A senior engineering team for problems that resist easy answers.

Dr. Regev brings 28 years of algorithm-development experience across radar and LIDAR signal processing, computer vision, multi-target tracking, radar micro-Doppler, deep-learning-based classification, optimization, and statistical signal processing. His work is backed by 10 published research papers and 8 patents.

He holds a Ph.D. in Electrical Engineering from Ben-Gurion University of the Negev, where his research focused on radar remote vital-sign sensing and target recognition. He also serves as an Adjunct Professor at Cal Poly Pomona's Electrical and Computer Engineering Department.

He also teaches training courses on radar, signal processing, and deep learning at academy.drnirregev.com.

Guy Regev is a veteran of the semiconductor design industry with more than 24 years of management and hands-on expertise across chip, FPGA, firmware, and software design.

His experience spans architecture through productization, including successful time-crunched tape-outs and flagship product introductions for processors, DSPs, AI/ML accelerators, cellular baseband SoCs, switch ASICs, vector processors, and array processors.

Karan Jakhar is a senior AI engineer with broad experience across computer vision, deep learning, and LLM/VLM systems, spanning AI solution architecture, model development, production deployment, and end-to-end MLOps. His work covers object detection, multi-object tracking, anomaly detection, agentic AI workflows, and real-time inference at scale.

His deployment stack includes NVIDIA DeepStream, TensorRT, CUDA, Jetson edge hardware, and vLLM-based model serving, with strong emphasis on model quantization, inference optimization, production monitoring, and automated retraining pipelines.