Media Analytics | Turgun Kashgari

Turgun Kashgari is a Senior Associate Researcher in the Media Analytics Department at NEC Laboratories America. His work focuses on efficient deployment and optimization of deep learning models, large language models, and vision-language models on local GPUs, CPUs, and edge devices. He earned his M.S. in Computer Science from the University of Central Florida in 2017, specializing in computer vision, machine learning, and data mining, and his M.S. in Communication and Information Systems from Shanghai Jiao Tong University.

Over the past several years, Turgun has worked extensively on real-time AI deployment, model quantization, model optimization, knowledge distillation, and low-latency inference. His recent work focuses on LLM and VLM optimization, including weight quantization, KV-cache quantization and optimization, speculative decoding, disaggregated serving, vocabulary reduction, and efficient serving architectures. He has hands-on experience with major deployment frameworks such as TensorRT-LLM, vLLM, LMDeploy, llama.cpp, OpenVINO, and SGLang.

Turgun has also contributed significantly to autonomous driving projects, deploying perception models and LLM/VLM-based planning models directly on vehicle platforms. He is experienced with ROS2, Autoware Universe, real-time perception pipelines, edge AI systems, and scalable model-serving infrastructure. His work supports NEC Labs’ efforts to build reliable, efficient, and high-performance AI systems for autonomous driving, intelligent transportation, smart cities, enterprise automation, and other real-world applications.