Find Academic Supervisors

Jianke ZhuView profile

Professor

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

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

Xuehai QianView profile

Professor

• Computer Architecture
• Computer Systems
• Hardware Security
• +3 more

Xuehai Qian is a Tenured Full Professor in the Department of Computer Science at Tsinghua University since July 2024. Prior to this, he served as an Associate Professor at Purdue University (2022-2024), Assistant Professor at the University of Southern California (2015-2022), and Postdoctoral Researcher at the University of California Berkeley (2013-2015). Ph.D. in Computer Science, University of Illinois at Urbana-Champaign, USA (2013) ME in Computer Science and Technology, Institute of Computing Technology, Chinese Academy of Sciences, China (2007) BE in Computer Science and Technology, Beihang University, China (2004) His research focuses on parallel computer architecture , hardware/software co-designed domain-specific architectures for graph analytics and machine learning , hardware security , and quantum computer architecture . He has pioneered scalable cache coherence protocols for atomic block execution, hardware sequential consistency violation detection, and distributed frameworks for graph processing leveraging emerging memory technologies. Xuehai Qian’s publications span computer architecture , graph analytics , machine learning systems , and quantum computing , with a strong emphasis on distributed systems , accelerators , and memory optimization . His work includes novel architectures for graph processing, decentralized training protocols, and ReRAM-based accelerators for deep learning. NSF CAREER Award (2018) ACSIC (American Chinese Scholar In Computing) Rising Star Award (2019) IEEE Senior Member (2019) Hall of Fame inductions: ASPLOS (2018), HPCA (2019), ISCA (2021), MICRO (2021) W.J. Poppelbaum Memorial Award (2013) He has advised students who have received Microsoft Research Lovelace Fellowships , Ph.D. Fellowships , and Facebook Fellowships . His research has been supported by grants such as the NSF SPX project on FPGA-based machine learning platforms and smaller NSF grants. Notably, he has served as an Associate Editor for Science China (Information Sciences) since 2023 and as a Guest Editor for IEEE Transactions on Parallel and Distributed Systems (2019).

Lei BuView profile

Professor

• Model Checking
• Bounded Model Checking
• Formal Methods
• +7 more

Lei Bu is a Professor and Vice Dean at the Software Institute , Nanjing University . He leads research in formal verification, cyber-physical systems, and software engineering, with a focus on bounded model checking and hybrid system analysis. B.Sc. and Ph.D. in Computer Science from Nanjing University (2004, 2010) Visiting student at Carnegie Mellon University and University of Texas at Dallas His research integrates formal methods and machine learning for verifying complex systems like IoT and software with real-time constraints. Key projects include BACH Toolset and BRICK for reachability analysis. Recent publications demonstrate expertise in hybrid system verification , cache side-channel detection , and parallel code analysis frameworks . His work bridges theoretical advancements with practical applications in safety-critical systems. Zhongchuang Software Talent Award (2023) CCF-IEEE CS Young Computer Scientist Award (2022) High-Tech Software Innovation Awards (2019-2023) As Principal Investigator, he leads major projects funded by National Science Foundation of China and Jiangsu Natural Science Foundation (2020-2027). Current tools include BACH for hybrid systems and MLB for Java symbolic execution.

Shaowei WangView profile

Professor

• Heat and mass transfer in porous media
• Fluid mechanics
• Mathematical methods in mechanics

Shaowei Wang is a Professor in the Department of Engineering Mechanics at the School of Civil Engineering, Shandong University, China. He holds a Ph.D. in Mathematics (2007) from Shandong University and completed post-doctoral research in fluid mechanics (2009) at Peking University. His research focuses on heat and mass transfer in porous media , fluid mechanics , and mathematical methods in mechanics . His recent publications highlight advancements in electro-osmotic flows, oscillatory non-Newtonian fluid dynamics, and stability analysis of bioconvection in porous media. Key themes include modeling viscoelastic fluids (Oldroyd-B, Maxwell), fractional calculus applications, and microchannel transport phenomena. First Prize in Natural Science of the Ministry of Education (2015) Second Prize of Natural Science Award of Shandong Province (2015) Du Qinghua Young Scholar Award (2016) Wang serves as Director of Shandong Society of Mechanics and editorial board member of multiple journals. His work bridges theoretical fluid dynamics with practical applications in microfluidics and geophysical systems.

• Superconducting quantum computation
• Quantum simulation
• Quantum information processing
• +7 more

Yuanzhen Chen is an Associate Professor in the Department of Physics at Southern University of Science and Technology (SUSTech), where he has been working since 2015. His research focuses on experimental investigation of superconducting quantum computation and quantum simulation, aiming to advance quantum information processing using superconducting circuits. Chen's work contributes to the development of quantum technologies that leverage quantum superposition and entanglement for computational advantages over classical systems. His educational background includes: Ph.D. in Physics from University of Maryland (1998-2005) M.S. from Chinese Academy of Sciences, Institute of Semiconductors (1995-1998) B.S. from University of Electronic Science and Technology of China (1991-1995) Chen's research interests center on superconducting quantum systems. His team focuses on two main areas: developing superconducting quantum chips using Josephson-junction-based devices to build qubits and measurement apparatus, and implementing quantum computation and simulation on these chips. They explore geometric quantum computation, quantum automata, quantum few-body systems, and simulation of condensed matter physics models. Their work aims to address fundamental challenges in quantum computing, including error correction and scalability. Analysis of Chen's recent publications reveals a consistent focus on advancing superconducting quantum circuit technology. His research has progressed from fundamental quantum gate implementations toward more complex quantum systems including multi-qubit architectures and topological quantum phenomena. A notable trend is the increasing sophistication of quantum control techniques, with recent work exploring hybrid digital-analog approaches and noise-resilient quantum gates. Chen collaborates extensively with theoretical researchers, particularly with Man-Hong Yung, to bridge theory and experiment in quantum computing. His laboratory at SUSTech has developed capabilities in fabricating and measuring superconducting quantum devices, with research outputs published in high-impact journals including Physical Review Letters and npj Quantum Information. The research team operates within SUSTech's Department of Physics, part of the Faculty of Science. They maintain experimental facilities for superconducting quantum device fabrication and characterization, with current work focusing on advancing toward practical quantum computing applications and exploring fundamental quantum phenomena using controllable superconducting systems.

HUANG LiView profile

Associate Professor

• Quantum Materials
• Novel Energy Materials
• Phase Selectivity under Nonequilibrium Conditions
• +7 more

HUANG Li is an Associate Professor in the Department of Physics at Southern University of Science and Technology (SUSTech) , where she has been since September 2019. She joined SUSTech in February 2013 as an Assistant Professor, advancing to her current rank. Her research focuses on quantum materials , novel energy materials , nonequilibrium phase selectivity , and surface/interfacial phenomena using first-principles computational methods and theoretical models . Educational Background: Ph.D. in Physics, Fudan University (2006) M.Sc. in Physics, Xiangtan University (2002) B.A. in Physics, Xiangtan University (1999) Research Interests span quantum materials (e.g., Moire superconductors , topological insulators ), novel energy materials (e.g., thermoelectrics , supercapacitors ), and surface/interfacial dynamics. Her recent work emphasizes two-dimensional systems , spin-valley-layer coupling , and nonequilibrium phase transitions in van der Waals heterostructures and metal-organic frameworks . Publications highlight her expertise in ab initio molecular dynamics , density functional theory , and quantum transport . Key trends include Moiré engineering in twisted bilayers, strain-tunable magnetism , and ferroelectricity in layered materials. Scientific Awards and Grants include leadership roles in projects funded by the National Natural Science Foundation of China and Shenzhen Science & Technology Commission . Notable grants address quantum state control in Moiré superlattices , nonlinear Hall effects , and thermoelectric performance enhancement . Professional Experience: Postdoctoral Research Associate at Ames Laboratory (2008–2012) Joint Postdoc at Georgia Institute of Technology & Ames Laboratory (2006–2008) Visiting Scholar at Harvard University & Oak Ridge National Laboratory (2004–2006)

• Mathematical Physics
• Topological Field Theories
• 2D Conformal Field Theories
• +3 more

Liang Kong is a Researcher at the Southern University of Science and Technology (SUSTech) . He previously held academic positions at Tsinghua University (Associate Professor), Harvard University (Research Associate), University of New Hampshire (Lecturer), and several postdoctoral institutes including the Max Planck Institute, IHES, and California Institute of Technology. Education : PhD in Mathematics (2005, Rutgers University), Master (1997) and Bachelor (1994) in Physics (University of Houston and University of Science & Technology of China). Research Interests : His work bridges mathematical physics , topological field theories , and category theory , focusing on 2D conformal field theories , topological phases of matter , and enriched monoidal categories . He explores connections between quantum field theories and algebraic structures like tensor categories and braided fusion categories, with applications to quantum computing and condensed matter physics . Publications : His research spans topological quantum field theory , conformal field theory , and quantum lattice models , with notable contributions to Levin-Wen models , Cardy algebras , and anyon condensation . Collaborative works with Xiao-Gang Wen and Ingo Runkel underpin his impact in topological order classification and gapless edge states . Positions : Current role at the Shenzhen Institutes of Quantum Science and Engineering (2018–present) follows appointments at Harvard, Tsinghua, and the University of New Hampshire.

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.

• Digital Economy
• Social Welfare
• Consumer Behavior
• +6 more

Dr. Shaobo (Kevin) Li is a Tenured Associate Professor at the School of Business, Southern University of Science and Technology (SUSTech), with secondary appointment in the Department of Information Systems & Management Engineering. He holds a PhD in Business Administration from Nanyang Technological University (2019), Master of Business Administration (University of Virginia, 2014), Master of Finance (West Virginia University, 2012), and Bachelor of Business Administration (Lanzhou University, 2011). National High-Level Youth Talent Program awardee Overseas High-Caliber Personnel in Shenzhen City Recipient of 2018 China Scholarship Council’s Excellent Self-Funded Student Scholarship His research focuses on the intersection of digital economy, social welfare, and technology-driven marketing, employing experimental methods, empirical models, and neuroscience. He serves as Associate Editor for the Journal of Business Research and has published in top UTD-24 journals including Journal of Consumer Research, Information Systems Research, and Production and Operations Management. His work examines platform economics, brand management during crises, and consumer behavior related to AI, sustainability, and health decisions. He has led 10+ research projects (National Natural Science Foundation, Ministry of Science and Technology 2030 Program) and received multiple research awards, including Academy of Marketing Science Best Doctoral Dissertation Proposal Award (2019) and Best Paper Awards at China Marketing Science (2020,2024), China Marketing International Conference (2023), and CMAU Annual Conference (2023,2024). Teaching accolades include SUSTech’s Premier Teaching Award, Top 10 Most Popular Professor among undergraduates, and Nanyang Business School’s Best Graduate Teaching Award (2017). Teaches Financial Marketing (undergraduate) Teaches Frontiers of Management & Research Methods (PhD) Actively recruiting research assistants, postdocs, and joint PhD candidates with Hong Kong Polytechnic University

• Quantum Technologies
• Rare Earth Materials
• Solid-State Spectroscopy
• +4 more

Dr. Shuping Liu is a Research Assistant Professor at the Institute for Quantum Science and Engineering , Southern University of Science and Technology (SUSTech), China, since August 2019. Her research focuses on solid-state quantum memory, rare earth crystals, and their applications in quantum storage, communication, and computation. Ph.D. in Materials Sciences (2016), Shanghai Institute of Ceramics, Chinese Academy of Sciences Joint Ph.D. (2015), Institute of Physics, Czech Academy of Sciences Master's (2012), University of Science and Technology of China Bachelor's (2011), Wuhan University of Technology Dr. Liu's expertise spans design, synthesis, and high-resolution spectroscopy of rare earth ion-doped materials, with applications in optical quantum technologies and scintillation ceramics. Her work addresses defect engineering, size reduction of nanoparticles, and optimization of luminescence properties for quantum memory systems. Her publications emphasize quantum-grade nanomaterials (2020–2021), coherent spectroscopy (2019), and scintillator optimization (2014–2017). Key methodologies include defect control, codoping strategies, and nanoscale fabrication, aligning with quantum storage and radiation detection technologies. Dr. Liu has no explicitly listed scientific awards or advisees in the provided text. Her collaborative work spans institutions including CNRS (France), Academy of Sciences of Czech Republic, and Shanghai Institute of Ceramics.

• Gene Transcription
• Epigenetic Regulation
• RNA Regulation
• +1 more

Huanhuan CUI is a Research Associate Professor in the Department of Biology within the School of Life Sciences at Southern University of Science and Technology (SUSTech) in Shenzhen, China. She joined SUSTech in December 2018 and serves as a master's supervisor, contributing to both research and graduate education in molecular biology and genetics. Educational Background: PhD in Biology, Free University of Berlin (2011.09-2016.04) MS in Animal Genetics, Northwest A&F University (2008.09-2010.06) BE in Bioengineering, Northwest A&F University (2004.09-2008.06) Dr. CUI's research focuses on the mechanisms and method development of gene transcription and epigenetic regulation, with particular emphasis on RNA translation control. Her work spans multiple biological systems including cancer biology, developmental biology, and cardiovascular research, demonstrating a strong interdisciplinary approach that integrates molecular biology, genomics, and bioinformatics techniques. She has made significant contributions to understanding chromatin remodeling, transcriptional regulation, and RNA processing mechanisms. Dr. CUI's publication record shows a consistent trajectory of high-impact research, with publications in prestigious journals including Nature Communications, Nucleic Acids Research, and Cellular & Molecular Immunology. Her work demonstrates expertise in CRISPR-based technologies, epigenetic regulation, and multi-omics approaches to studying complex biological processes. Before joining SUSTech, Dr. CUI held positions as a Clinical Research Manager at BGI Genomics (2017.09-2018.11), a PostDoc at Charite Universitaetsmedizin Berlin (2016.05-2017.06), and a Research Assistant at Humboldt University of Berlin (2010.09-2011.08), building a diverse research background that bridges basic science and clinical applications.

• Materials Science
• Computational Method Development
• Catalytic Mechanism Study
• +3 more

Dr. Li Lei is an Associate Professor and doctoral supervisor in the Department of Materials Science and Engineering at the Southern University of Science and Technology (SUSTech). He holds a BS from the University of Science and Technology of China and a PhD in Chemistry (2016) from the University of Nebraska-Lincoln. From 2016-2020, he conducted postdoctoral research with Prof. Graeme Henkelman at the University of Texas at Austin, where he developed the machine-learning software package PyAMFF. Education : BS (Materials Science, USTC), PhD (Chemistry, UNL) Affiliation : Southern University of Science and Technology, Shenzhen Peacock Plan Category B Talent Research Focus : His work bridges computational method development and catalytic mechanism discovery through: Machine learning algorithms for force field training Long-timescale dynamics simulations of nanomaterials Saddle-point searching methods for reaction pathways Monte Carlo-based catalyst optimization Development of catalytic reaction databases His recent publications in JACS , Nat. Commun. , and ACS Catalysis demonstrate expertise in: Machine learning-enhanced molecular dynamics Electrochemical catalyst design (ORR/OER) in situ reaction mechanism analysis Atomic-scale electrostatic modeling Scientific Contributions : - Led development of PyAMFF machine learning potential framework - Published 27+ SCI papers in top-tier journals - Collaborated with leading computational chemists (Henkelman, Zeng, Francisco) Awards : Shenzhen Peacock Plan Category B Talent Contact : Office: 5th Floor, North Building, College of Engineering, SUSTech Phone: 0755-88015040 Email: lil33@sustech.edu.cn | lei.li@sustech.edu.cn

Song YuView profile

Associate Professor

• Rock Mechanics
• Fracture Mechanics
• Numerical Simulation
• +4 more

Dr. Song Yu is an Associate Professor at the Department of Engineering Mechanics , School of Civil Engineering , Shandong University , with expertise in rock mechanics, fracture mechanics, and numerical simulation techniques. Education: B.E. (1989), M.E. (1992) in Machine Building, Ph.D. (2004) in Mould & Die Engineering, Post-doctoral research (2005-07) in Die & Mold CAD at Shanghai Jiao Tong University, Visiting Scholar at UC San Diego (2008) Research focuses on rock and soil mechanics , fracture mechanics , nondestructive AE detection , and numerical simulation for rock-metal interaction. Pioneered 3D DDA method applications in rock mechanics and fluid-solid coupling models. Recent publications emphasize geotechnical stability analysis under seismic loads, coupled hydro-mechanical modeling , and hexahedral mesh algorithms in metal forming. His work bridges computational methods with practical geotechnical challenges. Notable grants: National Natural Science Foundation of China (51579140), State Key Laboratory of Geotechnical Mechanics projects Teaches advanced topics in Finite Element Method (FEM) , structural optimization, and ANSYS simulation techniques. Collaborated with institutions including Shanghai Jiao Tong University and UC San Diego.

• Optimization Theory
• Variational Analysis
• Bilevel Programming
• +6 more

Zhang Jin is a Professor at the Department of Mathematics in the College of Science at Southern University of Science and Technology (SUSTech) since December 2024. He also serves as the Associate Vice Director of the Shenzhen National Applied Mathematics Center since February 2023. Education: Ph.D. in Applied Mathematics (2014, University of Victoria); M.Sc. in Operational Research (2010, Dalian University of Technology); B.Art in Journalism (2007, Dalian University of Technology) Research Interests span optimization theory , variational analysis , bilevel programming , and their applications in machine learning , economics , and data science . His work includes convergence analysis of first-order methods , stochastic/robust optimization , and error bound conditions . Recent Publications focus on nonconvex bilevel optimization , gradient-based algorithms , and stochastic programming , with papers in IEEE TPAMI , SIAM Journal on Optimization , and conferences like ICML , NeurIPS , and ICLR . Scientific Awards include the Youth Science and Technology Innovation Award from Guangdong Province (2022) , Youth Science and Technology Award from the Operations Research Society of China (2020) , and Junior Research Award from SUSTech's Faculty of Science (2020) . Students: Supervises Ph.D. candidates like Yixia Song , Peixuan Yang , and Qichao Cao , along with Master's students Yixuan Zhang , Kaiqi Sun , and Feifan Wang . Grants: Leads projects such as the National Key R&D Program (3.2M RMB, 2024-2028) and National Science Fund for Distinguished Young Scholars (2M RMB, 2023-2025) .

• 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.