DeepRoute.ai welcomes Dr. Qifeng Chen, an esteemed figure in the field, as a Visiting Professor today. Dr. Chen's expertise will bolster the efforts to address challenges in autonomous driving and harness the potential of deep learning for safe, smooth and efficient smart driving. Dr. Chen has been on the forefront of autonomous driving system research and development, and mutual collaboration promises accelerated progress towards artificial general intelligence in robots.

As DeepRoute.ai is rapidly shipping smart driving features in different car models for major automakers, the company aims to continuously upgrade its end-to-end model DeepRoute IO and bring embodied-AI-level of experience to consumers in diverse complex urban environments in China and beyond. Eventually, smart driving cars will truly be able to think and behave like a human. Eventually, end-to-end models will be extended into broader applications to achieve artificial general intelligence in robots, marking a pivotal step towards AI 3.0.

Maxwell Zhou, CEO of DeepRoute.ai expresses enthusiasm and says, "Dr. Chen's track record in frontier technology research and development, breakthroughs in generative AI and autonomous driving, and strong business acumen are unparalleled. His expertise will elevate our technology and research to new heights."

"From mapfree technology to DeepRoute IO, the company has consistently pioneered innovative solutions since its inception. I am aligned with DeepRoute.ai's vision of achieving artificial general intelligence in robots. I look forward to bridging academic research with industry impact on this journey." says Qifeng Chen.

Dr. Qifeng Chen earned global recognition, completing his PhD in computer science at Stanford University in 2017 and serving as a Associate Professor at the Hong Kong University of Science and Technology. He was named 35 Innovators under 35 in China by MIT Technology Review and received the Google Faculty Research Award. His research spans autonomous driving, machine learning, image processing and 3D vision, with multiple papers selected for full oral presentation in ICCV and CVPR.