Benyou Wang is an Assistant Professor at Shenzhen Loop Area Institute and also an Assistant Professor, PhD supervisor, and Presidential Young Professor at the School of Data Science, The Chinese University of Hong Kong, Shenzhen. His research interests include multimodal large foundation models, mathematical reasoning with large models, applications of large language models (in healthcare), and human–agent interaction.

Cong is the NTU President’s Chair Professor of Finance, Computing and Data Science, and an Associate Dean of Nanyang Business School. He is also the Rudd Family Endowed Chair Professor at Cornell University, a Finance Editor at the Management Science, a faculty scientist at IC3, the chief scientist at HoloBit, inaugural senior economic advisor at Chainlink Labs, and a lead founder of multiple research forums.

Xiao Yu, Professor and Doctoral Supervisor at the Institute of Artificial Intelligence, Xiamen University. He received his Ph.D. degree from City University of Hong Kong in 2017. His primary research areas include control theory, robotics, formal methods, and embodied AI.

Congliang Chen received a B.S. from the School of EECS at Peking University and a Ph.D. from The Chinese University of Hong Kong, Shenzhen. He is currently a Research Assistant Professor at the Shenzhen Loop Area Institute. His research interests include machine learning theory, numerical computation, optimization algorithms for large language models, and kernel generation and optimization. He proved distributed Adam with multi-worker acceleration and a communication-efficient Adam variant enabling 1-bit-per-parameter training.

Weiyang Liu is an Assistant Professor in the Department of Computer Science and Engineering at The Chinese University of Hong Kong. He received a Ph.D. in Machine Learning from the University of Cambridge (UK) and a Ph.D. in Computer Science from the Georgia Institute of Technology (USA), and previously served as a postdoctoral researcher at the Max Planck Institute for Intelligent Systems (Germany). His research interests include large-scale machine learning, foundational algorithms for large models, formal reasoning, and symbolic reasoning.

Li Shang, PhD, is a Professor and Doctoral Supervisor at the College of Computer Science and Artificial Intelligence, Fudan University. He graduated from Princeton University with a PhD in Computer Engineering. His research focuses on machine learning systems, embodied intelligence, VLSI and EDA. He has hosted multiple key projects from NSFC and MOST of China and published over 200 papers in top journals/conferences, with multiple best paper awards and nominations, and over 10,000 citations.

The Center is dedicated to advancing AI's understanding of 3D space and physical laws. By building upon these capabilities, we aim to achieve breakthroughs in robotics, achieving agile motion control and fine manipulation skills for humanoid robots.We will investigate the fundamental principles of multimodal generative models to develop general spatial intelligence foundation models. This effort seeks to extend the "pre-training plus fine-tuning" paradigm from language and image/video domains to 3D space.

The Center is committed to integrating world-class expertise with cutting-edge AI capabilities to drive paradigm shifts in AI-empowered scientific research and transformative advances in engineering practice.We advance both the foundations and applications of AI, accelerating computational efficiency, scientific discovery, and engineering innovation.

The Center is dedicated to advancing the frontiers of language modeling and human-computer interaction, with breakthroughs in three major areas:Speech Large Language Models (LLM)The objective is to develop an innovative generation of end-to-end speech-language models. By decoupling knowledge from language, these models will enable low-resource, high-efficiency multilingual interaction and support lightweight deployment on terminal devices.

The Center for AI for Social Science addresses the gap in current AI research that emphasizes "technical optimization while neglecting social context". It aims to transform research paradigms toward a multidimensional social intelligence framework that integrates "value alignment, social embedding, and cultural adaptation". The Center establishes a research framework consisting of three key components:

The Center systematically builds hardware/software systems and develops fundamental theories of artificial intelligence, focusing on 11 major areas: Machine Learning Theory, Model Training and Inference Frameworks, Mathematical Mechanisms, Statistical Optimization of Models, Computing Cluster Architectures, Operator Development and Optimization, Cluster Fault Management, Computing Resource Scheduling, Cluster Communication Optimization, AI Chip Design, Next-Generation AI System Architecture Methods and Mixed-Precision Algorithms. 

On January 25, at the National Finals of the 3rd National Artificial Intelligence Application Scenario Innovation Challenge, two innovative projects jointly submitted under the lead of our Institute's jointly-appointed professor, Professor Yujian Ye from Southeast University, achieved outstanding results. Among them, the project "Intelligent Amphibious Unmanned Transport System," completed in collaboration with Nanjing University of Information Science & Technology, Imperial College London, and The Hong Kong Polytechnic University, won the National Final Top Award.

On January 25, the innovative project "Key Technologies and Applications of High-Trustworthiness AI Scheduling via Multi-Agent Collaboration for Ultra-Large-Scale Power Grids," submitted by Professor Jianwei Huang, Professor Junhua Zhao from our institute, and the Dispatch and Control Center of Guangdong Electric Power Grid Co., Ltd., won the Top Award in the 3rd National Artificial Intelligence Application Scenario Innovation Challenge. It is the only project in the "AI + Energy and Power" field to receive this top honor.

On January 9, 2026, Professor Yau Shing-tung, a member of the Strategic Committee of the Shenzhen Loop Area Institute, a Fields Medal laureate, and a Chair Professor at Tsinghua University, visited the Shenzhen Loop Area Institute.

Amidst a wave of global technological transformation and deepening regional integration, higher education is becoming a key driver for industrial upgrading and collaborative scientific innovation. Recently, the formal signing of a memorandum of cooperation between the Shenzhen Loop Area Institute and The Hong Kong Polytechnic University marks the Institute's completion of strategic agreements with all participating and collaborating universities from Hong Kong.

Recently, a student team from the Shenzhen Loop Area Institute (SLAI), in collaboration with the Hong Kong University Multimedia Laboratory (HKU MMLAB), completed a rare domestic 24-hour continuous robot clothing-folding livestream. The entire process was led and narrated by the student team. The livestream was featured on the homepage recommendations of major domestic platforms, with cumulative views across all platforms exceeding 1 million, sparking widespread attention.

Recently, at the inaugural Theorem Proving Competition held during the 2025 CCF China Software Conference, PhD student Yuyang Zhao from the Shenzhen Loop Area Institute delivered an outstanding performance, securing first place and second prize overall.

Sharing Perspectives on the Future of AIShenzhen Loop Area Institute  Center for Language, Intelligence and Machines (LIMA)Highlights from the LIMA Open Day

From December 5 to 12, the Shenzhen Loop Area Institute (SLAI) hosted a week-long transnational academic exchange.

On November 28, 2025, the Shenzhen Loop Area Institute and Tencent Technology (Shenzhen) Co., Ltd. formally signed a Memorandum of Understanding (MoU) on institute-enterprise collaboration. The two parties reached a deep strategic partnership in areas including artificial intelligence talent cultivation, scientific research cooperation, and joint project development, ushering in a new chapter of institute-enterprise collaborative innovation.

  

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With the goal of strengthening China's core competitiveness in the global AI landscape, SLAI leverages its strategic location at the heart of the Guangdong-Hong Kong-Macao Greater Bay Area. By integrating world-class research resources, cross-border innovation capabilities from Shenzhen and Hong Kong, and leading industry ecosystem resources, SLAI has developed a distinctive “3I” talent-development model.