Find Academic Supervisors

• Quantum Computing
• MEMS Sensors
• Analog Circuit Design
• +5 more

Hua Chen is an Associate Researcher and PhD Supervisor at the School of Quantum Science and Engineering at Southern University of Science and Technology (SUSTech), with extensive experience in quantum computing circuit design and MEMS sensor interfaces. Previously, he served as an Associate Researcher at the Institute of Microelectronics, Chinese Academy of Sciences (2021-2022) and as an Assistant Researcher there from 2017-2021, building on his industry experience as an RF/Analog IC Design Engineer at Southwest Integrated Circuit Design Co., Ltd (2007-2010). Education: Ph.D. in Microelectronics and Solid-State Electronics, University of Chinese Academy of Sciences (2014-2017) M.Eng. in Electronic and Communication Engineering, University of Chinese Academy of Sciences (2011-2014) B.Eng. in Microelectronics, Chongqing University of Posts and Telecommunications (2003-2007) Dr. Chen's research focuses on interface circuit design for quantum computing and MEMS sensors, with particular expertise in high performance analog/RF/mixed-signal IC design. His recent work has shifted toward cryogenic circuit design for quantum bit control and readout systems, representing a strategic pivot toward China's national priority in quantum information technology. His publications reveal a consistent trajectory from MEMS gyroscopes and oscillators toward quantum computing hardware support circuits, demonstrating his ability to adapt expertise to emerging technological frontiers. Dr. Chen's research output shows a clear evolution from traditional MEMS sensor interfaces toward quantum cryogenic electronics, with his 15 most recent publications heavily concentrated in cryogenic circuit design for quantum applications. This represents a strategic shift aligning with China's substantial investment in quantum computing research, particularly in the development of control and readout electronics for scalable quantum systems. His significant honors include: Special talent of Shenzhen's Pengcheng Peacock Plan (January 2024) IEEE Senior Member (February 2022) Intellectual Property Specialist of Chinese Academy of Sciences (January 2020) Outstanding Employee (Top 10%) at Institute of Microelectronics CAS (2020) Multiple Graduate Student Scholarships from Institute of Microelectronics CAS (2015-2017) As a PhD Supervisor at SUSTech, Dr. Chen mentors graduate students in quantum circuit design while leading research funded through multiple sources including a Beijing Natural Science Foundation General Project (RMB 200,000) for RF MEMS disk oscillator drive circuits and a Youth Project (RMB 100,000) for MEMS gyroscope phase alignment. He has also participated in major national projects totaling over RMB 27 million, demonstrating his integration into China's strategic research initiatives. Dr. Chen leads a research group at the International Quantum Academy in Shenzhen focused on cryogenic CMOS integrated circuit design for quantum computing applications. His team develops specialized low-temperature measurement and control chips that address critical challenges in scaling quantum computing systems, with particular emphasis on MEMS-based quantum frequency references and cryogenic amplifiers that operate at temperatures near absolute zero.

• Quantum Dot Light-Emitting Diodes (QLEDs)
• Organic Light-Emitting Diodes (OLEDs)
• Device Physics
• +3 more

Prof. CHEN Shuming is a Tenured Professor and Doctoral Supervisor at the Department of Electronic and Electrical Engineering , Southern University of Science and Technology (SUSTech) . He has held academic positions since joining SUSTech in 2013 and was promoted to Professor in 2024. Education: PhD in Electronic and Computer Engineering (HKUST, 2012), Master in Optical Engineering (Sun Yat-sen University, 2008), Bachelor in Optoelectronics (South China University of Technology, 2005) Research Focus: Prof. Chen specializes in quantum dot light-emitting diodes (QLEDs) and organic light-emitting diodes (OLEDs) , with expertise in device engineering , device physics , and display/lighting applications . His work includes: Novel device structures (tandem, top-emitting, flexible) Charge transport and exciton dynamics Low-cost fabrication techniques (inkjet printing, laminating) Publication Trends: His recent papers address QLED stability , high-efficiency architectures , and AC-compatible devices , reflecting advancements in quantum dot technology and consumer electronics integration . Scientific Awards: Guangdong Natural Science Award (2024) Shenzhen Youth Science and Technology Award (2017) China Invention Association Innovation Award (2024) International Society for Information Display Outstanding Paper Award (2018) Advising and Grants: Prof. Chen has supervised 6 doctoral students, 5 master's students, and multiple undergraduates. He has led over 10 major projects, including National Natural Science Foundation grants and National Key R&D Program initiatives.

• Super-resolution microscopy
• 3D imaging techniques
• Biomedical Engineering
• +3 more

Yiming Li is an Associate Professor in the Department of Biomedical Engineering at Southern University of Science and Technology's School of of Engineering. His research focuses on cutting-edge 3D super-resolution imaging techniques and their biological applications, with expertise spanning optical instrumentation, theoretical optics, and advanced imaging algorithms developed during his postdoctoral work at EMBL and Yale University. Education: Ph.D. in Biophysics, Karlsruhe Institute of Technology (2010-2015) M.Sc. in Medical Physics, Heidelberg University (2009-2010) B.Eng. in Biomedical Engineering, Shanghai Jiao Tong University (2005-2009) Research Interests: Dr. Li specializes in developing advanced 3D super-resolution microscopy techniques with particular expertise in single-molecule localization microscopy , point spread function engineering , and real-time 3D imaging systems. His work bridges optical physics and biological applications, enabling nanoscale observation of cellular processes. His software earned first place in the SMLM Challenge 2016, the field's most prestigious software contest. Publication Trends: Dr. Li's research shows a clear progression from fundamental algorithm development to comprehensive imaging system design, with increasing emphasis on real-time 3D applications. His publications in Nature Methods, Nature Communications, and other high-impact journals demonstrate consistent innovation in super-resolution microscopy, particularly in point spread function calibration, aberration correction, and biological applications at the nanoscale level. Scientific Awards: National Overseas High-level Talents (Youth Program) (2020) Shenzhen Overseas High-level Talents Category B EMBL-EIPOD Marie Curie Postdoc Fellowship (2016-2019) Karlsruhe School of Optics and Photonics Fellowship (2010-2013) International Symposium on Biomedical Imaging Travel Grant (2013) Professional Activities: As a PhD supervisor at SUSTech, Dr. Li mentors graduate students in biomedical engineering. He serves as a reviewer for top journals including Nature Methods, Light: Science & Applications, and Optics Letters. His laboratory maintains active international collaborations with EMBL, Yale University, Oxford University, and Cambridge University, facilitating cross-institutional research in advanced imaging techniques. Research Laboratory: Dr. Li leads an active research group focused on next-generation imaging technologies, operating under the website https://li-lab-sustech.github.io/ . His laboratory combines theoretical optics, software development, and biological applications to push the boundaries of what's possible in optical microscopy for cellular and subcellular observation.

• Additive Manufacturing
• Ceramics
• Nanocomposites
• +7 more

BAI Jiaming is an Associate Professor at the Department of Mechanical and Energy Engineering, College of Engineering, Southern University of Science and Technology (SUSTech). His research focuses on additive manufacturing (3D printing) of ceramics, nanocomposites, and functional materials, with applications in energy, biomedical engineering, aerospace, and electronics. Education: PhD (2014), MSc (2009), Loughborough University; BSc (2008), Beijing University of Chemical Technology Research interests: Development of high-speed 3D printing systems, additive design optimization, and industrialization of ceramic/nanocomposite manufacturing. His work bridges material science, structural engineering, and applied technologies. Recent publications highlight advancements in ceramic composites for biomedical and energy applications, graphene-based energy storage systems, and process innovations for zirconia and polymer composites. Key themes include material dispersion, thermal properties, and biomimetic design. Scientific Awards: Fellow of the Institute of Materials, Minerals and Mining (FIMMM); Top 2% Scientists worldwide Advising: Actively recruits postdoctoral fellows, PhD/Master's students, and research assistants. His group has secured over 10 national/provincial research grants. Labs: Affiliated with SUSTech’s Shenzhen Key Laboratory of Additive Manufacturing of High-Performance Materials, which focuses on overcoming industrial bottlenecks in metal/polymer/ceramic AM.

• Space Plasma Physics
• Theoretical Plasma Physics
• Computational Plasma Physics
• +5 more

Professor LIU Kaijun is a distinguished space plasma physicist currently serving as Professor and Deputy Head of Department at Southern University of Science and Technology (SUSTech) in Shenzhen, China. He previously held academic positions at Auburn University in Alabama, USA, where he was promoted from Assistant Professor (2012) to tenured Associate Professor (2017). His career includes significant research experience at Los Alamos National Laboratory and the Finnish Meteorological Institute following completion of his doctoral studies. 2007: Ph.D. in Space Plasma Physics, Cornell University 2002: M.S. in Space Physics, Peking University 1999: B.S. in Space Physics, Peking University Professor Liu specializes in theoretical and computational space plasma physics, with particular expertise in plasma instabilities and wave-particle interactions in Earth's radiation belts. His work also encompasses pickup ion dynamics in the heliosphere and solar wind-planet interactions. His research employs advanced computational techniques including particle-in-cell simulations and linear stability analysis to understand fundamental plasma processes. Analysis of Professor Liu's publication record from 2015-2018 reveals a consistent focus on electromagnetic wave phenomena in space plasmas, particularly examining Bernstein instabilities, Alfvén-cyclotron waves, and magnetosonic waves. His work demonstrates strong interdisciplinary connections between theoretical plasma physics, computational modeling, and spacecraft observations, with significant contributions to understanding radiation belt dynamics and heliospheric plasma processes. National-level Leading Talent (2019) Professor Liu has established a robust research program with extensive collaborations across international institutions including Los Alamos National Laboratory, NASA missions, and various universities. His work has been supported by research grants enabling advanced computational studies of space plasma phenomena. He advises graduate students in space physics and leads research projects investigating fundamental plasma processes relevant to space weather prediction and heliospheric physics. Professor Liu directs a computational plasma physics research group at SUSTech's Department of Earth and Space Sciences, utilizing high-performance computing resources to simulate complex plasma phenomena in Earth's magnetosphere and the heliosphere. His team collaborates with observational space physics groups to validate theoretical models against spacecraft measurements from missions including Van Allen Probes and THEMIS.

• Wearable Technology
• Human-Computer Interaction
• Smart Textiles
• +7 more

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.

• Computational Design and Fabrication
• Design for Additive Manufacturing
• Adaptive Process Planning
• +6 more

Dr. Xiong Yi is an Assistant Professor at the School of System Design and Intelligent Manufacturing (SDIM) at Southern University of Science and Technology (SUSTech) in Shenzhen, China. He leads the Computational Design and Fabrication (CoDeFab) research group, focusing on the integration of computational design methods with advanced manufacturing technologies, particularly in the field of additive manufacturing. Dr. Xiong has established himself as a leading researcher in computational design for additive manufacturing, with a strong international research background spanning Europe and Asia. Dr. Xiong's educational journey includes: Doctor of Science (DSc) in Engineering Design and Production from Aalto University, Finland (2012-2016) Master of Science (MSc) in Machine Automation from Tampere University of Technology, Finland (2010-2012) Bachelor of Engineering (BEng) in Mechanical Engineering from Hubei University of Technology, China (2006-2010) Dr. Xiong's research primarily focuses on computational design and fabrication methodologies, with particular emphasis on design for additive manufacturing (DfAM), intelligent manufacturing systems, and smart materials. His work bridges the gap between theoretical design principles and practical manufacturing constraints, developing novel approaches for the production of complex engineered products. He has pioneered research in continuous fiber-reinforced composite additive manufacturing, developing innovative process planning and optimization techniques that enable the production of high-performance structural components. His research in electrothermally controlled origami and 4D printing of smart materials represents cutting-edge work at the intersection of materials science, mechanical engineering, and computational design. Dr. Xiong's recent publications reveal a strong focus on continuous fiber-reinforced composites, with significant contributions to 4D printing, metamaterials, and intelligent process planning. His work integrates computational design with manufacturing constraints, creating novel approaches for topology optimization, toolpath planning, and structural design that consider both performance requirements and manufacturability limitations. The research demonstrates increasing sophistication in materials science applications, particularly in programmable materials and multi-functional structures. Dr. Xiong has received multiple prestigious awards for his research contributions, including: Best Presentation Award at the 24th Chinese Conference on Mechanisms and Machine Science (IFToMM CCMMS2024) Best Presentation Award at the International Conference on Frontiers of Additive Manufacturing Research (RAAM 2024) Best Paper Award at the International Conference on Design for 3D Printing (ICD3DP 2023) PhD Scholarship from Aalto University (2016) Research Travel Grant from the International Association for Vehicle System Dynamics (IAVSD) (2013) National Scholarship from the Ministry of Education (2008) As a dedicated educator and mentor, Dr. Xiong serves as a PhD supervisor at SUSTech and has successfully guided students who have gone on to pursue advanced studies and careers at prestigious institutions including Hong Kong Polytechnic University, Beihang University, DJI Innovations, and Singapore's A*STAR research institute. His research is supported by multiple competitive grants, including key projects from the National Key R&D Program of China, the National Natural Science Foundation of China, and provincial and municipal funding agencies. Dr. Xiong also serves on the editorial board of the Journal of Engineering Design and as a guest editor for Composites Communications, contributing to the advancement of his field through scholarly service. Dr. Xiong leads the CoDeFab research group, which maintains a strong collaborative culture focused on 'design leading manufacturing, manufacturing driving design, and digital-intelligent integration.' The group has developed several advanced manufacturing platforms, including multi-axis continuous fiber-reinforced composite additive manufacturing systems, smart composite additive manufacturing platforms, and multifunctional soft matter open manufacturing platforms. With a focus on practical applications and innovation, the CoDeFab group actively collaborates with industry partners and has established a joint laboratory to bridge academic research with industrial implementation.

Cao HaishanView profile

Associate Professor

• Cryogenic Cooling
• Micro Cryocoolers
• Joule-Thomson Cooling
• +12 more

Cao Haishan is an Associate Professor at Tsinghua University, affiliated with the Department of Energy and Power Engineering in the School of Mechanical Engineering. His research focuses on cryogenic cooling systems, high heat flux thermal management, and the physics of amorphous ice formation and phase transitions. He leads a research group supported by the National Natural Science Foundation of China and industry partners including Huawei, Midea, and Lenovo. Ph.D., Mechanical Engineering, University of Twente, 2013 M.Sc., Chemical Engineering, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 2009 B.Sc., Chemical Engineering, Zhejiang University, 2006 Dr. Cao's research spans three major areas: cryogenic cooling (including micro cryocoolers and sorption systems), high heat flux electronic cooling (especially with non-condensable gases), and the formation and transformation of amorphous water ice. His work combines theoretical modeling, computational simulation, and experimental validation, often at micro and nano scales. He applies principles from thermodynamics, fluid dynamics, and materials science to solve engineering challenges in refrigeration and thermal control. The recent publications reflect a strong trend toward interdisciplinary research, integrating machine learning for heat transfer prediction, computational screening of MOFs for cryogenic switches, and fundamental studies of ice nucleation on various substrates. The articles span journals in physics, engineering, materials, and applied thermal sciences, indicating broad impact across multiple domains. Notable scientific awards include: Gustav and Ingrid Klipping Award (2016) Cryogenics Best Paper Award (2017) Annual Teaching Excellence Award, Tsinghua University (2023) Excellent Supervisor Award, Tsinghua University (2024) Multiple First Prize Advisor awards in national student contests on energy saving Dr. Cao has been principal investigator on several grants, including projects funded by the National Natural Science Foundation of China on amorphous ice lifetime and micro-cryocooling for semiconductor chips. He has also led industry-university collaborations with Huawei, Midea, and Lenovo. He advises graduate students and leads a research team focused on next-generation cooling technologies. He serves on editorial boards for Journal of Refrigeration , Vacuum and Cryogenics , and Energies , and has chaired sessions at major international conferences such as ICEC-ICMC and ACTS. His research group operates within the Institute of Thermophysics at Tsinghua University, leveraging facilities in the Lee Shau Kee Science and Technology Building. The team collaborates with national laboratories and international institutions, particularly maintaining ties with the University of Twente. Current efforts are directed toward ultra-low vibration cooling, efficient separation of non-condensable gases, and extending the stability of amorphous ice for cryobiological applications.

Wang ChunView profile

Associate Professor

• Operations Management
• Stochastic Control
• Decision-Making under Uncertainty
• +9 more

Wang Chun is a tenured Associate Professor in the Department of Management Science and Engineering at the School of Economics and Management, Tsinghua University. He currently serves as Deputy Director of the department and has held academic positions at Tsinghua since 2017. His work bridges stochastic control, reinforcement learning, and machine learning applications in operations management and financial technology. Education: Bachelor's Degree from Tsinghua University (2005) Master's Degree from the University of Wisconsin-Madison (2008) Doctorate in Operations Research from Columbia University (2014) Research Interests: His research focuses on stochastic control and decision-making under uncertainty, particularly in inventory management, revenue management, financial engineering, and sports analysis. He also investigates reinforcement learning algorithms for dynamic optimization and applies machine learning to business data analytics and financial technology. Published Work Trends: Wang’s publications span operations research, financial mathematics, and computational management science. Recent studies address seasonal optimization patterns, robust inventory models, and game-theoretic approaches to sports analytics. His work integrates theoretical advancements in dynamic programming with practical applications in financial engineering and market microstructure. Career History: 2023–Present: Associate Professor, Tsinghua University 2020–2023: Associate Professor, Tsinghua University 2017–2020: Assistant Professor, Tsinghua University Researcher at KCG (New York), leading studies on quantitative investment and asset optimization

• Power Management IC Design
• Analog Integrated Circuits Design
• Integrated Power Electronics
• +4 more

Junmin Jiang serves as Associate Professor in the Department of Electronic and Electrical Engineering at Southern University of Science and Technology's College of Engineering since 2022, following promotion from Assistant Professor. He directs a research group focused on cutting-edge analog/power IC design with strong industry partnerships including Texas Instruments, Qualcomm, and Analog Devices. His educational background includes: Ph.D. in Electronic and Computer Engineering (2017), The Hong Kong University of Science and Technology Visiting Scholar (2015-2016), State Key Laboratory of AMSV, University of Macau B.Eng. in Electronic Information Engineering (2011), Zhejiang University Dr. Jiang's research centers on power management IC design with three interconnected thrusts: Power ICs for Specific Applications (e.g., audio/LiDAR drivers), Power ICs for AI systems, and AI-enhanced power IC design. His work achieves breakthroughs in switched-capacitor converters, delivering ultra-high efficiency (>97%), fast transient response ( His 15 most recent publications demonstrate consistent leadership in top venues (ISSCC/JSSC), showing accelerating impact in hybrid converter topologies, parasitic loss reduction, and AI-integrated power management. The trend reveals increasing industrial relevance with 8 U.S. patents and real-world implementations in audio/LiDAR systems. Scientific recognition includes: IEEE SSCS Pre-Doctoral Achievement Award (2017) National Overseas High-level Talent (Youth Project, 2022) SUSTech Outstanding Teaching Award (2024) Shenzhen Industrial Innovation Talent Award (2023) As an advisor, he mentors 8+ students including ISSCC awardees and competition winners. His group actively recruits undergraduates for chip design projects, with students winning top honors in National Electronic Design and Mathematical Modeling competitions. Current teaching includes graduate Nonlinear Circuits and undergraduate Microcomputer Principles. The Jiang Research Group maintains strong industry ties for student placements and collaborates with international institutions in the U.S., EU, and Macau. Lab capabilities focus on full-cycle IC design from simulation to tapeout, with recent 100V-output converters achieving 86.2% efficiency for acoustic applications.

Fang KongView profile

Assistant Professor

• Online Learning
• Reinforcement Learning
• Machine Learning
• +4 more

Fang Kong is an Assistant Professor in the Department of Statistics and Data Science at the Southern University of Science and Technology (SUSTech). He earned his PhD in Computer Science from Shanghai Jiao Tong University under the supervision of Prof. Shuai Li and received his Bachelor's degree in Software Engineering from Shandong University. Education: PhD in Computer Science, Shanghai Jiao Tong University (2020-2024) Bachelor's Degree in Software Engineering, Shandong University (2016-2020) Dr. Kong is broadly interested in developing theoretically guaranteed algorithms for sequential decision-making problems, with particular focus on multi-armed bandits and reinforcement learning, as well as their applications in online experimentation and recommendation systems. His research spans theoretical foundations of bandit algorithms, matching markets, influence maximization, and online learning under various feedback structures. He has made significant contributions to the understanding of best-of-both-worlds algorithms that perform well in both stochastic and adversarial environments. His publication record shows a strong trajectory of high-impact work in top-tier conferences including NeurIPS, ICML, ICLR, AAAI, WWW, and AAMAS. His research demonstrates expertise in theoretical machine learning with a focus on bandit algorithms, particularly in matching markets and sequential decision-making problems. His work often bridges theoretical guarantees with practical applications in recommendation systems and online experimentation. Scientific Awards: CCF Doctoral Dissertation Award in Agent and Multi-Agent Systems (2025) Baidu Scholarship (2024) National Scholarship for PhD students (2023, 2022) AAMAS Student Scholarship (2023) Microsoft Research Asia Excellence Award (2022) Dr. Kong actively mentors students at various levels, including PhD and Master's students at SUSTech, visiting students from other institutions, and undergraduate researchers. He serves as a reviewer for top machine learning conferences (ICLR, NeurIPS, ICML, WWW) and journals (IEEE PAMI, TMLR). His teaching includes graduate Machine Learning and undergraduate Artificial Intelligence courses at SUSTech.

• Film and Television Animation
• Creative Photography
• Art History
• +2 more

Xue Hang is a Lecturer in the Animation Department at Tongji University's School of Art and Media, where he has been teaching since 2002. He holds a Master of Science degree in Optics from Fudan University (1993) and has expanded his expertise through international exchanges at Hungary's Academy of Art and Design (1998-1999) and Germany's Bauhaus University (2010). His multidisciplinary career spans physics, visual design, and new media arts. Research interests include: Film and television animation Creative photography Art history Visual aesthetics in digital media Key research projects involve: Teaching reform for high-definition film/TV development Multimedia documentation of historical narratives (e.g., 'Jinggangshan' music-dance epic) Cultural value preservation through modern creative industries Scientific awards highlight: 2021 Special Prize in Chinese Poetry Competition Multiple teaching excellence awards (2008-2014) 1996 Li Guohao Young Faculty Award 2009 Shanghai Teaching Achievement Award (Team member) His 15 most recent publications demonstrate expertise in multimedia production, cultural adaptation, and digital art education, with projects spanning both theoretical and practical domains of new media arts. Notable collaborations include international academic exchanges with Germany and Hungary.

• Electronic Design Automation (EDA)
• Analog/RF Circuit Simulation
• Multi-physics Analysis
• +2 more

Dr. QUAN Chen is an Associate Professor at the School of Microelectronics, Southern University of Science and Technology (SUSTech), holding this position since May 2025 after serving as Assistant Professor (2019-2025) and Research Assistant Professor at the University of Hong Kong (2012-2018). A Shenzhen high-level overseas talent, he earned his PhD from the University of Hong Kong and conducts cutting-edge research in electronic design automation. His academic credentials include: Ph.D. from The University of Hong Kong (2010) Master's degree from The University of Hong Kong (2007) Bachelor's degree from Sun Yat-Sen University (2005) Dr. Chen's research pioneers advanced EDA algorithms for large-scale analog/RF circuit simulation, post-Moore multi-physics analysis, and AI-assisted design technologies. His work addresses critical challenges in nanodevice modeling and quantum computing circuits, resulting in over 50 publications in top venues like IEEE TCAD and DAC, plus four Chinese patents. Analysis of his recent publications reveals dominant trends in exponential integrator methods for transient simulation, model order reduction techniques, and physics-informed machine learning for reliability analysis. His work bridges numerical mathematics with practical EDA applications across analog circuits, quantum hardware, and emerging memory technologies. Key recognitions include: Wu Wenjun Artificial Intelligence Science and Technology Award, Second Prize (2020) ICCAD Best Paper Award Nomination (2012) Dr. Chen actively recruits Postdoctoral Fellows, Research Assistants, and Graduate Students while leading major funded projects including NSFC key/general programs and Guangdong Provincial R&D initiatives. His industry partnerships with Huawei, Empyrean, and Guowei Group translate theoretical advances into real-world EDA solutions. He directs a specialized research group at SUSTech focused on computational methods for next-generation circuit design, fostering innovation in simulation algorithms and multi-physics analysis through academic-industry collaboration.

• Mineral Surface-Interface Interactions
• Gas Hydrates
• Unconventional Oil and Gas Resources
• +3 more

Yun Li is a Research Assistant Professor and Master's Supervisor at Southern University of Science and Technology (SUSTech), affiliated with the Department of Earth and Space Sciences within the Faculty of Science. He serves as a youth council member of the mineral materials division of the Chinese Ceramic Society and holds multiple research grants including the National Natural Science Foundation of China Youth Fund Project. Research Assistant Professor at SUSTech (2022-present) Postdoctoral Research Associate at SUSTech (2020-2022) Youth Director of International Association of Clay Minerals (2025-2029) Principal Investigator for multiple research projects Dr. Li earned his B.S. in Petroleum Engineering from Yan'an University (2010-2014), M.S. in Oil and Gas Field Development Engineering from Southwest Petroleum University (2014-2017), and Ph.D. in Mineralogy, Petrology, Mineral Deposit Geology from Guangzhou Institute of Geochemistry, Chinese Academy of Sciences (2017-2020). Dr. Li's research focuses on mineral surface-interface interactions and gas hydrates, with particular emphasis on unconventional oil and gas resources including gas hydrates, shale oil and gas, and geological hydrogen/helium. His work investigates the geological storage and mineralization of carbon dioxide, employing surface-interface analysis techniques, molecular simulation methods, and in-situ visualization experimental techniques (X-ray and neutron) to study energy/environmental fluid interactions with clay minerals. His research has significant applications in unconventional oil and gas development and carbon capture technologies. Analysis of Dr. Li's recent publications reveals a strong focus on molecular dynamics simulations of hydrate formation mechanisms in clay minerals, particularly examining how different cations, organic matter, and mineral structures affect methane and carbon dioxide hydrate formation. His work bridges fundamental surface science with practical energy applications, showing increasing emphasis on carbon dioxide storage mechanisms in recent years. His publications appear in high-impact journals including ACS Sustainable Chemistry & Engineering, Applied Surface Science, Applied Clay Science, and Langmuir. Young Director of International Association of Clay Minerals (AIPEA) (2025-2029) Young Director of Mineral Materials Branch of Chinese Ceramic Society (2023-2028) SUSTech 'Qiming' and 'Taiyi' Star Scientific Research Achievement Awards (2024) Top Ten Young Scholars' Report at 10th National Conference on Mineral Science and Engineering (2024) Excellent Presentation Awards at multiple international clay and mineral conferences Outstanding reviewer for Applied Clay Science journal As a Master's Supervisor, Dr. Li mentors graduate students in earth sciences and energy-related research. He has secured significant research funding including the China Postdoctoral Science Foundation, Guangdong Basic and Applied Basic Research Foundation, and Shenzhen Science and Technology Program. His current projects include the National Natural Science Foundation of China Youth Fund Project (2025-2027) focusing on unconventional energy resources. Dr. Li has participated in major infrastructure projects including the material genomics experimental facility in Shenzhen and the high-pressure neutron diffraction/imaging spectrometer at Chinese Spallation Neutron Source. Dr. Li's research integrates computational modeling with experimental techniques through collaborations with major research facilities. His work on in-situ visualization techniques connects with neutron source facilities, while his molecular simulation research requires high-performance computing resources. He serves on editorial boards for journals including Unconventional Resources and special issues on unconventional oil and gas, demonstrating leadership in his research community.

• Marine Hydrodynamics
• Nonlinear Wave Theory
• Wave-Structure Interactions
• +4 more

Dr. Feng Xingya is an Assistant Professor at the Department of Marine Science and Engineering , Southern University of Science and Technology (SUSTech), Shenzhen, China. He obtained his Ph.D. in Ocean Engineering from the National University of Singapore (NUS) in 2016 and held postdoctoral positions at NUS and the University of Oxford before joining SUSTech in 2019. His research focuses on marine hydrodynamics , nonlinear wave-structure interactions , and computational fluid dynamics , with applications in offshore renewable energy and oil & gas platforms. Ph.D., Ocean Engineering (2016), National University of Singapore B.Eng., Hydraulic Engineering (2011), Hohai University His work includes developing nonlinear potential flow models , numerical wave tank codes , and boundary element methods for analyzing wave interactions with floating systems. Recent projects involve marine renewable energy and machine learning tools for intelligent marine environment monitoring. Scientific contributions include the 2014 Outstanding Young Researcher Award at the KKHTCNN conference. He supervises Ph.D. students and leads a research group focused on marine hydrodynamics , offering opportunities for postdocs and doctoral candidates.