Guy Vinitzky
Technion Electrical Engineering student with hands-on experience building deep-learning systems in PyTorch and delivering efficient, performance-oriented AI infrastructure.
About
Technion Electrical Engineering student with hands-on experience building deep-learning systems in PyTorch and delivering efficient, performance-oriented AI infrastructure. Skilled in implementing model training pipelines, optimizing GPU/CUDA workflows, and integrating ML components into research-focused engineering projects.
Focused on efficient model implementation, downstream decision-oriented model behavior, and robust systems design. Strong foundation in ML/Deep Learning coursework and practical GPU-accelerated image processing, with interests spanning Object Detection (YOLO), optimization, and scalable compute-oriented AI development.
- Joined August 2026
Industry experience
- Computers & Electronics
- Software & Internet
Work experience
Built a two-stage deep-learning pipeline using 10 YOLO base models across five representations with a custom 1D CNN meta-model. Designed chronology-aware preprocessing using time windows to reduce look-ahead bias. Developed a downstream evaluation workflow focused on decision-oriented model behavior. Implemented the full training and evaluation pipeline in Python for performance and reproducibility.
Implemented adaptive histogram equalization using CUDA kernels for histogram computation, prefix-sum style scan, and bilinear interpolation. Optimized host-to-device and compute overlap using shared memory, tile-based processing, CUDA Streams, and queue-based asynchronous coordination. Explored RDMA-oriented data movement using pinned host memory and networking primitives to reduce transfer overhead, improving throughput for image-processing workloads.
Education
Certifications and awards
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