Directed by: Prof. Shipeng Li, Prof. Xi Zhu
The goal of the Center is to promote AI research for innovative applications and products. It combines the state of arts of multi-disciplinary research, develops core AI technologies, explores how these technologies can play a key role in meeting needs significant to our society, improves drastically productivity and eciency in our work and life, uncovers new compelling application scenarios, and builds disruptive products and services. Currently, the projects we are working on include: (1) Distributed & collaborative intelligent interactive systems; (2) Automatic synthesis of catalyst and functional nanomaterials guided by AI; (3) Task allocation, switching and collaboration in human-machine collective intelligence; (4) Big data driven time-space-correlation analysis & applications.
Directed by: Prof. David Zhang, Prof. Rui Huang
As one of the world leading research unit, this Center mainly focuses on various fields associated with computer vision, including high-level based image processing, low-level based image processing and biometrics, etc.
Biometrics recognition system. The center designs palm-prints system, fingerprints system and wrist/hand veins system. Additionally, the Center has also established Facial Beauty System to measure how a person is.
Traditional Chinese Medicine (TCM). According to the theoretical analysis of TCM, the Center has constructed multiple data collection devices for Tongue/Face Diagnosis, Pulse Diagnosis, and Odor diagnosis, etc. Furthermore, many feature extraction and classification algorithms for TCM diagnosis have also been studied.
Referring to the high-level based image processing, the Center aims to achieve face recognition, image classification, image retrieval and person Re-ID, etc.
Referring to the low-level based image processing, the Center has also done many works on image denoising, image super-resolution, image deblurring and image compression, etc.
Referring to the biometrics, the Center focuses on two aspects: Security Biometrics and Social Biometrics.
Directed by: Prof. Jianwei Huang
This Center focuses on designing effective incentive mechanisms and coordinated control schemes for effcient crowd intelligence systems, aiming at filling the gap between the fundamental theoretical research of crowd intelligence and the large-scale system implementation. It provides a strong engine for Shenzhen to become an international leader in the new generation of artificial intelligence industrial development.
At present, the Center has developed eight research themes, including Crowdsourcing and Crowdsensing, Smart Energy, Federated Learning, Blockchain, Privacy Aware Computing, Network Resource Sharing, Digital Twin and Digital Asset Pricing.
Directed by: Prof. Kai Hwang
The Center is committed to establishing a new multi-agent intelligent cloud-based ecosystem for smart healthcare, through employing cloud computing as management platform, artificial intelligence as analysis tool, and 5G IoT as big data collection and transmission method.
The Center's research projects include the establishment of (1) Multi-agent intelligent cloud platform; (2) Distributed cloud healthcare system; (3) Medical industry internet and social promotion services; (4) Deep learning based remote medical diagnosis and pathology; (5) Medical big data collection, storage, indexing and analysis system based on 5G IoT and network slicing.
Directed by: Prof. Hongyuan Zha
The Center's research interests cover a broad spectrum of machine learning and applications with societal impacts. Some of the Center's main research areas are listed below.
(1) Statistical and mathematical foundations of machine learning, including machine learning algorithms based on optimal transport theory, stochastic differential equations for MCMC, partial differential equations for generative models, and the mean field game theory; (2) Deep reinforcement learning and multi-agent reinforcement learning, off-policy and offline policy evaluation, and robust Markov decision processes; (3) The game theoretic perspective of machine learning, including strategic data acquisition, strategic learning and regression, and federated learning; (4) Machine learning methods for mechanism design, information design, information co-design, and general problems in computing economics; (5) Differential privacy and other privacy-preserving methods for machine learning, the trade-off between utility and privacy in machine learning, and constrained distributional robust learning; (6) Point process models and event history analysis, neural intensity functions and random measures, co-evolution of dynamics on networks and network t opology changes; (7) Machine learning and reinforcement learning for combinatorial optimization problems, graph neural networks, and dynamic graph generation.
Directed by: Dr. Yongquan Chen
"Autonomy and perception", "intelligence and emergence", "cooperation and group intelligence" are the three key scientific problems for research field of intelligent autonomous systems. The Center focus on this research area and carries out research projects, such as (1) Rigid-flexible coupling robot for oropharyngeal swab sampling; (2) Dynamic hand gesture recognition; (3) Multimodal fusion and perception, High-precision semantic map; (4) 3D LiDAR-based Graph SLAM, Visual semantic SLAM; (5) AI-based optimization control for mixed traffic flow.
These projects aim at filling the gap in the basic theoretical research of intelligent autonomous systems, and making a breakthrough in core technologies among smart sensing, fine manipulation, human-machine collaboration and human-vehicle-roadside collaboration. It also provides strong support for making Shenzhen an internationally leader in the new generation of artificial intelligence industrial development and implementing the Guangdong-Hong Kong-Macao Greater Bay Area construction strategy.
Directed by: Dr. Tian Dihong
Extended Reality, including virtual reality (VR), augmented reality (AR), and mixed reality (MR), is expected to be the next form of human-computer interaction and personal computing, just as smart phones have done in the past decade. At AIRS, the Center on Extended Reality (CXR) focuses on conducting research and advanced development of key technologies for extended reality, including computational imaging, display, and automated content generation using AI technologies. The Center is also developing pilot systems to demonstrate applications of XR in manufacturing, collaboration, and education.
The Center’s current research directions are primarily twofold: (1) Extended Reality Content Generation — to explore automating 3D content creation with the aid of semantics using Generative Adversarial Network (GAN); (2) Computational Imaging and Display — to research theories and techniques for computational imaging, particularly for optical microscope, light-field imaging and display.
Directed by: Prof. Tin Lun Lam, Prof. Zhenglong Sun
The Research Center on Intelligent Robots is committed to collaborating with leading international experts to research leading-edge robotic technologies to give impetus to the application of the technologies in new fields, popularizing the knowledge of robotics and AI to society, and strives to build a Shenzhen-based world-class robotics research and application promotion hub. The main research areas of the center are novel robot design and multi-robot systems. Research topics cover:
Novel Robot Design — Freeform robotics, Soft robotics and Marine robotics;
Multi-robot Systems — Cooperative environment perception, Relative positioning, Multi-robot manipulation, Multi-task optimization planning and Decentralized control.
Directed by: Dr. Ning Ding
Research Center on Special Robots is committed to the research and development of special robots for large-scale city infrastructures including bridges, tunnels, high-voltage power transmission and underground pipe network, which can assist or replace professional staff to go to high-risk operation areas and carry out daily inspection, surface local repairing, emergency rescue, decommissioning of equipment and facilities.
The Center's main research directions include: (1) Bionic climbing special robot mechanism design and multi-robot cooperative motion control; (2) Non-destructive testing of concrete and metal components and identification algorithm of diseases based on evolutional recognition mechanism; (3) Autonomous repairing and control of surface damage on infrastructure surface guided by visual and tactile; (4) Research on the mechanism of smart city with human-machine collective intelligence.
Directed by: Dr. Long Han
Our Mission: Improve the health level of mankind with robotics
Research Directions: Focus on short-term health recovery (surgical robots) and long-term health maintenance (surface cleaning robots)
Perception: Development and integration of new sensors for environmental state awareness (in-vivo and in-vitro)
Control: Research on precise control and stiffness shifting of flexible manipulator of different scales
Navigation: Autonomous navigation and task planning system based on multi-modal image data
Core Advantages: Rich experience in the combination of industry and research, good at guiding the direction of scientific research with industrial value
Directed by: Prof. Jiangfan Yu
The Research Center on Micro-Nanorobotics is highly multidisciplinary. It is dedicated to the research ranging from fundamental study on material sciences, physics, and biology to the technologies and solutions on robotics, AI strategy, control theory and biomedicine.
The Center develops advanced micro-nanorobots with novel materials, structures, assemblies, swarm behaviours and functions, in order to aim various applications, including but not limited to targeted drug delivery, cancer treatment, cell measurement, point-of-care diagnostics, polluted water cleaning, and physics at micro-nanoscale.
The Center is bringing cutting-edge technologies around the world with great promise in solving problems that people really cares about.
Directed by: Prof. Shiqi Yu
OpenCV Center (OpenCV China Team) is supported by AIRS with the aim of development, maintenance and promotion of OpenCV. OpenCV (Open Source Computer Vision Library) is one of the most popular computer vision and machine learning open source software library. It has been 20 years since OpenCV's first release. Being a Apache 2.0 licensed product, OpenCV is to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products. AIRS, together with Intel and OpenCV Foundation etc., is now one of the copyright holders of OpenCV.