جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence and Accounting
• Artificial Intelligence and Auditing
• Intelligent Finance
• +۵ مورد دیگر

Cheng Yuhan is an Assistant Professor at Shandong University's School of Management, serving as director of the Center for Artificial Intelligence and Digital Finance and recognized as a Taishan Scholar Young Expert in Shandong Province. His interdisciplinary research bridges artificial intelligence with finance, accounting, and economics through collaborations with MIT and Tsinghua University. His educational background includes: Bachelor of Science in Mathematical Sciences from Beijing Normal University Double Degree in Economics from Peking University National School of Development PhD in Finance from Tsinghua University PBC School of Finance Cheng's research focuses on AI applications in accounting, auditing, and finance, particularly large language models for financial regulation, asset pricing, and macro-finance. He integrates computational methods to solve complex financial problems using industrial-grade computing infrastructure, enabling novel approaches to traditional economic analysis. His recent publications demonstrate a clear trend toward generative AI in financial modeling, with emphasis on stock factor generation, predictive analytics, and economic forecasting. These works showcase how language models transform financial analysis through automated insight extraction and data-driven decision frameworks. Key honors include: Taishan Scholar Young Expert award Best Paper Award at 2024 China International Risk Forum Outstanding Paper Awards at 13th International Conference on Futures and Derivatives Membership in Shandong Provincial Philosophy and Social Sciences Young Talent Team Cheng mentors students across Master of Accounting, Master of Auditing, and MBA programs while securing competitive grants including National Natural Science Foundation of China Youth Fund. His lab supports students in academic exchanges, with former research assistant Dou Yun admitted to University of Chicago Economics Master's with scholarship. His research lab features industrial-grade hardware including NVIDIA H100, Huawei Ascend 910b, A100, and A800 processors, providing near-tech-company computing power for large-scale AI/finance research and industrial application development.

Hong Huaqingمشاهده پروفایل

استاد

• Corpus Linguistics
• Computer-Assisted Instruction
• Machine Translation
• +۳ مورد دیگر

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 Liمشاهده پروفایل

استاد

• AI-Empowered Distributed Systems
• MultiModal Large Models
• Embodied Intelligence
• +۹ مورد دیگر

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.

Zhumin Chenمشاهده پروفایل

استاد

• Natural Language Processing
• Artificial Intelligence
• Big Data Processing
• +۷ مورد دیگر

Zhumin Chen is a Professor and Associate Dean at the School of Artificial Intelligence, Shandong University. He serves as a member of multiple committees including the Natural Language Processing Committee of China Computer Federation (CCF) and holds leadership roles in research institutions like the Qingdao Key Laboratory of Big Data Technology Innovation. His research focuses on natural language processing, artificial intelligence, and big data, with a strong emphasis on large language models, healthcare applications, and recommendation systems. He has secured over 30 major grants including National Key Research and Development Programs and has published extensively in top venues like ACL, SIGIR, and NeurIPS. His work has been recognized with awards such as the SIGIR 2024 Best Paper Honorable Mention and the Shandong Science and Technology Progress First Prize. He leads the development of large-scale AI models and platforms, including the Shanda Intelligent Assistant, which supports teaching and research across the university. Dr. Chen collaborates with institutions like Microsoft Research Asia and Purdue University, and has co-founded multiple industry partnerships with companies such as Inspur and Hisense. His academic services include reviewing for top conferences (SIGIR, WWW, ACL) and journals, and he actively mentors students through doctoral and master’s programs.

Liu Hongyanمشاهده پروفایل

استاد

• Big data management and analysis
• machine learning
• data mining
• +۷ مورد دیگر

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).

• Intelligent imaging
• Animation games
• AIGC (Artificial Intelligence Generated Content)
• +۲ مورد دیگر

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 .

• Journalism
• Communication
• Computational Communication
• +۵ مورد دیگر

Xu Xiang is a Tenured Professor and Vice Dean at Tongji University School of Art and Media , where he serves as Director of the Big Data and Computational Communication Research Center. He is also Editor-in-Chief of Computing, Intelligence, and Communication , reviewer for CSSCI journals, and former Deputy Secretary-General of Beijing Society of Literature and Art. PhD in Literary Theory (Beijing Normal University, 2009) M.A. in Chinese Language and Literature (Tsinghua University, 2006) B.A. in Sociology (Nanjing University, 2004) His research focuses on computational communication, particularly analyzing social media networks, user behavior, and information dissemination. He established key theoretical frameworks including 'Opinion Paradigm', 'Social Echo Chamber', 'Influence Circle', 'Idol Conformity', 'Emotional Setting', and 'Silent Public Opinion', with extensive publications on social media emotional dynamics, information narrowing, and cultural communication mechanisms. His 15 most recent publications (2017-2022) demonstrate consistent exploration across computational communication theory, algorithmic platform analysis, and social media's role in cultural dissemination. Key research trends include information narrowing mechanisms, emotional preference patterns, and structural transformations in social media ecosystems. Fourth China 'News Communication Academic Award' (2018) Youth New Media Academic Research 'Qi Hao Award' (2018) National News Academic Youth Scholar Award (2012) Beijing-Taiwan Research Award (2013) Beijing Outstanding Talent Funding (2011) Tongji University '13th Five-Year Plan' Scientific Research Advanced Individual (2020) As an award-winning mentor, he guided student teams to first, second, and third prizes in multiple national competitions including China Data Journalism Competition and National Undergraduate New Media Creative Competition. His research bridges academic theory with policy practice, with findings receiving Central Politburo member instructions and extensive national media coverage.

• High-precision satellite data processing
• Earthquake rupture process inversion
• Natural disaster forecasting and early warning
• +۱ مورد دیگر

Kejie Chen is an Associate Professor (Full Research Fellow) and Doctoral Supervisor at the Department of Earth and Space Sciences, Southern University of Science and Technology , with concurrent part-time doctoral supervision at Qinghai Normal University . He holds degrees in Geophysics (PhD, GFZ/University of Potsdam), Geodesy (MS, Wuhan University), and Surveying & Mapping (BS, Chang'an University). Selected as National Overseas High-level Young Talent (2021), China Association for Science and Technology Young Talent Support Program (2020) Key participant in developing NASA JPL's real-time tsunami early warning system His research focuses on precise GNSS/InSAR data processing , multi-source earthquake rupture inversion , and AI-driven disaster prediction systems. This work spans earthquake/tsunami early warning, global change geodetic responses, and Earth observation satellite applications. Recent publications include work in Water Resources Research (2025) analyzing groundwater through satellite geodesy, demonstrating his expertise in integrating observational techniques for hydrological studies. His team's research has established novel perspectives in satellite-based water monitoring. Scientific awards include: 2023 Fu Chengyi Youth Science and Technology Award 2023 Li Shanbang Young Earthquake Science Award 2023 SUSTech Outstanding Tutor Award As an educator, he teaches Space Geodesy Applications (graduate), Geophysics Advances (graduate), and Earth Science Big Data & AI (undergraduate). His research group actively recruits PhD candidates and research assistants for Earth observation studies. Current affiliations: Correspondence reviewer for National Natural Science Foundation of China Editorial board member for Satellite Navigation and Acta Geodaetica et Cartographica Sinica Guest editor for Remote Sensing and Sustainability journals

• Atmospheric Remote Sensing
• Atmospheric Physics
• Atmospheric Environment
• +۳ مورد دیگر

Dr. Li Ying is an Associate Professor and Doctoral Supervisor at the Department of Marine Science and Engineering, Southern University of Science and Technology (SUSTech), where she directs the Center for Marine Atmospheric Sciences. Her research focuses on atmospheric aerosol remote sensing , secondary pollution numerical modeling , and ocean-atmosphere interaction studies under climate change contexts. She holds a PhD in Atmospheric Environmental Science from the Hong Kong University of Science and Technology (2011), MSc in Atmospheric Science from Peking University (2006), and BSc in Physics from Bohai University (2002) with joint study at Tsinghua University. Her professional journey includes roles as Research Assistant Professor at HKUST (2015-2016) and Postdoctoral Fellow at HKUST (2011-2015), with visiting scholar experience at the University of Tennessee (2008-2009). Her research group develops satellite-based remote sensing algorithms for aerosol components (PM2.5, black carbon), studies ozone formation mechanisms in the Pearl River Delta, and creates novel emission control evaluation methods . She leads major projects including Shenzhen Smart City Atmospheric Monitoring and Guangdong-Hong Kong-Macao Air Quality Research Team . Scientific achievements include 60+ SCI publications in journals like Remote Sensing of Environment and Environmental Science & Technology Over 2,400 citations and H-index 24 Two ESI Highly Cited Papers Recipient of Shenzhen Overseas High-level C Talent (2017)

• Consumer Behavior
• Product and Service Experience
• Decision Science
• +۳ مورد دیگر

Maggie Wenjing Liu is a tenured Associate Professor in the Department of Marketing at Tsinghua University's School of Economics and Management (SEM). She holds leadership roles as Associate Director of the Computational and Behavioral Science Lab and China Retail Research Center, and Chair of the Marketing Department's Academic Seminar Committee. Education: Ph.D. in Marketing, Rotman School of Management, University of Toronto M.S. in Marketing, NUS Business School, National University of Singapore Bachelor in Economics, University of International Business and Economics Research Focus: Her work centers on consumer behavior , product/service experience , decision science , and pricing , examining psychological mechanisms through experimental and analytical methods. Key themes include ritualistic consumption, AI-human interaction in marketing, visual branding effects, and cross-cultural service responses. Publication Trends: Recent work (2017-2025) appears in top journals like Production and Operations Management (UTD) and Journal of Consumer Psychology (FT50), revealing strong interdisciplinary connections between behavioral science, marketing strategy, and data-driven consumer insights with increasing focus on AI applications and crisis response. Scientific Awards: National Natural Science Foundation Youth Project Outstanding Evaluation (2017) National Natural Science Foundation General Project Outstanding Evaluation (2021) Tsinghua University teaching reform project Grade A (2020) Beijing Higher Education Young Elite Scholar Award Two-time Outstanding Expert Reviewer (Journal of Marketing Science) Society of Asian Retailing and Distribution Best Paper Award Advising & Grants: As a doctoral advisor, she mentors PhD candidates who frequently co-author publications. She secured three National Natural Science Foundation General Programs, one Youth Project, three provincial/ministerial grants, and multiple Tsinghua projects, with two NSFC projects rated Outstanding upon completion. Labs & Leadership: She co-directs Tsinghua SEM's Computational and Behavioral Science Lab and China Retail Research Center, driving research at the intersection of marketing analytics, consumer neuroscience, and retail innovation while serving on editorial boards for Marketing Letters and Journal of Business Research .

Wei Huمشاهده پروفایل

استاد

• Artificial Intelligence
• Knowledge Graphs
• Semantic Web Technologies
• +۵ مورد دیگر

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.

• Information Science & Library Science
• Computational Social Science
• Policy Simulation
• +۳ مورد دیگر

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).

• Semiconductor thin film materials and devices
• Material nano-characterization
• Electromechanical coupling characterization
• +۳ مورد دیگر

Huang Boyuan serves as an Associate Professor and Doctoral Supervisor in the Department of Materials Science and Engineering at Southern University of Science and Technology (SUSTech). His research group operates within the Guangdong Provincial Key Laboratory of Information Functional Oxide Materials and Devices, utilizing advanced facilities including AFM, PLD, ALD, CVD, SHG, semiconductor analyzers, and cleanroom lithography equipment. Education: Ph.D. in Mechanical Engineering, University of Washington (2016-2020) B.S. in Physics, Nanjing University (2012-2016) Huang's research focuses on developing cutting-edge characterization techniques, particularly artificial intelligence atomic force microscopy (AI-AFM) and mechanically gated transistors (MGT). His work bridges materials science, nanotechnology, and artificial intelligence to investigate nanoscale multi-field coupling mechanisms in semiconductor materials. The research group actively explores two-dimensional thin film materials, experimental mechanics, and energy material interfaces, with particular emphasis on data-driven approaches to material characterization. Huang's publication portfolio demonstrates consistent high-impact output across materials science and nanotechnology domains, with increasing emphasis on AI-integrated characterization methods. His recent work shows strong interdisciplinary connections between materials physics, machine learning, and semiconductor device engineering, reflecting the growing importance of data science in advanced material characterization. Scientific Recognition: R&D 100 Awards Finalist (2020) Shenzhen Natural Science Award (2021) Shenzhen Overseas High-level Talent (2020) National Excellent Self-financed Overseas Student Scholarship (2020) Featured in MIT Technology Review Huang has successfully secured funding for eight research projects, including the NSFC Original Exploration Plan project and Major Research Plan Integration Project. His research group actively mentors graduate students and postdoctoral fellows, with several students receiving prestigious awards and scholarships. The team maintains strong industry connections, with two authorized patents achieving technology transfer. The research group operates within state-of-the-art facilities at SUSTech, maintaining collaborative relationships with national research initiatives including the National Major Scientific Research Instrument Development Projects. Current recruitment efforts focus on doctoral candidates and research assistants specializing in two-dimensional thin film materials, experimental mechanics, and energy material interface studies.

• Ultra-low power digital circuit design
• Energy-efficient AI processor design
• Compute-in-memory
• +۵ مورد دیگر

Dr. Longyang Lin is an Assistant Professor at the School of Microelectronics, Southern University of Science and Technology (SUSTech) in Shenzhen, China. He received his Ph.D. from the National University of Singapore in 2018 and has been with SUSTech since May 2021. His research focuses on cutting-edge integrated circuit design with emphasis on ultra-low power systems, hardware security, and cryogenic circuits. Education: Ph.D., National University of Singapore, 2018 M.Sc., Lund University, 2011-2013 B.Sc., Umeå University & B.Eng., Shenzhen University, 2007-2011 Dr. Lin's research spans ultra-low power digital circuit design , energy-efficient AI processor design , compute-in-memory , on-chip sensor fusion , and cryogenic CMOS circuit design . His work addresses critical challenges in battery-less systems, hardware security, and energy-efficient computing. He has developed innovative solutions for self-powered sensor nodes, widely energy-scalable VLSI systems, and secure integrated circuits that operate across extreme temperature ranges. His recent publications demonstrate a strong focus on hardware security, ultra-low power design, and biomedical applications. The research shows a clear progression toward more integrated systems that combine sensing, processing, and communication in highly energy-constrained environments. Many papers address the challenge of maintaining performance while drastically reducing power consumption, with several targeting sub-nanowatt operation. Scientific Awards: Takuo Sugano Award for Outstanding Far-East Paper, ISSCC 2022 ISSCC Demonstration Session Certificate of Recognition, 2022 ISSCC Demonstration Session Certificate of Recognition, 2020 IEEE SSCS Singapore Chapter Award, 2017 & 2018 ISSCC Student Travel Grant Award, 2017 Dr. Lin actively mentors students and researchers, with openings for Research Assistant Professors, Postdoctoral Fellows, Research Assistants, and Graduate Students. His research group benefits from ample funding and regular tape-out opportunities (3-5 per year across different process nodes). He serves as Associate Editor for IEEE Transactions on VLSI Systems and has authored or co-authored over 40 publications, including 10 in IEEE JSSC, 5 in ISSCC, and 12 in VLSI Circuits conference. His laboratory focuses on integrated circuit design for ultra-low power applications, with specialized expertise in hardware security, energy harvesting systems, and cryogenic electronics. The research environment supports tape-outs in advanced CMOS processes, enabling practical validation of theoretical designs.

• Management Information Systems
• Business Analytics
• Decision Support Systems
• +۲ مورد دیگر

Wei Huang (Wayne) is a Chair Professor and founding dean of the College of Business at Southern University of Science & Technology (SUSTech) in Shenzhen, China. He holds the prestigious National Yangtze Chair in Management Information Systems and has over 35 years of full-time teaching and research experience across multiple continents. His academic career spans renowned institutions including University of New South Wales (Sydney, Australia), National University of Singapore (NUS), Harvard University, Chinese University of Hong Kong (CUHK), and Xi'an Jiaotong University. His research interests focus on Management Information Systems , specifically on using IS/IT to support decision-making and collaboration, and business analytics. Dr. Huang has published over 200 research papers in top-tier journals including MIS Quarterly (MISQ), Journal of Management Information Systems (JMIS), Journal of the Association for Information Systems (JAIS), and IEEE Transactions, with his work being cited by leading journals such as Management Science and ISR. His recent publications demonstrate a clear trend toward integrating emerging technologies like artificial intelligence, blockchain, and IoT with traditional business analytics to create more robust decision support systems. The research spans multiple subfields including machine learning, data visualization, collaborative technologies, and cross-cultural aspects of information systems adoption, reflecting both the breadth and depth of his scholarly contributions. AIS Fellow (2020) - second professor from a Chinese university to receive this honor Sandra Slaughter Outstanding Services Award (2018) - first mainland Chinese scholar to receive this award National Yangtze Chair in Management Information Systems Outstanding SIG Award for AIS SIG-ISAP (2017) Highest Quality Rating from the British Library Outstanding Professional Service Award of ICIS Dr. Huang has secured significant research funding from diverse sources including the Australian Research Council (ARC), National Science Foundation of China, National University of Singapore, Chinese University of Hong Kong, and Harvard University. His leadership extends beyond research to academic service where he has served as PACIS Council Chair (2019-2022), founding President of AIS SIG-ISAP for over 15 years, and key founding member of China AIS Chapter. He currently serves as Vice Chairman of the Teaching Steering Committee for Management Science and Engineering Programs at Guangdong Universities, Honorary Dean of the China Guoxin Credit Big Data Research Institute, and several other high-level advisory roles with Chinese governmental bodies.