Dr. Jiamin Li is an Associate Professor at the School of Microelectronics, Southern University of Science and Technology (SUSTech), Shenzhen, China. She holds a Ph.D. and B.Eng. in Electrical and Computer Engineering from the National University of Singapore (NUS). Her research focuses on biomedical integrated circuits, energy harvesting, and wireless body-area networks. Education: Ph.D. and B.Eng. in Electrical and Computer Engineering from NUS Employment: Associate Professor (2024–Present), Assistant Professor (2022–2024) at SUSTech; Research Fellow at NUS Dr. Li's research addresses wireless body area powering , low-power biosignal interfaces , and intelligent biosignal processors . Her work leverages microsystem design for applications in biomedical engineering , particularly in energy-autonomous medical devices and human body-coupled communication . Her recent publications highlight advancements in concurrent power/data transmission , subharmonic pulse injection , and triboelectric energy harvesting for biomedical systems. Key venues include IEEE JSSC , Nature Electronics , and conferences like ISSCC and BioCAS. Awards: IEEE SSCS Predoctoral Achievement Award, ISSCC Best Demo Award, ASSCC SDC Best Design Award Committees: IEEE SSCS Women-in-Circuit (WiC) Committee, ISSCC Student Research Preview Committee Opportunities: Positions available for Ph.D., Master's, Postdoctoral Fellows, and Visiting Scholars
Dr. Yi-Feng Chen is a Research Assistant Professor and Master's Supervisor in the Department of Biomedical Engineering at the Southern University of Science and Technology (SUSTech) in Shenzhen, China. He joined SUSTech as a postdoctoral fellow in November 2020 and was promoted to Research Assistant Professor in February 2023. His academic journey includes interdisciplinary training across engineering, neuroscience, and biomedical applications. Dr. Chen's educational background includes: Ph.D. in Engineering from Wuhan University of Technology (2014-2017), supervised by Professor Quan Liu M.Sc. from Wuhan University of Technology (2011-2014), supervised by Professor Zhou Zude B.Sc. from Wuhan University of Technology (2007-2011) He also participated in exchange programs at Yuan Ze University in Taiwan (2012) and the University of Auckland in New Zealand (2015). Dr. Chen's research spans the intersection of biomedical engineering, neuroscience, and artificial intelligence, with particular focus on brain-computer interfaces and rehabilitation technologies. His work combines advanced signal processing techniques with clinical applications, especially in decoding neural signals for movement intention and monitoring brain states during anesthesia. His research has significant implications for neurorehabilitation, assistive technologies, and intraoperative neurophysiological monitoring. His recent publications demonstrate a clear trajectory toward increasingly sophisticated neural decoding techniques, with a focus on coordinated limb movements and practical rehabilitation applications. The work shows progression from basic EEG signal processing to complex bimanual movement decoding and robot-assisted rehabilitation systems, reflecting a translational research approach from basic science to clinical applications. Dr. Chen has secured significant research funding as principal investigator and core contributor on multiple projects: National Natural Science Foundation of China Youth Science Fund Project (2024-2026) Guangdong Natural Science Foundation General Project (2024-2026) Ministry of Science and Technology National Key R&D Program Project (2023-2026) Shenzhen Science and Technology Innovation Commission Key Project (2022-2025) As a Master's Supervisor, Dr. Chen mentors graduate students in biomedical engineering with focus on neural engineering and rehabilitation robotics. His laboratory collaborates closely with clinical partners to ensure research relevance to real-world medical challenges, particularly in neurorehabilitation and intraoperative monitoring.
Wei Zhang is a tenured Professor at the Southern University of Science and Technology (SUSTech) , Shenzhen, China, and a Senior Member of IEEE. He serves as Associate Editor for IEEE Transactions on Control System Technology and leads the CLEAR Lab (Control & Learning for Robotics and Autonomy) within the School of Automation and Intelligent Manufacturing (AiM). His career spans institutions including the University of California, Berkeley (postdoc), and The Ohio State University (Assistant/Associate Professor). Education: PhD in Electrical Engineering from Purdue University (2009), MS in Electrical and Computer Engineering from University of Kentucky (2005), BS in Automation from University of Science and Technology of China (2003) Research Interests focus on integrating control theory, optimization, and machine learning to develop intelligent systems. Key areas include: Legged Robots: Dynamic locomotion control, bio-inspired gait design, and push recovery mechanisms Autonomous Systems: Real-time motion planning, obstacle avoidance, and safe navigation in adversarial environments Smart Grids: Distributed control for energy systems and transactive energy optimization Machine Learning: Reinforcement learning for robotics, Q-learning convergence analysis, and hybrid control-learning frameworks Publication Trends highlight interdisciplinary work at the intersection of robotics and control systems. His recent 2024 papers address: Whole-body control for wheeled-quadrupedal robots Geometric object pose refinement in computer vision Task-space Riccati feedback for underactuated systems Teacher-student reinforcement learning architectures Scientific Awards include: 2016 : NSF CAREER Award 2015 : Lumley Research Award (Ohio State University) 2013 : AFOSR Summer Faculty Fellowship 2018 : National Distinguished Expert (Young, China) 2019 : International Underwater Robot Competition 2nd Prize (team advisor) Academic Leadership involves editorial roles at IEEE Transactions on Control System Technology and IEEE Transactions on Power Systems. His lab provides state-of-the-art robotics platforms including quadruped robots, Kuka manipulators, and UAVs for algorithm validation. Research collaborators span The Ohio State University , UC Berkeley , CMU , and The University of Hong Kong .
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.
Dr. Yanqing Hu is an Associate Professor at the Department of Statistics and Data Science, School of Science, Southern University of Science and Technology (SUSTech). With a Ph.D. in Systems Theory from Beijing Normal University (2011) and postdoctoral experience at the Levich Institute, City University of New York (2011-2013), his work focuses on big data analysis of complex systems, particularly in social media dynamics, network resilience, and graph neural network applications. Ph.D.: Beijing Normal University (Systems Theory, 2011) Postdoctoral: Levich Institute, CUNY (2011-2013) Research spans complex network analysis, information spreading mechanisms, and predictability of network structures. His work combines theoretical frameworks with real-world applications in social networks, infrastructure systems, and brain connectivity. Recent publications explore information percolation in social media, resilience quantification in interdependent networks, and intrinsic structure predictability. These studies appear in high-impact journals like Nature Human Behaviour (IF: 24.3), Nature Communications (IF: 17.7), and PNAS (IF: 10). World AI Conference Youth Outstanding Paper Nomination Beijing Outstanding Doctoral Dissertation Award Guangdong Special Support for Young Talents Guangdong Outstanding Youth Fund Collaborations include leading researchers from Boston University, King's College London, and Shenzhen-Hong Kong Institute of Microelectronics. His work informs network defense strategies and efficient navigation mechanisms in complex systems.
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.
Wang Jianmin serves as Professor and Doctoral Supervisor at Tongji University's School of Art and Media, concurrently holding the position of Vice Dean since 2014. With a computer science PhD from Sun Yat-sen University, he bridges engineering and media arts through pioneering research in intelligent communication systems and digital media interfaces. His work focuses on human-centered design for emerging technologies, particularly in automotive and virtual environments. His academic foundation includes: PhD in Engineering (Computer Software and Theory), Sun Yat-sen University (2003) Master's in Computational Mathematics, Sun Yat-sen University (1999) Bachelor's in Computational Mathematics, Nankai University (1996) Professor Wang's research centers on intelligent communication systems and digital media art, with significant contributions to automotive human-machine interfaces (HMI), virtual reality applications, and user experience methodologies. His investigations into driver-robot transparency, augmented reality navigation, and mixed-reality educational platforms demonstrate interdisciplinary innovation connecting computer science, cognitive psychology, and design theory. Current projects explore AI-driven media systems for urban environments and safety-critical interaction frameworks. Analysis of his recent publications reveals a cohesive research trajectory focusing on automotive HMI (40% of output), human-robot interaction (30%), and mixed reality applications (30%). His work consistently emphasizes experimental validation through driving simulators and user studies, yielding practical design guidelines for industry implementation. The interdisciplinary nature spans computer science, cognitive ergonomics, and media studies, with increasing emphasis on AI integration in communication systems. His scientific recognition includes national and provincial awards for innovation in human-computer interaction and educational technology: 2019 China Industry-University-Research Innovation Award for automotive HMI systems 2020 China User Experience Alliance Excellence Award 2012 Guangdong Dingying Science and Technology Award Multiple national/provincial science progress awards (2001-2009) 2020 Tongji University Teaching Achievement Award for curriculum development As an educator, Professor Wang mentors graduate students in national design competitions including the 'Core Cup' Future Automotive HMI Challenge and International User Experience Innovation Competition. His research program is supported by substantial funding from diverse sources: National Grants: National Natural Science Foundation projects on driver behavior modeling and cognitive testing Ministry of Education: 15+产学合作 projects for virtual simulation labs and curriculum development Shanghai Municipal: Publicity Department funding for smart city media research Industry Partnerships: Huawei (intelligent vehicle HMI), SAIC Motor (AR-HUD design), and automotive electronics firms He directs Tongji's Media Experiment and Practice Teaching Center and the All-Media Research Institute, leading teams developing virtual simulation platforms for emergency news reporting, intelligent vehicle interaction testing systems, and mixed reality educational tools. Current initiatives focus on AI-enhanced media art for urban applications and next-generation HMI frameworks for autonomous mobility solutions.
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.
Zhan Ma is a Professor and PhD Advisor at the School of Electronic Science and Engineering, Nanjing University. He leads research in Neural Video Communication, Smart Cameras, and Computational Vision Models. His work focuses on end-to-end learning for compression, networking, and hardware-software co-design. Dr. Ma holds a PhD from New York University's Tandon School of Engineering (2010), and prior to his current role, he served as Senior Staff Researcher at Huawei (2013-2015) and Senior Researcher at Samsung (2011-2013). Research highlights include pioneering work in point cloud compression (adopted into IEEE standards) and dual-camera systems for high-resolution video acquisition. His algorithms are deployed in WeChat/WeChat Video for rate-quality optimization and in ISO standards for video complexity indicators. Recent work emphasizes machine learning-driven approaches for image/video compression and adaptive streaming frameworks. Honors include the 2023 IEEE CAS Society Outstanding Young Author Award and multiple best paper awards at IEEE WACV, BMSB, and other venues. He leads the Vision Lab at Nanjing University and collaborates with industry partners on practical implementations of his research.
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).
Zhu Yan serves as Professor at Tsinghua University's School of Economics and Management, Department of Management Science and Engineering. He concurrently holds leadership positions as Dean of Tsinghua's Internet Industry Research Institute, Director of the Advanced Information Technology Business Application Laboratory, and Executive Deputy Director of the Medical Management Research Center. Education: Postdoctoral Fellow (1998-2000) and Ph.D. in Nuclear Energy Technology (1994-1998) at Tsinghua University, Bachelor's in Engineering Physics (1989-1994) Professional Experience: Professor (2010-present), Associate Professor (2002-2010), Lecturer (2000-2002); Visiting Scholar at MIT Sloan, CUHK, and Lancelot Institute Professor Zhu's research spans digital transformation , industrial blockchain , and digital production relations , with emphasis on practical applications in healthcare, construction, and finance. His work bridges theoretical frameworks with industry implementation, particularly in China's digital economy evolution. Current projects focus on industrial internet integration and digital finance systems. His 15 most recent publications demonstrate strong interdisciplinary focus, connecting information systems with healthcare analytics (40%), industrial digitalization (35%), and economic policy (25%). The research shows increasing emphasis on AI-driven diagnostic systems and pandemic-responsive economic strategies since 2020. Beijing Philosophy and Social Sciences Excellent Achievement Award (2020) China Petroleum and Chemical Automation Association Science and Technology Progress Award (2010) Multiple Beijing Science and Technology Progress Awards (2001, 2005) Tsinghua University Outstanding Teaching Award (1999) As academic advisor to national initiatives, Professor Zhu leads the China Technology Economics Society's Blockchain Division and serves as Chief Academic Officer for Chengdu University of Information Technology's Blockchain Industry College. His industry partnerships include SAP Global HR Advisory role since 2000 and CCTV Financial Commentary position since 2015. Current research funding focuses on digital infrastructure development through the Industrial Digital Finance Technology Application Laboratory. He directs the Advanced Information Technology Business Application Laboratory, which develops enterprise digital transformation frameworks, and co-leads the Medical Management Research Center's AI diagnostic initiatives. Current projects include national blockchain infrastructure development and pandemic-resilient supply chain systems.
Li Zhongfei is a Chair Professor and Vice Dean of the School of Business at Southern University of Science and Technology (SUSTech). He is a member of the State Council's Discipline Review Group, National Outstanding Young Scientist, National Model Teacher, and recipient of the State Council's Special Government Allowance. His career spans roles as Distinguished Professor at Lingnan College, Executive Dean at Sun Yat-sen University, and leadership positions in academic societies such as the Chinese Society for Systems Engineering. Education : PhD in Management (1997-2000) and Master's in Operations Management (1988-1990) from the Chinese Academy of Sciences, and a Bachelor of Science in Mathematics from Lanzhou University. Research Interests : His work focuses on Technological Finance Green Finance Pension Finance Financial Engineering and Risk Management Insurance and Actuarial Science with applications to financial markets, digital finance, and sustainability. Scientific Trends from his publications include: ESG rating impacts on capital markets Green innovation under carbon pricing Machine learning in cryptocurrency forecasting Robust portfolio optimization under uncertainty Climate risk and policy analysis Post-pandemic economic recovery and systemic risk Scientific Awards : Recipient of the National Teaching Achievement Award, Guangdong Province Philosophy and Social Sciences prizes, Zhong Jiaqing Operations Research Award, and recognition as a Top 2% Scientist (Stanford, 2023). He was honored as a National Model Teacher and 'Top Ten Most Respected Business School Deans in China.' Grants & Projects : Principal investigator in NSFC key projects, including 'Intelligent Investment and Risk Management under Dual Carbon Strategy' and 'Financial Innovation and Risk Management.' His projects address fintech, pension funds, and climate risk. Labs & Teams : Leads advanced research teams in SUSTech's School of Business and collaborates with international institutions like the University of Waterloo and Hong Kong Polytechnic University.
Andrew I. Cooper is a Professor at the University of Liverpool, Director of the Materials Innovation Factory, and Honorary Professor at East China University of Science and Technology (ECUST). He pioneers research in advanced organic functional materials, including conjugated microporous polymers, porous organic cages, and porous liquids, and developed the first autonomous mobile robotic chemist. Fields of Interest: Materials chemistry, robotics, AI-driven synthesis, and computational design of functional materials. Scientific Impact: Over 200 SCI-indexed papers, 52,000+ citations, H-index 117. Key journals: Nature , Science , JACS , Angewandte Chemie . Awards: Royal Society of Chemistry Professorship, Outstanding AI Leader award, Fellow of the Royal Society and European Academy of Sciences. Leadership: Editor-in-Chief of Chemical Science , trained 47 Chinese postdoctoral fellows and PhD students, and leads international collaborations with Chinese universities. Research Trends: Articles focus on robotics, AI, computational materials design, photocatalysis, and dynamic porosity in molecular systems.
Shunxiang Cao is an Assistant Professor at Tsinghua Shenzhen International Graduate School in China, where he has worked since July 2022. He earned his Ph.D. in Aerospace Engineering from Virginia Tech (United States) between August 2014 and August 2020 and completed his B.S. in Aerospace Engineering at Beihang University (China) from September 2010 to May 2014. Prior to his current role, he served as a Postdoctoral Scholar at the California Institute of Technology (United States) from November 2019 to May 2022. Teaches courses such as Advanced Numerical Analysis, Numerical Methods for PDEs, and Fluid-Structure Interaction simulations. Research Interests include fluid-structure interaction, computational fluid dynamics, shock/bubble dynamics, material failure analysis, embedded-boundary methods, resolvent-based optimization, Kalman inversion, high-intensity focused ultrasound, and digital twin technology. His work focuses on numerical modeling, optimization, and fluid-solid coupling mechanisms in diverse applications like underwater propulsion, energy storage membranes, and medical acoustics. Scientific Awards include the USNCCM16 Conference Award (2021), Graduate Fellowship at Virginia Tech (2014-2015), Merit Undergraduate Student in Beijing (2014), and Singapore Technology Engineering Fellowship (2010-2013).
Dr. Bai Ziqian is an Assistant Professor in the School of Automation and Intelligent Manufacturing at Southern University of Science and Technology (SUSTech) in Shenzhen, China. Recognized as a Pujiang Scholar and Shenzhen Pengcheng Peacock Talent, she has established herself as a leading researcher at the intersection of wearable technology, textile engineering, and human-computer interaction. Her work bridges technical innovation with practical design applications, focusing on user-centered solutions that enhance human experience through technology integration. Dr. Bai's educational background includes: PhD in Smart Wearable Product Design (2011-2015), Hong Kong Polytechnic University MA in Fashion and Textile Design (2005-2006), Hong Kong Polytechnic University BA in Fashion Design and Engineering (2001-2005), South China Agricultural University Her research spans wearable technology, tangible interactive interfaces, IoTs, ergonomics, functional garments, wearables for healthcare, material innovation, smart home applications, and user-centered design. Dr. Bai has pioneered work in smart wearable fabrics and sensing mechanisms based on flexible materials, with a particular focus on human-computer interaction theory and practice. She has established a research team that has mastered key technologies in smart fabrics, interactive textiles, physiological signal monitoring, and human-computer interaction systems. Her approach consistently emphasizes user-centered design principles, ensuring that technological innovations serve practical human needs while maintaining aesthetic appeal. Dr. Bai's publication record demonstrates a clear evolution from foundational work in photonic textiles toward increasingly sophisticated wearable healthcare and human-computer interaction systems. Her recent publications focus on advanced sensor technologies, energy harvesting for wearables, and sophisticated data analysis for human motion and physiological monitoring. The interdisciplinary nature of her work is evident in publications spanning materials science, biomedical engineering, textile technology, and design methodology, with papers appearing in high-impact journals including Advanced Functional Materials (IF: 19.5), ACS Sensors (IF: 8.9), and Computers in Industry (IF: 10). Dr. Bai has received numerous prestigious awards that highlight both the technical and artistic dimensions of her work: 2024 German Red Dot Design Award for Best Design 2013 Neo-Neon, permanent collection at China Silk Museum (State grade 1 museum) 2019 Finalist, ThermoBlanket, TechStyle for Social Good International Competition 2017 1st Prize Teaching Award, Donghua University 2017 China National Textile and Apparel Council Teaching Award Multiple Service Learning Awards from Hong Kong Polytechnic University She has successfully secured research funding from prestigious sources including the National Natural Science Foundation of China and Guangdong Province's General Project. Her projects include a collaborative effort with the Guangdong Provincial Department of Education and Li Ning Company on a 'flexible wearable lower limb functional electrical stimulation system.' Dr. Bai has extensive teaching experience across multiple institutions and has guided student teams to success in national competitions. She currently leads the Human-Computer Interaction Design Laboratory (HCID) at SUSTech, which focuses on advanced design, engineering, and technology research at the intersection of disciplines, training the next generation of interdisciplinary designers and engineers.
