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Liu HongyanView profile

Professor

• Big data management and analysis
• machine learning
• data mining
• +7 more

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).

Jianke ZhuView profile

Professor

• Computer Vision
• Machine Learning
• 3D Reconstruction
• +3 more

Jianke Zhu is a Professor at the College of Computer Science and Technology of Zhejiang University . He obtained his Ph.D. in Computer Science and Engineering from The Chinese University of Hong Kong and conducted postdoctoral research at the BIWI Computer Vision Lab, ETH Zurich . His research focuses on Computer Vision and Machine Learning , with a particular emphasis on 3D scene understanding, LiDAR-based mapping, and neural rendering. Dr. Zhu’s research spans several subfields, including 3D Reconstruction , Semantic Segmentation , Multimodal Learning , and Autonomous Driving . His work integrates Neural Networks , LiDAR Processing , and Uncertainty Quantification to address challenges in real-time and adverse conditions. Selected Recent Trends: 2025 publications highlight his work in Hexagonal Mesh-based Neural Rendering , Instance-aware 3D Scene Understanding , and Efficient Visual Projectors for Multimodal LLMs . Earlier works include Box2Mask for Instance Segmentation (2024) and Token Selection for Point Cloud Learning (2025). Scientific Awards : Senior member of the IEEE Advising and Grants : As a Doctoral Supervisor , he mentors students in advanced topics like LiDAR Odometry and Multi-view Stereo Recovery . His projects have attracted funding for autonomous driving , 3D scene modeling , and neural rendering .

• Information Science & Library Science
• Computational Social Science
• Policy Simulation
• +3 more

Zhuoren Jiang is a tenure-track Assistant Professor and Doctoral Supervisor at the Department of Information Resources Management, School of Public Affairs, Zhejiang University. He holds a Ph.D. and serves as a key faculty member in the department, with his office located in Room 612-2 of the School of Public Affairs building at Zhejiang University's main campus in Hangzhou. Dr. Jiang's research spans multiple interdisciplinary domains, with primary focus on Information Science & Library Science, Computational Social Science, Policy Simulation, and Artificial Intelligence Algorithms and Applications. His work bridges social science, data science, and computer science, creating innovative approaches to understanding complex social phenomena through computational methods. He has developed expertise in graph representation learning, large language models, and their applications in scientific impact prediction, legal reasoning, and policy analysis. His publication record reveals a strong trajectory in high-impact venues, with recent work focusing on multimodal business analysis, legal judgment prediction, policy style measurement, and scientific peer review systems. His research demonstrates an increasing emphasis on integrating large language models with graph-based approaches to solve complex interdisciplinary problems, particularly in the domains of legal informatics and scientific communication. Zhejiang University Teaching Excellence Award, 2024 Best Short Paper Awards Nominee, SIGIR Conference, 2024 Alibaba Research Fellowship, 2019 & 2020 Boya Postdoctoral Fellowship, Peking University, 2016 Best Poster Award, JCDL, 2013 Dr. Jiang actively mentors students and seeks highly self-motivated PhD and master's candidates interested in interdisciplinary research. He has served as principal investigator or sub-project lead for multiple research projects including National Key R&D Program, Major Projects of the National Social Science Foundation of China, and Projects of the National Natural Science Foundation of China. His academic service includes editorial board membership for Frontiers in Big Data and peer reviewing for numerous top journals including Information Processing & Management and Journal of the Association for Information Science and Technology. He maintains active collaborations with industry, having previously served as a consultant (visiting professor) at Alibaba DAMO Academy and currently as a collaborating expert at Tongyi Lab. His professional memberships include ACM (Association for Computing Machinery), ACM SIGIR, ACL (Association for Computational Linguistics), and ASIS&T (Association for Information Science and Technology).

• Artificial General Intelligence (AGI)
• Data Mining
• Social Networks
• +2 more

Jie Tang is a Professor at the Department of Computer Science, Tsinghua University , and a Fellow of ACM, AAAI, IEEE . His research focuses on Artificial General Intelligence (AGI) , with significant contributions to large pre-trained models like GLM-130B, ChatGLM, CogView, CogVideo, and CodeGeex. Research Trends : Jie Tang's work spans AGI development with human-like reasoning Graph Neural Networks for network representation Social network mining and influence modeling Academic knowledge graph construction (AMiner system) Advancing foundation models for cross-modal tasks Scientific Awards : SIGKDD Test-of-Time Award SIGKDD Service Award NSFC Distinguished Young Scholar 2nd National Award for Science & Technology Advising and Grants : He mentors highly-motivated students and postdocs in AGI research. His work has received extensive funding and recognition, including over 400 publications in top conferences (IJCAI, AAAI, NeurIPS, KDD) and journals (TPAMI, TKDE).

• Knowledge Representation and Reasoning
• Natural Language Processing
• Machine Learning
• +3 more

Xiaowang Zhang is a Full Professor at the College of Intelligence and Computing, Tianjin University, China. His research spans Knowledge Graphs, Natural Language Processing, Multi-modality, and Software Engineering, with a focus on semantic reasoning, relation extraction, and software vulnerability detection. He leads a team advising international students and contributes to open-access research in venues like ACL, WWW, and ISWC. Education : PhD from Peking University (2011), Postdoc at Hasselt University (2011-2014), Visiting Associate Professor at Griffith University (2018). His research integrates Knowledge Graphs for relation extraction and rule learning, advances LLMs in few-shot learning and cross-lingual stance detection, and addresses software engineering challenges through vulnerability description analysis and code translation error detection. Recent work emphasizes temporal reasoning and explainability in AI systems. Article trends highlight interdisciplinary applications of Knowledge Graphs in NLP tasks, leveraging graph structures for QA systems, and improving software security through feature inference and multi-interest recommendation frameworks. While no explicit awards are listed, his collaborations with institutions like Griffith University and Hasselt University demonstrate global academic engagement. He advises international students and emphasizes programming skills, communication, and teamwork in future advisees. His full_description expands on 15+ years of contributions to knowledge representation, semantic networks, and code generation systems.

Zhiyuan LiuView profile

Associate Professor

• Large Language Models
• Natural Language Processing
• Knowledge Graphs
• +4 more

Zhiyuan Liu is a Tenured Associate Professor in the Department of Computer Science and Technology at Tsinghua University, Beijing, China. He has held this position since December 2021, having progressed through the ranks from Assistant Professor (2016-2017), Tenure-track Associate Professor (2017-2021), and Assistant Researcher (2013-2016). His academic journey at Tsinghua began with his undergraduate studies (2002-2006), continued through his PhD (2006-2011), and included a postdoctoral fellowship (2011-2013). Dr. Liu's research centers on Large Language Models , Natural Language Processing , Knowledge Graphs , and Social Computing . His work spans knowledge-guided NLP, representation learning, and practical applications in domains including legal intelligence and multimodal systems. He has made significant contributions to knowledge representation learning, network embedding techniques, and few-shot natural language processing methodologies. His publication record demonstrates a clear evolution toward large-scale language models and knowledge-integrated NLP systems. Recent work focuses on efficient pretraining and fine-tuning methods for LLMs, multimodal LLMs, tool learning with LLMs, and domain-specific large models for scientific intelligence. His research shows strong interdisciplinary applications, particularly in legal intelligence and social computing, with several papers receiving prestigious recognition including F5000 awards and conference best paper honors. First Prize of Qian Weichang Chinese Information Processing Science and Technology Award (2024) World Internet Conference Awards for Pioneering Science and Technology (2023, 2022) Wu Wenjun Artificial Intelligence Science and Technology Award (2023) First Prize of the State Natural Science Award (2022, 2020) MIT Technology Review 35 Innovators Under 35, China (2018) National Young Talents Program (2020) Dr. Liu has mentored over 20 PhD students and numerous Master's students, many of whom have received top honors including Tsinghua Outstanding PhD Theses, Beijing Outstanding Graduate awards, and Siebel Scholarships. His research is supported by major grants including the Key Program of the National Natural Science Foundation of China for 'Theories and Methods of Few-shot Natural Language Processing' (2023-2027), and the Beijing Municipal Science & Technology Commission project on 'Sparse Modular Large Model Technology' (2023-2025). He leads research in the Natural Language Processing Laboratory at Tsinghua University, where his team develops cutting-edge LLM infrastructure, knowledge computing systems, and applications in legal intelligence. The lab maintains strong industry collaborations with Tencent, Baidu, and AMD, and has contributed to several successful startups emerging from his research.

Yepang LiuView profile

Associate Professor

• Software Testing and Analysis
• Adaptive Systems
• Mobile Computing
• +4 more

Yepang Liu is a tenured Associate Professor in the Department of Computer Science and Engineering at Southern University of Science and Technology (SUSTech). He leads the Software Quality Lab and directs the Trustworthy Software Research Center under the Research Institute of Trustworthy Autonomous Systems. His academic journey includes a B.Sc. in Computer Science from Nanjing University (2010) and a Ph.D. in Computer Science and Engineering from The Hong Kong University of Science and Technology (HKUST) in 2015, followed by postdoctoral research at HKUST's CASTLE Lab and Cybersecurity Lab (2015–2018). Research interests focus on Software Testing and Analysis Empirical Software Engineering AI for Software Engineering (AI4SE) Trustworthy AI Mobile Computing Software Security Current projects explore automated testing for emerging technologies like HarmonyOS and extended reality (XR), leveraging large language models (LLMs) and reinforcement learning. Awarded thrice with ACM SIGSOFT Distinguished Paper Awards (ICSE 2021, ASE 2016, ICSE 2014) and a Platinum Level Research Artifacts Honor (FSE 2016), Liu has also received teaching accolades, including SUSTech's Junior Faculty of the Year (2021) and the Top-10 Most Popular Instructor Among 2024 Graduates. His work is funded by the National Natural Science Foundation of China, National Key Research and Development Program of China, and industry partnerships.

Wei ChenView profile

Professor

• Data Visualization
• Visual Analytics
• Biomedical Image Computing
• +5 more

Wei Chen is a Professor at the State Key Laboratory of CAD&CG, College of Computer Science, Zhejiang University, Hangzhou, China. His academic journey began and ended at Zhejiang University, where he earned both his Bachelor's (1996) and Ph.D. (2002) in Computer Science, followed by a visiting Ph.D. position at the Fraunhofer Institute in Germany (2000-2002) and a visiting scholar role at Purdue University (2006-2008). Research Focus: Visualization, Visual Analytics, Biomedical Image Computing, Big Data Analytics. Academic Leadership: Served on editorial boards of journals like IEEE Transactions on Visualization and Computer Graphics, Journal of Visual Informatics, and as Chair of IEEE Pacific Visualization Symposium. Impact: Over 110 IEEE/ACM Transactions and CCF-A papers, four Chinese textbooks on visualization, and two monographs on big data technology. His recent publications (2023-2024) span domains like visual analytics for health insurance fraud detection, quantum circuit visualization, federated learning visualization, urban mobility modeling, and AI-enhanced cultural heritage preservation. A thematic trend shows integration of deep learning, large language models, and human-in-the-loop systems with visual interfaces. Scientific Awards include the Zhejiang Province Natural Science First Prize (2021, 2017), CCF Technology Invention First Prize (2020), Wu Wenjun Artificial Intelligence Science and Technology Progress First Prize (2023), and multiple Best Paper/Poster recognitions at IEEE VIS and Pacific Visualization conferences. He actively mentors graduate students and leads the Visual Analytics Group , contributing to national and international standards in visualization research. His editorial and organizational roles in top conferences further solidify his influence in shaping the field.

Andrew Chi-Chih YaoView profile

Professor

• Algorithms
• Cryptography
• Quantum Computing
• +3 more

Andrew Chi-Chih Yao is a distinguished Professor and Dean at Tsinghua University, leading the College of AI and the Institute for Interdisciplinary Information Sciences. He holds dual roles as Professor at Tsinghua's Center for Advanced Study and Distinguished Professor-At-Large at The Chinese University of Hong Kong. His academic journey includes professorships at MIT, Stanford, UC Berkeley, and Princeton University (1986–2004). Education: Ph.D. in Physics (Harvard, 1972) and Ph.D. in Computer Science (University of Illinois, 1975). Research focuses on Algorithms, Cryptography, Quantum Computing, and Artificial Intelligence. He pioneered foundational work in communication complexity, secure computation protocols, and quantum circuit theory. His contributions to computational theory include Yao’s minimax principle and the millionaires’ problem framework for privacy-preserving computation. Recent publications address AI safety, quantum replication, and secure systems for global challenges like DNA synthesis and emissions trading. His 2024 work on AI risk management underscores ongoing engagement with cutting-edge tech ethics. Awards: Kyoto Prize (2021), Turing Award (2000), Pólya Prize (1987), and over 20 honorary doctorates. Grants/Advisory Roles: Key contributor to interdisciplinary initiatives at Tsinghua, including AI and blockchain research. Advised projects on secure computing and cryptographic protocols. Labs/Teams: Leads teams in quantum computing, AI ethics, and secure multiparty computation at Tsinghua.

• Neuroscience
• Machine Learning
• Control Theory
• +4 more

Dr. LIU Quanying is an Associate Professor in the Department of Biomedical Engineering at the Southern University of Science and Technology (SUSTech), where she has been a faculty member since September 2019. She serves as the Principal Investigator of the Neural Computing and Control Laboratory (NCC lab) and is a doctoral supervisor. Prior to joining SUSTech, she earned her PhD in Biomedical Engineering from ETH Zurich and conducted postdoctoral research at Caltech. Education: PhD in Biomedical Engineering, ETH Zurich (2013-2017) Master in Computer Science, Lanzhou University (2010-2013) Bachelor in Electrical Engineering, Lanzhou University (2006-2010) Research Interests: Dr. Liu’s research integrates neuroscience, machine learning, and control theory. Her work focuses on multi-modal neural signal processing (EEG, sEEG, fMRI, DTI), explainable AI for neuroscience, and optimization techniques for neuromodulation (tES, TMS). She has developed high-density EEG source localization algorithms and data-driven brain network modeling frameworks, aiming to enhance precision in neural stimulation and control. Scientific Awards: The New Brain 30 (2023) AAIC Travel Award (2019) Estes Stars Award (2018) 深圳市孔雀人才计划C类 Laboratory and Team: As the PI of the NCC lab, Dr. Liu leads a team focused on machine learning algorithms, neurocomputational modeling, and neurofeedback control. The lab actively recruits graduate students, postdocs, and visiting researchers, emphasizing interdisciplinary collaboration in neuroscience and AI.

Guanhua ChenView profile

Assistant Professor

• Natural Language Processing (NLP)
• Large Language Models (LLMs)
• Applied Machine Learning
• +4 more

Dr. Guanhua Chen is an Assistant Professor in the Department of Statistics and Data Science at Southern University of Science and Technology (SUSTech). His research focuses on Natural Language Processing (NLP), Large Language Models (LLMs), and Multimodal AI, with applications in drug discovery and urban planning. He previously earned his Ph.D. from the University of Hong Kong and B.S./M.S. from Tsinghua University, with internships at Microsoft Research Asia and Huawei Noah’s Ark Lab. Education: Ph.D. in Computer Science (University of Hong Kong, 2022), B.S. and M.S. in Computer Science (Tsinghua University, 2012 & 2014) Dr. Chen's research explores LLMs, data synthesis, multimodal systems, and model compression. He leads a lab equipped with 16 RTX 4090 GPUs, 16 L40 GPUs, and 4 A100 GPUs, providing resources for students to experiment with open-source and proprietary LLM APIs. His recent publications highlight innovations in LLM jailbreaking, parameter-efficient tuning (MiLoRA), cross-lingual transfer (mCLIP), and evaluation frameworks for robustness testing. Notably, he was awarded the Microsoft Research Asia StarTrack Scholar in 2025. Key Publications: mCLIP (ACL 2023), ImPart (ACL 2025), MiLoRA (NAACL 2025) Dr. Chen actively seeks motivated PostDoc, PhD, and Master's students. He serves as an Area Chair for ACL and EMNLP and contributes to advancing AI through open-source projects like mCLIP on GitHub.