬𝐭𝐚𝐧𝐭 𝐚𝐧𝐝 𝐈𝐧𝐬𝐭𝐫𝐮𝐜𝐭𝐨𝐫 𝐑𝐨𝐥𝐞𝐬: • Taught and assisted in courses on super-resolution techniques and detector technologies. Instructed final project on fiber drawing processes.