Hong Huaqing is a Professor and doctoral supervisor at the Corpus Research Institute of Shanghai International Studies University. He holds roles as honorary director of the Chinese Corpus Linguistics Research Association and international expert at Peking University's Education Development Center. Formerly, he worked at Nanyang Technological University (Singapore) in roles such as researcher at the Learning Research and Development Center and director of the e-Learning Center of the Lee Kong Chian School of Medicine. His research spans machine translation, natural language processing, corpus linguistics, and educational technology. He supervises master's and doctoral students, co-supervises postdoctoral researchers, and focuses on smart education driven by big data analysis and innovative learning ecosystems. Research emphasizes corpus-based methods applied to language education, including computational frameworks for student engagement, wearable sensors in learning analytics, and cross-linguistic rhetoric studies. His work bridges technological innovation (e.g., AI-driven tutorial systems) with pedagogical practice, addressing challenges in non-English language education and teacher training.
Wenzhong Li is a Professor at the School of Computer Science, Nanjing University, where he leads research at the State Key Laboratory for Novel Software and Technology. His academic career spans over 15 years with significant contributions to AI-empowered distributed systems, big data mining, and networking applications. He teaches Computer Networks and guides graduate students in Distributed Computing Research. Professor Li's research focuses on cutting-edge areas including AI-Empowered Distributed Systems and Applications (MultiModal Large Models, Embodied Intelligence, Edge Computing), Big Data Mining (Time Series Analysis, Graph Computing, Social Networks Analysis), and AI-Based Distributed Resource Scheduling. His work bridges theoretical foundations with practical implementations in real-world systems. His recent publications demonstrate a strong trend toward integrating deep learning with graph theory and time series analysis, with applications in human activity recognition, network optimization, and multimodal systems. The research spans multiple disciplines including artificial intelligence, computer vision, networking, and data mining, with a particular emphasis on practical implementations for real-world problems. Best Paper Runner Up at KSEM 2023 for 'Learning-based Dichotomy Graph Sketch for Summarizing Graph Streams with High Accuracy' Best Paper Award at APNet 2018 for 'Toward Effective and Fair RDMA Resource Sharing' Professor Li has advised numerous PhD and Master's students who have gone on to prominent positions at institutions like Nanjing University, Huawei, Alibaba, Microsoft, and various international universities. His research is supported by substantial grants from the National Natural Science Foundation of China, Natural Science Foundation of Jiangsu Province, National Power Grid, and other major funding bodies, totaling multiple multi-year projects with significant budgets. He leads the AINet Group and is affiliated with the Sino-German Institute of Social Computing and MobileCloud research initiatives. His DISLAB provides the organizational framework for his research team, which includes dozens of graduate students and collaborators working on cutting-edge problems in AI, networking, and distributed systems.
Professor Liu Hongyan is a full-time Professor in the Department of Management Science and Engineering at Tsinghua University's School of Economics and Management, where he has served since 1994, achieving the rank of Professor in 2011 after previously holding positions as Associate Professor (2003-2011) and Teacher. His research bridges theoretical data science with practical applications across e-commerce, healthcare, and social media platforms. Education: PhD in Management, School of Economics and Management, Tsinghua University (2001) His research focuses on big data management , machine learning , and business intelligence with specialized expertise in personalized recommendation systems , medical/financial data analysis , and computer vision applications . Recent work integrates large language models and causal inference to solve complex problems in short video platforms, live streaming, and healthcare analytics, emphasizing real-world impact through industry collaborations. Analysis of his 15 most recent publications (2023-2025) reveals a strong trajectory toward multimodal AI systems combining recommendation engines with computer vision, particularly in 3D animation for advertising and healthcare. Key trends include LLM-enhanced display advertising, emotion-aware facial animation, and medical image annotation using adversarial learning, while maintaining core contributions to behavioral data mining in social networks. Scientific recognition includes: National Archives Administration's Outstanding Scientific and Technological Achievement Award Multiple Best Paper Awards at international conferences Outstanding Doctoral Dissertation Supervisor designation from the Society for Management Science and Engineering Special Award for National Natural Science Foundation project on user behavior pattern discovery Professor Liu has secured leadership roles in major National Natural Science Foundation projects including Innovation Research Groups and international cooperation initiatives. His industry impact is demonstrated through patented recommendation systems adopted by multiple companies, particularly in personalized content delivery for live streaming and short video platforms. As an Outstanding Doctoral Dissertation Supervisor, he mentors the next generation of data science researchers. He serves as Deputy Director of Tsinghua University's Center for Artificial Intelligence and Management Research and holds key positions in national academic societies including the E-Commerce and Cyberspace Management Committee (China Management Modernization Research Association) and the Information Systems Engineering Committee (Chinese Society for Systems Engineering).
Southern University of Science and Technology (SUSTech)China
CHEN Wei is a Chair Professor at the Department of Biology, School of Life Sciences, Southern University of Science and Technology (SUSTech), Shenzhen, China. He holds a Ph.D. from the Max Planck Institute for Molecular Genetics (2006) and previously served as a Full Professor (W3) at the Max-Delbrück Center for Molecular Medicine and Charité – Universitätsmedizin Berlin (2015-2016). Prior to joining SUSTech, he led research groups at prestigious German institutions, contributing to large-scale genome centers and the Berlin Institute of Health. Education : Ph.D. (2006, Max Planck Institute), M.S. (2002, Sichuan University), B.S. (1993, Xiamen University) His research focuses on systems biology and genomics, particularly post-transcriptional gene regulation mechanisms and their roles in human diseases. His lab integrates next-generation sequencing technologies with computational approaches to study non-coding RNA functions, alternative splicing, and chromatin dynamics. Key projects include CRISPR-based functional studies, 3D genome analysis, and RNA editing in neurological and metabolic disorders. Recent publications highlight his work in Drosophila developmental genomics, chloroplast translation control, and cancer biology. The 2025 study on spatiotemporal multi-omics in Drosophila and 2024 articles on MatK's role in tRNA splicing and CRISPR-activated transcriptional regulation exemplify his interdisciplinary approach. Earlier works (2023-2022) address immune cell trafficking, alternative polyadenylation, and chromatin remodeling in cancer metastasis. At SUSTech, he leads a team with 4 research assistant professors, 2 postdoctoral fellows, 3 research assistants, and 7 graduate students. His lab has secured significant funding from EU and German agencies (€7M+), though specific awards are not detailed in the provided text. Teaching responsibilities include General Biology and Principles of Cell Biology.
Ma Xufeng is an Assistant Professor in the Animation Department at the School of Art and Media, Tongji University , Shanghai. She earned her PhD in Image Arts from Chung-Ang University, South Korea , and completed a postdoctoral fellowship at the School of Journalism and Communication, Tsinghua University . Her research bridges intelligent imaging, animation games, AIGC, new media art, and the metaverse , focusing on intelligent image production and dissemination, AI-driven art therapy, and serious games . Education: PhD in Image Arts, Chung-Ang University, South Korea (2018.09–2021.02) Master of Image Arts, Chung-Ang University, South Korea (2016.09–2018.06) Bachelor of Art Design (Animation), Zhongnan University of Economics and Law, China (2011.09–2015.07) Research Interests: Dr. Ma’s scholarship sits at the intersection of artificial intelligence, digital media, and therapeutic applications . She explores how AI-generated content (AIGC) can revolutionize animation, game design, and immersive storytelling . A second strand investigates serious games and VR systems for autism rehabilitation and emotional therapy , leveraging game psychology to craft interventions that blend aesthetics, technology, and mental health . Publications & Research Trends: Her most recent work (2021-2024) charts a trajectory from VR-based rehabilitation games to AI painting for art therapy , demonstrating a shift from interactive technology prototypes toward critical and aesthetic theories of AI art . Collectively, her publications map the evolution of intelligent media ecosystems and their societal impact. Scientific Awards & Grants: Principal Investigator, Korean BK21+ CFT Convergence Research Project – VR immersive game for autistic children (2020) Principal Investigator, Korean BK21+ CFT Convergence Research Project – Fitness-bicycle functional game (2019) Special Selection Award, Seoul International Animation & Cartoon Festival (2020) Nomination, Golden Kuker–Sofia International Animation Festival (2020) Teaching & Labs: At Tongji University, Dr. Ma contributes to undergraduate and postgraduate curricula in animation, new media art, and game design . She is affiliated with the Omnimedia Research Institute and the Media Experiment and Practice Teaching Center , where she guides students in AI-driven content creation and VR/AR prototyping .
Xuehai Qian is a Tenured Full Professor in the Department of Computer Science at Tsinghua University since July 2024. Prior to this, he served as an Associate Professor at Purdue University (2022-2024), Assistant Professor at the University of Southern California (2015-2022), and Postdoctoral Researcher at the University of California Berkeley (2013-2015). Ph.D. in Computer Science, University of Illinois at Urbana-Champaign, USA (2013) ME in Computer Science and Technology, Institute of Computing Technology, Chinese Academy of Sciences, China (2007) BE in Computer Science and Technology, Beihang University, China (2004) His research focuses on parallel computer architecture , hardware/software co-designed domain-specific architectures for graph analytics and machine learning , hardware security , and quantum computer architecture . He has pioneered scalable cache coherence protocols for atomic block execution, hardware sequential consistency violation detection, and distributed frameworks for graph processing leveraging emerging memory technologies. Xuehai Qian’s publications span computer architecture , graph analytics , machine learning systems , and quantum computing , with a strong emphasis on distributed systems , accelerators , and memory optimization . His work includes novel architectures for graph processing, decentralized training protocols, and ReRAM-based accelerators for deep learning. NSF CAREER Award (2018) ACSIC (American Chinese Scholar In Computing) Rising Star Award (2019) IEEE Senior Member (2019) Hall of Fame inductions: ASPLOS (2018), HPCA (2019), ISCA (2021), MICRO (2021) W.J. Poppelbaum Memorial Award (2013) He has advised students who have received Microsoft Research Lovelace Fellowships , Ph.D. Fellowships , and Facebook Fellowships . His research has been supported by grants such as the NSF SPX project on FPGA-based machine learning platforms and smaller NSF grants. Notably, he has served as an Associate Editor for Science China (Information Sciences) since 2023 and as a Guest Editor for IEEE Transactions on Parallel and Distributed Systems (2019).
Daohong Qiu is an Associate Professor and Master Tutor at the Geotechnical and Structural Engineering Center, School of Civil Engineering, Shandong University. His research focuses on advanced geological prediction in tunnels, surrounding rock stability, structural health monitoring for urban rail transit, and TBM tunneling performance optimization. Position: Associate Professor Affiliation: School of Civil Engineering, Shandong University Email: qiudh@sdu.edu.cn Research Interests: He specializes in geotechnical engineering challenges related to underground construction, including rock burst prediction , disaster control , and machine learning applications in geological modeling. His work emphasizes integrating advanced computational methods like quantum genetic algorithms and RBF neural networks with field data to improve tunnel safety and efficiency. Publication Trends: His recent 2019 studies address subsea tunnel risk assessment , rock burst prediction in underground caverns, and machine learning-driven surrounding rock classification . Earlier works (2014-2015) explore SVM/GA-SVM for geological disaster forecasting, while pre-2010 papers focus on optimization theory and stress field analysis. Patent Contributions: He holds multiple invention patents for geological prediction devices, including three-dimensional geological network modeling , seismic signal detection , and concrete elevation control systems .
Chang Danting is an Assistant Professor at the School of Management, Shandong University . His research focuses on capital markets , information disclosure mechanisms , sell-side analyst dynamics , and institutional investor behavior . Education : Bachelor's degree from Shanghai University of Finance and Economics (2011.09-2015.06) PhD (Master-PhD combined) from Shanghai Advanced Institute of Finance, Shanghai Jiao Tong University (2015.09-2021.09) Joint PhD Candidate at Harvard Business School (2019.08-2020.09) His research integrates empirical finance with data mining techniques , examining market anomalies such as the size puzzle and valuation-fundamentals expectation gaps . Recent studies analyze analyst coverage impacts on return patterns and institutional investor decision-making through empirical frameworks. Current research projects include the National Natural Science Foundation of China Youth Project (Principal Investigator) and collaborations on financial technology reform and cross-border financial services . Teaching responsibilities encompass undergraduate courses in Accounting , Financial Statement Analysis , and Investment , along with graduate seminars on Accounting Theory Frontiers and Financial Reporting During Crises .
Southern University of Science and Technology (SUSTech)China
Dr. Wei Cai is a Research Associate Professor in the Department of Ocean Science and Engineering at the Southern University of Science and Technology (SUSTech). He also serves as Assistant to the President of the Academy of Marine Sciences at SUSTech and Assistant Director of the Shenzhen Branch of the Laboratory of Marine Science and Engineering of Guangdong Province. Additionally, he is the Deputy Director of the Marine Robot & Power System Laboratory and a member of the National Technical Committee for the Standardization of Submersibles. Dr. Cai received his educational background as follows: Doctor of Biomedical Engineering : Zhejiang University, September 2007 - June 2012 Bachelor of Biomedical Engineering : Zhejiang University, October 2002 - June 2007 Dr. Cai has dedicated his career to marine technology research for nearly 15 years, with expertise spanning multiple disciplines of ocean science and engineering. His primary research interests focus on marine sensors , scientific applications of submersibles , and polymetallic sulfide resources in the international seabed area . His work bridges engineering innovation with practical oceanographic applications, particularly in deep-sea exploration technologies. Dr. Cai has extensive field experience, having participated in 12 cruises on China Ocean Voyages, where he served as chief scientist for several important missions including sea trials of the "Qianlong II" AUV in 2016, "Qianlong III" AUV in 2018, and Deep-Sea Drilling Rig in 2021. His January 2019 expedition with the "Deep Sea Warrior" manned submersible reached a depth of 2,773 meters in the Southwest Indian Ocean, demonstrating his hands-on expertise in extreme deep-sea environments. Dr. Cai's research portfolio demonstrates a clear progression from fundamental sensor development to sophisticated deep-sea exploration systems. His early work focused on chemical sensors for water quality monitoring, particularly for heavy metal detection, which laid the foundation for his later specialization in marine applications. Over time, his research evolved toward deep-sea technologies, with increasing emphasis on autonomous underwater vehicles (AUVs), hydrothermal vent systems, and polymetallic sulfide resource exploration. His publications reveal strong interdisciplinary connections between chemical engineering, robotics, marine geology, and environmental science, with practical applications in both resource exploration and environmental protection. Dr. Cai's scientific achievements have been recognized with several prestigious awards: Second Prize of National Science and Technology Progress Award (Team), 2019 Outstanding Contribution Award of China Marine Engineering Consulting Association (Team), 2019 Outstanding Graduate of Zhejiang Province, 2012 2022 Pearl River Talent Plan Young Top Talent 2022 Shenzhen "Pengcheng Peacock Plan" Special Post C As a principal investigator, Dr. Cai has secured significant research funding, including the National Key Research and Development Program of China, projects from the Deep Blue Project Fund by Shanghai Jiao Tong University, and various provincial and national research grants. His leadership extends to serving as deputy chief designer of technical upgrade and scientific application of the "Qianlong II" AUV. Dr. Cai has also contributed to major scientific endeavors as a participant in numerous China Ocean Voyage projects, with funding ranging from millions to tens of millions of RMB per project. Dr. Cai leads the Marine Robot & Power System Laboratory at SUSTech, where his team focuses on developing advanced marine technologies for deep-sea exploration. His laboratory work integrates robotics, sensor development, and data analysis to create comprehensive solutions for underwater research and resource exploration. The lab's current projects include developing high-sensitivity methane sensors for deep-sea environments, systems for detecting heavy metals in hydrothermal plumes, and wireless sensor networks for red tide early warning systems. This multidisciplinary approach positions Dr. Cai's team at the forefront of marine technology innovation in China.
Wei Hu is a full Professor and Ph.D. supervisor in the Department of Computer Science and Technology at Nanjing University, China. He earned his Ph.D. and B.S. from Southeast University in 2009 and 2005, respectively, and joined Nanjing University faculty in 2009. He has held visiting positions at Stanford University (2014-2015), University of Texas at Arlington (2016-2017), and University of Toronto (2017) as a visiting scholar/professor. Research Interests focus on Knowledge Graphs : Representation learning, foundation models, and error detection Databases : Entity alignment, crowdsourcing, and blockchain integration Digital Medicine : Collaboration with Nanjing University's National Institute of Health Data Science Publication Trends show expertise in knowledge graph reasoning, federated learning, and biomedical applications. Recent works include in-context learning for graph reasoning and blockchain-based data fusion systems. Scientific Awards include Huawei 2025 Challenges Spark Award ASE 2024 Distinguished Paper Award CHIP 2021 Best Paper Award CCKS 2018 Best English Paper Award Nanjing University Study Abroad Program Awardee (2013) IBM China Excellent Student (2008) Advising involves leading the Knowledge Fusion Group at Nanjing University, mentoring 18 current and former Ph.D. and Master's students. Professional services include editorial roles at Transactions on Graph Data and Knowledge and Big Data Research , plus committee memberships in CCF, CIPSC, and JSCS.
ZHOU Xianghong is a Professor and PhD Advisor at the School of Economics and Management, Tongji University. Currently serving as Assistant Dean, she specializes in urban public service management, medical care, and health policy. Her academic and professional work bridges public administration, poverty reduction, and sustainable development. Doctor of Laws (Sociology), Nanjing University (1999–2002) Post-doctorate in Management Science and Engineering, Tongji University (2002–2005) Her research focuses on macro-level policy analysis, particularly in urban public service management , medical care and health policy , and poverty reduction mechanisms . She has led studies on smart city development, agricultural carbon emission efficiency, and health resource allocation. The 15 most recent publications span interdisciplinary topics, including environmental economics, machine learning for recommendations, and public health governance. Her work emphasizes quasi-experimental methods, regional disparities, and policy evaluation in urban and rural contexts. ZHOU has secured grants from the National Natural Science Foundation of China (NSFC) and Shanghai government agencies for projects on smart city governance, poverty reduction, and environmental policy. She has taught courses across MPA, MBA, and executive programs, focusing on public affairs, policy analysis, and urban innovation.
Guo Xunhua is a Professor in the Department of Management Science and Engineering at Tsinghua University's School of Economics and Management. He serves as Party Branch Secretary and holds significant leadership roles including Executive Director and Secretary-General of the China National Association for Information Technology (CNAIS), Vice President of the China Society of Information Economics, and Secretary-General of the Information Management Committee of the China Management Modernization Research Association. His educational background includes dual bachelor's degrees in Management Information Systems and Computer Science and Technology from Tsinghua University (2000), followed by master's and doctoral degrees in Management Science and Engineering from the same institution (2005). He has been teaching at Tsinghua since 2005 and maintains international academic connections through visiting positions at RWTH Aachen University and MIT Sloan School of Management. Guo's research spans Management Information Systems, E-commerce, Social Networks, and Business Intelligence, with a focus on business intelligence methods in internet environments and behavioral patterns under emerging information technologies. His work integrates both 'technology' and 'behavior' perspectives within information systems research. His recent publications reveal a strong trend toward AI applications in e-commerce, personalized recommendation systems, social commerce dynamics, and the psychological aspects of digital interactions. Ministry of Education Changjiang Scholar Young Scholar (2019) Ministry of Education Outstanding Achievement Award for Scientific Research in Humanities and Social Sciences Beijing Philosophical and Social Sciences Outstanding Achievement Award Beijing Higher Education Teaching Achievement Award Multiple Tsinghua University Teaching Achievement Awards Professor Guo serves as Assistant Editor-in-Chief of the Journal of Information Systems and sits on editorial boards for international journals including Information Technology & People, Electronic Commerce Research, and Journal of Global Information Management. His teaching portfolio includes graduate courses in IT and Organization, and undergraduate courses in Principles of Computer Systems, Management Information Systems, and Introduction to Management Science and Engineering Research.
Hai Lin is a Professor at the State Key Lab of CAD&CG (Zhejiang University, China). His research spans computer graphics, scientific visualization, volume rendering, virtual reality, and graphical electromagnetic computing. He earned B.Eng and M.Eng degrees from Xidian University (1987, 1990) and a Ph.D. in Computer Science from Zhejiang University. Current Position: Professor, Zhejiang University (1990–Present) Research Fellow, Medical Visualization, De Montfort University (2000–2003) Visiting Professor, University of Bedfordshire Research Focus includes: Medical Imaging: AI-driven tumor segmentation (colorectal, liver), retinal disease classification (SatFormer), and mandible segmentation via LRVRG. Electromagnetic Computing: Shape deformation optimization, GPU-based wave propagation prediction, and scattering analysis. Scientific Visualization: Graph convolutional networks for volume data, voxel2vec representations, and dynamic network exploration. Collaborations involve PhD students (Huan Liu, Yiming Li, YanKai Jiang, Han Wang) and teams at Zhejiang University. His work integrates AI with electromagnetic and medical imaging domains, emphasizing GPU acceleration and novel algorithm design.
Deqiang Mao is a Professor of Hydrogeology at the Department of Hydraulic Engineering, School of Civil Engineering, Shandong University, Jinan, China. He holds a PhD in Hydrology from The University of Arizona (2012), with prior academic appointments at New Mexico Institute of Mining and Technology (Assistant Professor, 2016-2017) and postdoctoral positions at Colorado School of Mines and The University of Arizona. His research focuses on hydrogeophysics, inverse modeling, and groundwater system characterization. Education: PhD (The University of Arizona), MS (China University of Geosciences), BS (China University of Mining and Technology) His work integrates geophysical methods like induced polarization and resistivity tomography with hydrological modeling to solve subsurface characterization challenges, including contaminant transport, coal seam fires, and aquifer heterogeneity. He actively collaborates with international researchers and serves on AGU committees for hydrogeophysics and groundwater. As a reviewer for major journals, he emphasizes quantitative approaches in hydrogeology and geophysics. Deqiang Mao's research has driven innovations in bioelectrochemical remediation of hydrocarbon-contaminated soils, time-domain induced polarization tomography, and high-performance computing applications in subsurface hydrology. He has co-authored numerous peer-reviewed articles in Geophysics , Water Resources Research , and Journal of Hydrology , advancing field and laboratory techniques for groundwater monitoring. He maintains an open research group at Shandong University, seeking students with quantitative backgrounds in hydrogeology or geophysics. His work bridges theoretical developments in inverse modeling with practical applications in mining hydrology, contaminant remediation, and geophysical survey optimization.
Chen Jian is the Lenovo Chair Professor at the School of Economics and Management, Tsinghua University , and Director of the Ministry of Education Key Research Base for Humanities and Social Sciences . With a career spanning over 30 years at Tsinghua, he has held multiple leadership roles in academic societies, including Vice Presidency in four top-tier Chinese academic societies and editorial positions in over ten international journals. Research Focus: Systems engineering, supply chain optimization, and decision theory Courses Taught: Dynamic systems analysis and control, operations management His scientific contributions include over 200 publications and 50 major projects, with significant impact in operations management, supply chain coordination, and emerging business models. He has trained numerous doctoral students and received prestigious accolades like the National Science Fund for Distinguished Young Scholars and IEEE Fellow status.
