جست‌وجوی استاد و پژوهشگر

• 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.

• Applied Signal Processing
• Inverse Problems
• Greedy Algorithms
• +۵ مورد دیگر

Florian Bossmann is an Associate Professor at the College of Mathematics, Harbin Institute of Technology (HIT), specializing in Applied Signal Processing with a focus on algorithms and applications. His research encompasses inverse problems, greedy algorithms, sparsity, and compressed sensing, with applications in seismic exploration, ptychography, and video processing. He holds a PhD in Mathematics from the University of Göttingen (2013) and a Diplom in Mathematics from the University of Duisburg-Essen (2009). Current projects include NSFC-funded seismic data interpolation and a start-up grant for applied signal processing research. He teaches courses like 'Signal and Image Processing' and 'Calculus for Civil Engineering'. Supervising Master/PhD students in signal processing, he emphasizes collaboration and innovation. His lab, the ASP Group, explores cutting-edge methods in multidimensional data reconstruction and algorithm design. Prominent publications focus on impedance inversion, neural network applications in geoscience, and object reconstruction techniques. He has led collaborative research initiatives with institutions like the Fraunhofer Institute and the Helmholtz Center for Environmental Health.

• Financial Mathematics
• Computational Finance
• Derivatives Pricing
• +۳ مورد دیگر

ZENG Pingping is an Associate Professor in the Department of Mathematics at Southern University of Science and Technology (SUSTech), where she has been faculty since June 2016, initially as Assistant Professor before promotion to Associate Professor in June 2023. Her academic career includes postdoctoral research at Hong Kong University of Science and Technology (2015-2016) and University of Vienna (2014-2015), plus a visiting scholar position at University of Waterloo (2014). Education: Ph.D. in Financial Mathematics, Hong Kong University of Science and Technology (2010-2014) B.S. in Applied Mathematics, University of Electronic Science and Technology (2006-2010) ZENG Pingping's research focuses on advanced financial mathematics with particular expertise in derivatives pricing, computational finance, and risk management. Her work bridges theoretical mathematical finance with practical applications in financial markets, developing sophisticated algorithms for pricing complex financial instruments. She specializes in stochastic volatility models, Lévy processes, and numerical methods including Hilbert transforms and Monte Carlo simulations. Her research has significant implications for understanding market behavior, managing financial risk, and developing new quantitative financial products. Analysis of her publication record reveals a consistent trajectory of high-impact research in quantitative finance, with recent work (2022-2024) increasingly focusing on Asian options, drawdown analysis, and regime-switching models. Her publications appear in top-tier journals including Mathematical Finance, Quantitative Finance, and SIAM Journal on Financial Mathematics, demonstrating her standing in the field. Notably, several papers have achieved recognition on the SSRN Top Ten List, highlighting their influence in academic finance circles. Scientific Awards: 9th Epsilon Fund Award from HKUST Department of Mathematics (2014) SUSTech Third Teaching Competition Second Prize (2019) SUSTech Outstanding Communist Party Member (2019) ZENG Pingping actively mentors students and researchers, currently leading a research group at SUSTech focused on financial mathematics and computational finance. She has secured significant research funding including a National Natural Science Foundation of China General Program (2022-2025) worth 500,000 RMB for developing new Monte Carlo methods and applications in derivatives pricing and risk management, plus an earlier Youth Science Foundation Project (2018-2020) focused on Hilbert transform methods for derivatives pricing. Her research group welcomes postdoctoral researchers, doctoral students, and research assistants interested in cutting-edge quantitative finance research.

Zhiyuan Liuمشاهده پروفایل

دانشیار

• Large Language Models
• Natural Language Processing
• Knowledge Graphs
• +۴ مورد دیگر

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

• Digital Media and Interactive Design
• 3D Animation
• Immersive Imaging

Liu Yun serves as a Tutor and Deputy Director of the Office at the Media Experiment and Practice Teaching Center within Tongji University's School of Art and Media. She holds dual Master's degrees in Design from Tongji University and Media Arts and Media Design from Bauhaus-Universität Weimar, Germany, alongside a Bachelor's in Animation from Tongji University. Education: Master of Arts, Design, Tongji University (2014–2017) Master of Arts, Media Arts and Media Design, Bauhaus-Universität Weimar, Germany (2015–2017, Dual Degree) Bachelor of Arts, Animation, Tongji University (2010–2014) Her research centers on digital media and interactive design, with specialized expertise in 3D animation, immersive imaging, and cross-cultural applications. She pioneers projects integrating traditional Chinese handicrafts into university curricula and develops augmented reality narratives for historical education, such as Holocaust storytelling. Her work bridges technical innovation in virtual environments with artistic expression and cultural preservation, emphasizing societal impact through educational technology. Liu Yun's publications reveal a consistent focus on extended reality (XR) for cultural heritage and pedagogy, evolving from foundational service design in community charity systems (2017) to immersive dome alternatives (2019) and Holocaust education (2020), culminating in practical frameworks for cultural education using traditional crafts (2021). This trajectory highlights her commitment to applying immersive technologies to real-world educational and societal challenges. Scientific Awards: Fifth National Digital Creative Teaching Skills Competition, second prize (2022) Tongji University Teaching Achievement Award, third prize (2021) Shanghai Higher Education First-Class Undergraduate Course (2021) National First-Class Undergraduate Course (2020) Guoqing Cup National College Art and Design Works Exhibition Award (2018) Tongji University Teacher Ethics and Style Outstanding Teacher (2022) Tongji University Young Female Teacher Talent Development Fund (2022) Tongji University Jiayuan-Kaisheng Reward Fund (2021) Liu Yun has secured significant research funding, including the Shanghai Art Science Planning Project on immersive storytelling with red cultural resources (2021, ¥150,000) and multiple university-level curriculum reforms. She has trained over 500 public cultural professionals through Shanghai's municipal training programs (2019–2021) and developed virtual simulation courses recognized as national and municipal first-class courses. While not listed as a primary thesis advisor, she contributes to experimental teaching projects and mentors students through courses like Media Experiment and Practice Workshop. As Deputy Director, she manages the Media Experiment and Practice Teaching Center's operations, which houses the Omnimedia Research Institute and supports cutting-edge facilities for XR development, 3D animation, and interactive media production. The center serves as a hub for cross-disciplinary collaboration between faculty, students, and industry partners in Shanghai's cultural sector.

• Design
• Human-Computer Interaction
• Intelligent Transportation Systems
• +۲ مورد دیگر

You Fang is a Professor at Tongji University's School of Art and Media, serving as PhD Supervisor in Design and Automotive Engineering. As Director of the Automotive Interaction Design Lab/User Experience Lab, they lead cutting-edge research in intelligent cognitive interaction, smart cockpit design, and embodied cognition applications. Their work bridges academia and industry through collaborations with Huawei, Baidu, and SAIC, while maintaining international partnerships with institutions in Germany, Australia, and Finland. PhD in Computer Software and Theory (Sun Yat-sen University, 2003) Master's in Computer Animation (Bradford University, 2005) Engineering Master's in Fashion Design (Northwest Institute of Textile Technology, 2000) Research focuses on three core areas: 1. Cognitive Interaction Design for autonomous vehicles, 2. Hybrid Spatial Information systems integrating physical and virtual environments, and 3. Art Therapy Applications using traditional movement cognition. Their work spans from theoretical studies in cognitive science to practical implementations in commercial automotive systems. Recent publications reveal a strong emphasis on AR-HUD interface optimization (7/15 papers), human-vehicle collaboration (4/15), and multimodal interaction (5/15). Key themes include driver trust assessment, spatial perception modeling, and non-verbal communication mechanisms in intelligent transportation. Scientific Recognition : 2022 Chinese Cultural and Tourism Government Award 2021 Tongji Yucai Award (2nd Prize) Multiple Ministry of Education Technology Progress Awards 27 invention patents (2017-2022) As educational innovator, they developed the award-winning Interaction Design: Design Thinking and Practice textbook adopted by 10+ Chinese universities, and pioneered digital education sandboxes for interactive design pedagogy.

• Intelligent Sensing
• Machine Learning
• Unmanned Autonomous Systems
• +۳ مورد دیگر

Dr. Qi Hao is an Associate Professor and Deputy Director of the Department of Computer Science and Engineering at Southern University of Science and Technology (SUSTech) in Shenzhen, China. He also serves as Executive Director of the SUSTech & Haylion Intelligent Transportation Center and Head of the SUSTech & FengXiangBiao ICV Education Joint Laboratory. Prior to joining SUSTech in 2014, he was an Assistant Professor at the University of Alabama (2007-2014) following postdoctoral training at the University of Kentucky. Dr. Hao received his PhD in Electrical and Computer Engineering from Duke University in 2006, with Master's and Bachelor's degrees from Shanghai Jiaotong University (1997 and 1994). His academic journey includes research positions at Singapore's Data Storage Institute (1998-2001) and engineering experience at Shanghai Electric Tool Research Institute (1997-1998). As an expert in intelligent sensing and unmanned autonomous systems, Dr. Hao's research spans bionic intelligent sensor design, machine learning applications, and autonomous vehicle technologies. His work demonstrates a strong integration of theoretical frameworks with practical implementations, particularly in pyroelectric infrared sensing, UAV systems, and distributed sensor networks. His research has evolved to address increasingly complex challenges in autonomous navigation, multi-robot coordination, and edge computing for intelligent transportation systems. Dr. Hao's publication trend reveals a strategic shift toward integrated autonomous systems, with recent work emphasizing robotics, machine learning, and wireless communication. His research bridges computer vision, sensor fusion, and deep learning to solve practical challenges in autonomous vehicle perception, wireless energy transfer, and human activity recognition. The interdisciplinary nature of his work connects electrical engineering principles with cutting-edge AI techniques. US National Science Foundation Research Awards (2009, 2011) Multiple IEEE conference best paper awards and finalists (2012-2021) Shenzhen Overseas High-level Talents Peacock Plan Category C (2017) Advanced Educators in Shenzhen (2017) Outstanding Teacher of Guangdong Province (2021) SUSTech Outstanding Research and Service Awards (2017-2021) Dr. Hao has secured significant research funding as Principal Investigator for projects from NSFC, Shenzhen Nanshan District, and industry partners including Huawei, Intel, and Haylion Technology. His current projects focus on intelligent binary sensing, next-generation camera systems, autonomous driving safety frameworks, and federated learning for vehicle perception. He has also contributed to educational initiatives through Guangdong Province and Shenzhen City education reform projects. Leading the SUSTech & Haylion Intelligent Transportation Center and the SUSTech & FengXiangBiao ICV Education Joint Laboratory, Dr. Hao oversees research teams developing solutions for intelligent transportation challenges. His labs integrate expertise across computer science, electrical engineering, and mechanical engineering to advance autonomous vehicle technologies, sensor networks, and robotics applications for real-world implementation.

• High Performance Computing
• Distributed Systems
• Cloud Computing
• +۲ مورد دیگر

Zhuozhao Li is an Assistant Professor in the Department of Computer Science and Engineering at Southern University of Science and Technology (SUSTech) in Shenzhen, China. He joined SUSTech in August 2021 after serving as a Postdoctoral Scholar at the University of Chicago from July 2018 to July 2021. His research focuses on high-performance computing, distributed systems, and cloud/edge computing, with applications across scientific domains. Ph.D. in Computer Science, University of Virginia, May 2018 M.S. in Computer Science, University of Southern California, May 2012 B.E. in Computer Science, Zhejiang University, July 2010 Dr. Li's research spans several critical areas in modern computing infrastructure. His primary focus is on High Performance Computing , where he develops novel approaches to optimize computational efficiency in scientific applications. In Distributed Systems , his work addresses challenges in large-scale system coordination and resource management. His contributions to Cloud/Edge Computing focus on improving virtualization techniques and resource allocation strategies. Additionally, he explores applications in the Internet of Things , examining how distributed computing paradigms can enhance IoT infrastructure. Dr. Li's publication record demonstrates a consistent focus on advancing distributed computing systems and their scientific applications. His recent work shows a clear progression from foundational research on data-parallel frameworks and job scheduling toward more applied systems for scientific computing. His contributions to projects like funcX and DLHub represent significant advancements in making distributed computing more accessible for scientific workflows. A notable trend is the increasing interdisciplinary nature of his work, with applications spanning from computational biology (SARS-CoV-2 research) to privacy-preserving spatial crowdsourcing. ACM HPDC Best Paper Nominees, 2019 IEEEMASS Service Award, 2019 Outstanding Graduate Research Assistant, University of Virginia, 2018 Dr. Li actively mentors students and researchers, currently recruiting PhD students, Master's students, postdocs, and research assistants for his research group at SUSTech. His research has been supported through various collaborative projects, including significant contributions to the U.S. Department of Energy National Virtual Biotechnology Laboratory Project about COVID-19, which was awarded the Secretary of Energy Achievement Award. His work on funcX, DLHub, and Parsl represents major software infrastructure development efforts with broad scientific impact. Dr. Li is affiliated with multiple research initiatives, including the Globus Lab (during his postdoc at University of Chicago) and various collaborative projects involving high-performance computing resources. At SUSTech, he leads a research group focused on distributed systems and high-performance computing. His work often involves collaboration with researchers across institutions, particularly in projects related to scientific computing infrastructure like funcX and DLHub.

• Control Theory
• Game Theory
• Signal Processing
• +۴ مورد دیگر

Kemi Ding is an Associate Professor at the School of Automation and Intelligent Manufacturing, Southern University of Science and Technology (SUSTech), leading the LEMONS lab (Learning and Mathematical Optimization in Networked Systems). Her career spans postdoctoral research at Arizona State University and Nanyang Technological University, followed by roles at SUSTech since 2021. Education Ph.D., Electronic and Computer Engineering, HKUST (2018) B.E., Electronic and Information Engineering, HUST (2014) Visiting Student, Harvard SEAS (2016-2017) Her research bridges control theory, game theory, signal processing, and machine learning , focusing on cyber-physical system security/privacy , networked estimation , and graph-based learning methods . She has published in top journals like Automatica and IEEE Transactions series, emphasizing secure and robust networked systems. Key publication trends include: Game-theoretic approaches to sensor security and deception strategies Optimization of estimation under bandwidth and attack constraints Graph signal processing for networked system modeling Privacy conflict resolution in social networks Resilient control theory under adversarial conditions

Wang Ziganمشاهده پروفایل

دانشیار

• Finance
• Economics
• Applied Microeconomics
• +۱۳ مورد دیگر

Wang Zigan is a Tenured Associate Professor in the Department of Finance at Tsinghua University's School of Economics and Management, with additional appointments at the Shenzhen Institute of Economics and Management and the Institute of Innovation Management at Tsinghua University Shenzhen International Graduate School. His research spans international finance, corporate finance, and environmental economics, with a focus on empirical analysis of financial markets and corporate behavior. Education PhD in Economics, Columbia University (2009-2015) Master of Philosophy in Economics, Columbia University (2009-2012) Master of Arts in Economics, Columbia University (2009-2011) Bachelor of Economics, Tsinghua University (2005-2009) Research Focus Professor Wang's research examines critical intersections between financial markets and real economic activity. His primary expertise lies in foreign exchange dynamics, corporate investment behavior under regulatory constraints, and banking network structures. He employs advanced computational methodologies including machine learning and network analysis to address complex questions in international finance and corporate governance, with particular attention to how institutional contexts shape market outcomes. Publication Trends His recent scholarly output demonstrates a sophisticated integration of traditional finance theory with cutting-edge data science techniques. Wang's work increasingly examines how digital transformation impacts financial markets, with growing emphasis on financial technology security and high-dimensional econometric methods. His publications in premier journals including Journal of International Economics and Journal of Financial Economics reveal consistent methodological innovation while addressing fundamental questions about market efficiency and corporate decision-making. Professional Experience Assistant Professor, School of Business, The University of Hong Kong (2015-2023) Visiting Professor, State University of New York (2014) Teaching Responsibilities At Tsinghua University, Professor Wang teaches graduate-level courses including Seminars on Advanced Topics in Finance, Research on Frontier Issues in Finance, and Cryptography and Network Security. His curriculum emphasizes both theoretical foundations and practical applications of computational methods in modern finance, preparing students for careers at the intersection of finance and technology.

Andrew Chi-Chih Yaoمشاهده پروفایل

استاد

• Algorithms
• Cryptography
• Quantum Computing
• +۳ مورد دیگر

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

Chen Guoqingمشاهده پروفایل

استاد

• Business Intelligence
• Big Data Analysis
• E-commerce
• +۴ مورد دیگر

Chen Guoqing is a Professor and Senior Professor of Humanities at Tsinghua University's School of Economics and Management, where he serves as Deputy Director of the Academic Committee. He chairs the National Natural Science Foundation of China's Big Data Major Research Program Guidance Expert Group and directs the Ministry of Education's Higher Education Management Science and Engineering Professional Teaching Guidance Committee, with additional roles on national informatization and New Liberal Arts committees. Education: Bachelor's Degree, Renmin University of China (1982) Master's Degree, University of Leuven, Belgium (1988) Doctorate, University of Leuven, Belgium (1992) Research Focus: Professor Chen pioneers research in Business Intelligence and Big Data Analysis, developing frameworks like PAGE for data-driven decision-making. His work spans E-commerce, IT Strategy, and Fuzzy Logic, with recent emphasis on personalized recommendation systems, online consumer behavior, and AI-human collaboration in business contexts. His publications reveal a trajectory from foundational fuzzy logic research to cutting-edge big data applications, consistently bridging technical innovation with managerial relevance. Awards: AIS Fellow (first from mainland China) IFSA Fellow Fudan Management Outstanding Contribution Award Changjiang Scholar Distinguished Professor National Science Fund for Distinguished Young Scholars National Outstanding Doctoral Dissertation Advisor Leadership: As former Executive Vice Dean of Tsinghua SEM and Vice President of IFSA, he has shaped academic policy globally. He leads major NSFC projects and international collaborations while advising government bodies on informatization strategy. His teaching includes national-level courses like "Management Information Systems" and "Management in the Big Data Era."

• Ultrafast manipulation of electronic properties
• Ultrafast manipulation of magnetic properties
• Ultrafast manipulation of phononic properties
• +۴ مورد دیگر

GU Mingqiang is a Research Associate Professor in the Department of Physics at Southern University of Science and Technology (SUSTech) in Shenzhen, China. He received his PhD in Physics from Nanjing University in 2014 under the supervision of Professor Wu Xiaoshan and conducted postdoctoral research at Northwestern University with James Rondinelli as co-advisor. His educational background includes a BS in Mechanical Engineering from South China University of Technology (2004-2008) and a PhD in Physics from Nanjing University (2008-2014), with additional research experience as a Visiting Scholar at Indiana State University (2011-2013). Professor GU's research focuses on exotic electronic states in strongly correlated and topological materials using first-principles calculations. His major research interests include: Ultrafast manipulation of electronic, magnetic, and phononic properties using lasers Band topology and topological structure of material energy bands Design and regulation of strongly correlated oxide materials and topological materials His publication record demonstrates consistent contributions to top journals in condensed matter physics, with research spanning ultrafast control of materials, topological states, and correlated electron systems. His work shows a progression from fundamental superlattice studies to more recent applications of ultrafast techniques for controlling material properties on picosecond timescales. His notable scientific recognition includes: 2020 Shenzhen Overseas High-level (Peacock Plan) Category B Talent Introduction Professor GU has developed innovative computational methods including a density functional theory-based time-dependent density matrix Liouville equation scheme (TDLDFT) for studying charge transfer after photoexcitation and methods for calculating one-dimensional edge states in three-dimensional materials using Wannier orbitals. His research combines theoretical development with experimental collaboration, as evidenced by his publications in journals like Nature Materials and Science.

• Quantum Transport
• Quantum Materials
• Interface Physics
• +۵ مورد دیگر

HE Hongtao is an Associate Professor in the Department of Physics at Southern University of Science and Technology (SUSTech), where he has been employed since August 2011. His research focuses on quantum transport phenomena and quantum materials physics, with particular emphasis on topological insulators, spintronics, and interface physics. Ph.D., Department of Physics, Hong Kong University of Science and Technology, 2006 B.S., Department of Physics, China University of Science and Technology, 2001 Professor He's research spans multiple cutting-edge areas in condensed matter physics. His primary focus is on quantum transport in topological materials, where he investigates the influence of spin-orbit coupling on electronic and spin transport properties under extreme conditions of low temperature and high magnetic fields. He also conducts significant work on interface physics, particularly studying epitaxial transition metal oxide films and heterojunctions. His research has important implications for developing next-generation spintronic and quantum computing devices. Analysis of Professor He's publication record reveals a strong focus on topological materials, particularly topological insulators like Bi2Te3 and Bi2Se3, where he has made significant contributions to understanding magnetotransport phenomena. His work spans fundamental quantum transport phenomena including weak antilocalization, linear magnetoresistance, and topological Hall effects. More recently, his research has expanded to Dirac semimetals, topological Kondo insulators, and 2D material heterostructures, demonstrating a consistent trajectory toward increasingly complex quantum materials systems. Selected candidate of Peacock-plan Award, Shenzhen Highly Cited Paper by Web of Science (Phys. Rev. Lett. 106, 166805) Highly Cited Paper by Web of Science (Nature Communications 7, 10301) Professor He has secured significant research funding, including as Project Leader for a National Natural Science Foundation Youth Project (2013-2015), a General Project (2016-2019), a Guangdong Natural Science Foundation project (2015-2018), and a Shenzhen Knowledge Innovation Program project (2014-2016). He actively recruits research fellows and postdoctoral positions, indicating an active research group. His 49 SCI-indexed papers have accumulated over 1,300 citations with an h-index of 16, demonstrating substantial impact in his field. While specific laboratory details aren't provided in the text, Professor He's research on epitaxial film growth and quantum transport measurements suggests he operates specialized low-temperature and high-magnetic field experimental facilities. His collaborations with researchers across multiple institutions, including Hong Kong University of Science and Technology, Chinese University of Hong Kong, and various mainland Chinese universities, indicate an extensive research network in condensed matter physics.

• Superconducting Qubits
• Circuit QED Systems
• Quantum Computing
• +۴ مورد دیگر

Jian Li is an Associate Researcher at the Institute of Quantum Engineering, Southern University of Science and Technology (SUSTech). He received his education from Central South University (B.Sc.), Chalmers University of Technology (M.Sc.), and Aalto University (D.Sc.). Prior to joining SUSTech in April 2019, he conducted research at Aalto University's Low Temperature Laboratory and the University of Glasgow's School of Engineering. His educational background includes: 2006.08-2012.09: D.Sc. in Engineering Physics, Aalto University, Finland 2004.09-2006.06: M.Sc. in Nanoscale Science and Technology, Chalmers University of Technology, Sweden 2000.09-2004.07: B.Sc. in Applied Physics, Central South University, China Jian Li's research focuses on cutting-edge quantum technologies, particularly in the areas of superconducting qubits, circuit QED systems, quantum computing, and quantum simulation. His work explores the fundamental properties and potential applications of superconducting quantum devices, with a special emphasis on developing practical quantum computing systems. He has made significant contributions to understanding quantum phenomena in superconducting circuits and their interactions with mechanical oscillators. His scientific work demonstrates a strong trend toward advancing quantum information processing using superconducting circuits. His publications span multiple high-impact journals including Nature, Nature Communications, and Physical Review Letters, reflecting his contributions to both theoretical and experimental aspects of quantum engineering. His research bridges fundamental quantum physics with practical quantum computing applications. His notable scientific contributions include: First international experimental verification of quantum simulation of motional averaging phenomenon Realization of microwave-band optomechanical hybrid systems with superconducting transmon circuit QED Observation of Autler-Townes Effect in superconducting multi-level artificial atoms Jian Li has published 19 academic journal papers in prestigious venues including Nature, Nature Communications, Physical Review Letters, and Advanced Materials. His research is supported by Shenzhen's strategic focus on quantum science as one of ten key development areas, with the Shenzhen Institute of Quantum Science and Engineering being one of the first three "Ten Basic Research Institutions" established in January 2018. He is based at Room 508, Building 1, Huiyuan, Southern University of Science and Technology, No. 1088 Xueyuan Avenue, Nanshan District, Shenzhen.