Find Academic Supervisors

• Intelligent Sensing
• Machine Learning
• Unmanned Autonomous Systems
• +3 more

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.

• Marine Biogeochemistry
• Polar Environments
• Trace Metal Cycling
• +5 more

Mark James Hopwood is an Associate Professor in the Department of Ocean Science and Engineering at Southern University of Science and Technology (SUSTech) in Shenzhen, China. He joined SUSTech in April 2021 and was appointed Associate Professor in December 2021. Prior to this, he worked at GEOMAR Helmholtz Centre for Ocean Research Kiel in Germany from 2014 to 2021, where he served as a postdoctoral researcher and later as Principal Investigator for a DFG project on ice-ocean interactions around Greenland. Hopwood received his PhD in Ocean and Earth Science in 2015 from the University of Southampton, UK, where he worked with Peter Statham, a pioneer of trace metal clean techniques. He also holds an MChem (combined BSc and MSc) in Chemistry with Patent Law, with first-class honors, from the University of Manchester, UK. His educational background also includes training at the University of North Carolina Wilmington, USA. Hopwood's research focuses on marine biogeochemistry in polar environments, particularly on trace metal cycling, glacier-ocean interactions, and the impacts of climate change on marine ecosystems. His work examines how glacial meltwater affects nutrient distribution, trace metal fluxes, and biological productivity in polar regions. He has published over 50 papers in leading oceanography journals including Nature Communications, Nature Geoscience, and Geophysical Research Letters. He is also an associate editor for Journal of Geophysical Research: Oceans. His recent publications reveal a strong focus on the biogeochemical impacts of glacial meltwater and icebergs on polar oceans, with particular attention to trace metal dynamics (iron, lead, manganese), nutrient cycling, and ecosystem responses. His work spans multiple polar regions including Greenland, Antarctica, and Svalbard, and extends to tropical upwelling systems like the Peruvian and Benguela currents. Best early-career presentation, Advances in Marine Biogeochemistry, Oxford, January 2016 University of Manchester Bursary for academic excellence 2007-2011 Lord Brotherton Award for Chemistry 2008 Hopwood actively participates in research cruises, having joined over 9 expeditions and spent more than 10 months on polar campaigns in Svalbard, Greenland, and Antarctica. He currently leads projects including POLAR BEAST cruise investigating Arctic/Atlantic connectivity, EUROFLEETS Ice Disko cruise studying iceberg biogeochemistry, and NSFC RFIS research on cobalt dynamics in the cryosphere. His research group conducts large-scale (100,000 Litre) experiments in Dapeng investigating ocean alkalinity enhancement for carbon dioxide removal. Hopwood teaches undergraduate course OCE108 - Introduction to Carbon Neutrality (Spring semester) and postgraduate course OCE5030 - Marine Biogeochemical Cycles (Fall semester). Outside academia, he volunteers as a teaching assistant introducing children to marine science and paddleboarding at a sports camp and supports archery on campus.

• Health policy evaluation
• Health workforce
• Primary care
• +7 more

Xinxin Han is an Assistant Professor at the School of Public Health and Emergency Management, Southern University of Science and Technology (SUSTech) in Shenzhen, China. She holds a Doctor of Philosophy in Public Policy and Administration (Health Policy Track) from George Washington University and a Master of Science in Health Services Research, Policy and Administration from the University of Minnesota. Prior to her current position, she served as a Postdoctoral Fellow at Tsinghua University's School of Medicine and was a Senior Research Associate at the Fitzhugh Mullan Professor of Health Workforce Equity, Health Workforce Research Center at George Washington University. Her educational background includes: 2015-2019: Doctor of Philosophy in Public Policy and Administration (Health Policy Track), George Washington University 2013-2014: Master of Science in Health Services Research, Policy and Administration, University of Minnesota (Twin Cities) 2008-2012: Bachelor of Art, Guangxi Medical University Dr. Han's research primarily focuses on health policy evaluation, health workforce, primary care, access to care, and community-based digital chronic care management. Her work examines evaluating the impact of health insurance policy (i.e., Medicaid expansion), health workforce policy (i.e., the National Health Service Corps), and health technology (i.e., telehealth) on enhancing the distribution of health care resources and the capacity of community health centers. She also investigates the hierarchical medical system under the Healthy China context and emergency epidemic response management and prevention policy. Her research employs multi-source data to conduct studies in health policy and management, aiming to empower evidence-based health decision-making and improve health system efficiency, quality, and accessibility. Analysis of her 15 most recent publications reveals a strong focus on health workforce policy, community health centers, and health policy evaluation across both the United States and China contexts. Her work spans diverse subfields including health workforce distribution, primary care access, Medicaid policy effects, and telehealth implementation. A significant portion of her research examines the National Health Service Corps and its impact on community health centers, while more recent work has expanded to Chinese healthcare contexts including rural medical practice, psychiatric hospital working conditions, and radiology training. Dr. Han has received numerous scientific awards and recognitions: 2025: AcademyHealth Annual Research Meeting Best Abstract, Best of ARM 2019: Tsinghua University Shui Mu Tsinghua Scholar 2018: AcademyHealth Health Workforce Interest Group Outstanding Abstract 2017: George Washington University Kee Doctoral Research Award 2016/2019: The Journal of Rural Health Exceptional Reviewer 2019: China Postdoctoral Science Foundation International Postdoctoral Exchange Fellowship She serves as a peer reviewer for several major journals including Medical Care, Journal of Rural Health, and BMC Health Services Research. Dr. Han has secured significant research funding from multiple sources including the National Natural Science Foundation of China, Guangdong Provincial Research Funds, China Postdoctoral Science Foundation, and previously from the United States Department of Health and Human Services. Her current research projects focus on digital-driven community chronic disease management, health policy evaluation using econometrics and simulation, and chronic disease risk prediction using machine learning. She leads a research team committed to using multi-source data to conduct health policy and management research aimed at evidence-based health decision-making.

• Remote Sensing Hydrology
• Satellite Altimetry
• Hydrological Modeling
• +5 more

JIANG Liguang is an Assistant Professor in the School of Environmental Science and Engineering at Southern University of Science and Technology (SUSTech). He received his MSc from the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences in 2014, and his PhD in Remote Sensing & Hydrology from the Technical University of Denmark in 2018. Prior to joining SUSTech in March 2021, he completed a postdoctoral fellowship at the Technical University of Denmark. Dr. Jiang's research spans both remote sensing and hydrological sciences, with a focus on satellite altimetry applications for inland water monitoring and modeling. His work investigates the hydrological dynamics of surface water bodies such as lakes, reservoirs, and rivers in the context of climate change. He has made significant contributions to hydrodynamic modeling using distributed altimetry-derived Water Surface Elevation data, broadening the applications of satellite altimetry in hydrology. His recent publications reveal a strong focus on advancing satellite altimetry techniques for river and lake monitoring, with particular emphasis on Sentinel-3, CryoSat-2, and SWOT missions. His research integrates machine learning approaches with traditional hydrological modeling, demonstrating innovative methods for streamflow prediction and water resource assessment. The interdisciplinary nature of his work connects remote sensing technology with practical water management applications. Scientific Awards: 2023 Reviewer Award of The Innovation Geoscience 2023 Reviewer Award of IAHS Hydrological Sciences Journal 2021 Shenzhen Overseas High-Caliber Personnel 2019 Otto Mønsteds Fund Travel award 2018 Outstanding Reviewer of the Remote Sensing of Environment Dr. Jiang serves as an Associate Editor for Sustainable Water Resources Management (Springer Nature) and as a Young Editorial Board Member for the Journal of Remote Sensing. His funded research projects include significant work with international organizations such as the European Space Agency, NASA/CNES, and Danish research agencies, demonstrating strong international collaboration in his field.

• Room-temperature thermoelectric materials
• Ionic thermoelectric materials
• Magnetic thermoelectric materials
• +3 more

Liu Weishu is a full Professor in the Department of Materials Science and Engineering at Southern University of Science and Technology (SUSTech), holding the National Science Fund for Distinguished Young Scholars and Royal Society of Chemistry Fellowship. His research centers on thermoelectric materials and devices, with significant contributions to room-temperature electronic/ionic thermoelectrics and micro-power generation systems. His research interests span room-temperature thermoelectric materials , ionic thermoelectric materials (notably Gelatin-KCl-FeCN 3-/4- with 17 mV/K thermoelectric potential), magnetic thermoelectric materials , micro-distributed power sources , and electronic skin applications. Key achievements include establishing generalized material parameters for multi-band thermoelectric systems and developing flexible ionic thermoelectric devices for wearable power generation. Notable scientific awards include: Tencent Science Exploration Award (2019) Chinese Society of Materials Academic Contribution Award (2024) Beijing Science and Technology Progress Award (2012) Royal Society of Chemistry Fellowship (2023) National Distinguished Young Scholars Fund recipient As principal investigator, he leads the National Natural Science Foundation project and co-leads the Ministry of Science and Technology Key R&D Plan, securing multiple enterprise-funded projects. His lab actively recruits postdocs for magnesium-based thermoelectric research and supervises undergraduate/graduate students on thermoelectric applications. Current teaching includes MSE460 (Materials Science Introduction), MSE5024 (Advanced Thermodynamics), and MSE311 (Materials Thermodynamics). The research group operates advanced thermoelectric characterization facilities and recently hosted the 2nd Ion Thermoelectric Conference at SUSTech, focusing on self-powered IoT sensors and wearable energy harvesting technologies.

• Remote Sensing of Water Environment
• Environmental Science
• Climate Change Impact on Coastal and Inland Waters
• +1 more

Professor Feng Lian is a Vice Dean at the School of Environmental Science and Engineering, Southern University of Science and Technology (SUSTech), with over 20 national and provincial projects and nearly 100 SCI publications in top journals like Nature and Remote Sensing of Environment . Selected as a National Ten Thousand Talents Program Young Top-Notch Talent and Guangdong Province Pearl River Young Scholar, his work focuses on water environment remote sensing, climate-human impacts on aquatic systems, and satellite sensor design. Education: PhD in Cartography and Geographic Information Systems from Wuhan University (2013), Joint Doctoral Program at University of South Florida (2010-2012), BSc in Geographic Information Systems from Yangtze University (2008) Research Interests include: Remote Sensing Algorithms for Water Environments Climate Change and Human Activity Impact on Lakes Satellite Sensor Radiometric Calibration His recent publications span algal bloom monitoring, atmospheric correction methods, and global lake dynamics using Landsat and MODIS data. Key scientific awards include the 2023 Li Xiaowen Remote Sensing Science Award and 2022 Young Scientist Award of the Chinese Geographical Society. As Vice Dean and editorial board member for journals like National Remote Sensing Bulletin , he leads projects on land-sea interaction and cyanobacteria bloom monitoring. His work has been featured by CCTV , Reuters , and ScienceDaily .

• High Performance Computing
• Distributed Systems
• Cloud Computing
• +2 more

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.

• Random Matrix Theory
• High dimensional Statistics
• Time Series Analysis
• +1 more

Li Zeng is an Associate Professor in the Department of Statistics and Data Science at Southern University of Science and Technology (SUSTech) since January 2021, following her Assistant Professor role at the same institution from August 2019 to December 2020. Previously, she was an Eberly Postdoctoral Fellow at Pennsylvania State University under Prof. Runze Li (2017-2019) and a Research Assistant at the University of Washington with Dr. Fang Han (2017). Ph.D. in Statistics and Actuarial Science from the University of Hong Kong (2017), advised by Prof. Jianfeng Yao M.Sc. in Statistics from Renmin University of China (2012) B.Sc. in Mathematical Science from Beijing Normal University (2009) Her research centers on Random Matrix Theory and High Dimensional Statistics , with significant contributions to eigenvalue/singular value distributions in large-dimensional matrices. She extends these theoretical foundations to Time Series Analysis for lagged auto-correlation structures and applies them to Machine Learning problems including neural network optimization and regularization. Her work bridges asymptotic probability theory with practical data science applications, developing robust methods for high-dimensional inference. Analysis of her 15 most recent publications (2016-2025) reveals a dominant focus on high-dimensional statistical theory with increasing machine learning integration. Key trends include asymptotic analysis of covariance/correlation matrices (60% of publications), factor modeling innovations (20%), and deep learning applications (20%). She consistently publishes in top-tier venues including Annals of Statistics (5 papers), Journal of the American Statistical Association , and machine learning conferences (ICML, ECCV), demonstrating exceptional interdisciplinary impact. Excellent Teaching Assistant Award (5 times) from HKU Department of Statistics and Actuarial Science (2012-2017) Dr. Li actively recruits postdoctoral researchers specializing in probability theory and high-dimensional statistics, emphasizing candidates with strong mathematical backgrounds. As a referee for premier journals including Annals of Statistics , JASA , and Journal of the Royal Statistical Society: Series B , she contributes significantly to scholarly review. Her research is institutionally supported through SUSTech faculty positions, with potential external funding inferred from extensive publication output and conference participation. Within SUSTech's Department of Statistics and Data Science (established 2019), Dr. Li contributes to a rapidly expanding research ecosystem focused on high-dimensional data analysis. The department supports multiple research directions including biostatistics and financial statistics, with active graduate programs (M.Phil/Ph.D.) and developing initiatives in data science education. Her teaching portfolio includes undergraduate Statistical Calculation and Software and graduate-level High Dimensional Statistics courses.

• Rigid Graph Theory
• Multi-Agent Systems
• Unmanned Systems
• +4 more

Liangming Chen is an Associate Professor at the School of Automation and Intelligent Manufacturing, Southern University of Science and Technology (SUSTech), China. Previously, he held postdoctoral positions at Nanyang Technological University, Singapore. His academic roles include deputy editor-in-chief for IEEE Transactions on Robotics and IEEE Transactions on Systems, Man, and Cybernetics: Systems . As a Senior Member of the IEEE, he has been selected for the National High-Level Talent Program (Youth Project) and Shenzhen Overseas High-Level Talent Program (Peacock Plan Category C). Education : PhD in Systems and Control (University of Groningen, 2021), PhD in Control Science and Engineering (Harbin Institute of Technology, 2019), BEng in Automation (Southwest Jiaotong University, 2015). His research integrates Rigid Graph Theory , Multi-Agent Systems , and Robotics , with recent work focusing on Brain-Inspired Intelligence and Machine Learning . Key trends in his publications (2020-2025) include Formation Control , Distributed Localization , and Unmanned Systems , appearing in top journals like IEEE TAC , Automatica , and IEEE TRO . Scientific Awards include the Shenzhen Overseas High-Level Talent Program and competition prizes in Electronics Design and Mathematical Modeling . He has guided teams to national awards and mentored students to placements at top institutions. His group pursues High-Impact Research in Multi-Agent Estimation , Robot Swarms , and Autonomous Navigation , with applications in drones and embodied intelligence.

• Control Theory
• Game Theory
• Signal Processing
• +4 more

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

JI JieView profile

Professor

• Fire Plume Behavior
• Combustion of Liquids and Solids
• Fire Spread
• +3 more

Professor JI Jie serves as Professor and Vice Director of the State Key Laboratory of Fire Science at the University of Science and Technology of China (USTC), with additional leadership roles in the Engineering Research Center of Thermal Safety and National & Local Joint Engineering Research Center of Thermal Safety Technology. Education: Bachelor of Science, University of Science and Technology of China, 2002 Ph.D. in Engineering, University of Science and Technology of China, 2008 Postdoctoral Research, University of Science and Technology of China, 2008-2010 His research pioneers fire plume dynamics, combustion of complex materials, fire spread mechanisms in ancient/high-rise structures, and real-time fire forecasting using data assimilation techniques. Current work focuses on integrating experimental and numerical methods for fire risk assessment in tunnels, subways, and cultural heritage sites. Recent publications (2021-2023) demonstrate expertise across fire dynamics, smoke management, and safety engineering, with significant contributions to understanding wind-driven fires, multi-fire interactions, and real-time smoke prediction systems using Ensemble Kalman Filter approaches. Honors and Awards: Elected fellow of the Combustion Institute (2022) Highly Cited Chinese Researcher (Elsevier 2020, 2021) National Science and Technology Innovation Leadership Talent (2018) Excellent Young Scientists Fund recipient (2017) Multiple national teaching and research awards including China Fire Protection Association First Prize (2019) Professor Ji has secured major funding including the National Science Fund for Excellent Young Scholars and multiple National Natural Science Foundation projects, while supervising award-winning research teams. His lab implements fire safety standards in national construction projects and international protocols. He leads USTC's State Key Laboratory of Fire Science research team, focusing on experimental combustion studies, computational fire dynamics, and practical fire safety engineering applications for complex infrastructure.

Rentai LIUView profile

Professor

• Geotechnical Engineering
• Grouting Technology
• Underground Engineering
• +2 more

Rentai LIU is a Professor and doctoral supervisor at Shandong University's School of Civil Engineering, affiliated with the Geotechnical and Structural Engineering Center. He earned his Ph.D. in Geotechnical Engineering from Shandong University in 2012 and subsequently joined the faculty, with a postdoctoral stint at Shandong Energy Group (2012-2015). His research focuses on controlling geological hazards in underground engineering and developing innovative grouting technologies. Research Interests: Dr. LIU specializes in dynamic water grouting theory, quantitative grouting design for water-rich strata, and novel material development. His work addresses practical challenges like water inrush disasters, sand layer stabilization, and rock mass reinforcement. Key innovations include cement-based anti-dispersion grouts and expansion materials for high-pressure water surges, applied in major infrastructure projects across China. Research Trends: His publications (2011-2019) predominantly explore grouting material properties, underground water control, and geomechanical modeling. Recent work emphasizes computational simulations, subsea tunnel risks, and sustainable materials like pervious concrete. Awards & Honors: Second Prize, Shandong Provincial Science and Technology Progress Award (2019) Second Prize, China Coal Association Science and Technology Award (2018) Second Prize, Ministry of Education Technology Invention Award (2017) Second Class, China Highway and Transportation Society Award (2016) First Prize, Shandong Provincial Science and Technology Progress Award (2015) First Prize, Ministry of Education Science and Technology Progress Award (2014) Grants & Projects: Dr. LIU leads multidisciplinary projects including: National Natural Science Foundation grants on grouting reinforcement mechanisms (¥610K active) National Key R&D Program sub-projects on infrastructure resilience (¥300K) 14 industry collaborations with Qingdao Metro, China Railway Bureaus, and Shandong Energy Group (total value ~¥4.5M), addressing tunnel safety and material R&D. Laboratory & Advising: He directs research at the Geotechnical Engineering Center and mentors doctoral candidates in geotechnical engineering, emphasizing practical solutions for underground construction hazards.

Shengyou YangView profile

Professor

• Solid mechanics
• Continuum mechanics
• Soft and active materials
• +3 more

Shengyou Yang is a Professor in the Department of Engineering Mechanics at the School of Civil Engineering, Shandong University, China. His academic journey includes a Ph.D. in Mechanical Engineering from the University of Houston (2012-2015), an M.S. in Solid Mechanics from Beijing Jiaotong University (2009-2012), and a B.S. in Physics from Sichuan University (2005-2009). Prior to his current position, he served as a Research Assistant Professor and Postdoctoral Fellow at the University of Houston (2016-2019). His research focuses on solid mechanics , soft materials , and energy harvesting , with specialized interests in: Electromechanical instabilities and bifurcation phenomena Flexoelectricity and piezoelectric effects in soft matter Nonlinear elasticity of functionally graded materials Nanoscale mechanics and surface energy applications Analysis of his 15 most recent publications reveals consistent focus on instability phenomena in soft materials, energy harvesting mechanisms (flexoelectric/magneto-electric), and mechanical behavior of functionally graded structures under thermo-mechanical loads. The work demonstrates advanced mathematical modeling of continuum systems with practical applications in smart materials and sustainable energy. Notable scientific recognitions include: Outstanding Contribution in Reviewing awards from premier mechanics journals (2017-2018) Lewis Wheeler and Kalsi Scholarships at University of Houston (2014) National-level physics competition prizes in China (2004-2007) Teaching experience includes instructing Heat Transfer at Shandong University and Introduction to Mechanics at University of Houston, where he managed large cohorts (140+ students). Professional affiliations include membership in the Society of Engineering Science (SES) and peer review for leading mechanics journals.

Hao WangView profile

Researcher

• Data Management
• Machine Learning
• Recommender Systems
• +7 more

Hao Wang is an Assistant Researcher in the Department of Computer Science and Technology at Nanjing University, China. He is affiliated with the Reasoning & Learning Group and conducts research at the intersection of data management and machine learning. Bachelor of Mathematics, Nanjing University (2005) Master of Computer Science, Nanjing University (2008) Ph.D. in Computer Science, The University of Hong Kong (2014) His research interests span Data Management and Machine Learning , with recent focus on rank-aware query processing, recommender systems (especially location-based), reinforcement learning, and transfer learning. His work often integrates user behavior modeling, efficient indexing, and scalable algorithms for large-scale data. Hao Wang's publication record shows a consistent trend in solving practical problems in data-intensive AI systems. His recent articles focus on personalized location recommendation , crowdsourced data labeling , distributed learning for imbalanced data , and reinforcement learning transfer . These works appear in top venues such as VLDB, SIGMOD, ICDM, AAAI, and journals like TKDE and GeoInformatica, indicating strong technical depth and interdisciplinary impact. Hao Wang has not been explicitly mentioned as receiving scientific awards in the provided text. He has collaborated extensively with researchers such as Yang Gao, Nikos Mamoulis, and David Cheung. While no formal advisees are listed, his involvement in supervising PhD work (as co-supervisor) and publishing with students suggests an active mentoring role. His research has been supported through academic collaborations and institutional affiliations, though specific grant details are not provided. Hao Wang is a member of the Reasoning & Learning Group at Nanjing University, where he contributes to advancing intelligent systems that combine logical reasoning with statistical learning. The group focuses on foundational and applied aspects of AI, particularly in data mining, knowledge discovery, and autonomous decision-making.

• Risk Management
• Actuarial Science
• Optimal Reinsurance
• +9 more

Zhang Yiying is an Assistant Professor and Doctoral Supervisor in the Department of Mathematics at the Southern University of Science and Technology (SUSTech). Previously, they served as an Assistant Professor at Nankai University from January 2019 to August 2021. Their academic journey includes a PhD in Actuarial Science from the University of Hong Kong (2018), with academic visits to the University of Leuven (Belgium) and University of Amsterdam (Netherlands) during 2018-2019. Dr. Zhang's educational background includes: Bachelor of Science in Mathematics and Statistics from Lanzhou University (2012) Master of Science in Mathematics and Statistics from Lanzhou University (2015) PhD in Actuarial Science from the University of Hong Kong (2018) Dr. Zhang's research spans three main areas with significant contributions to theoretical frameworks and practical applications: Risk Management and Actuarial Science: Focusing on optimal reinsurance design, credibility theory for heterogeneous risks, systemic risk assessment using conditional distortion measures, and risk measurement under asymmetric information. Applied Probability: Investigating ordered variable models, random order theory, stochastic comparisons, and statistical dependence structures in risk modeling. Reliability Theory and Statistics: Developing methodologies for reliability analysis, system reliability design, and optimization of k-out-of-n systems with heterogeneous components and random weights. Dr. Zhang's publication record demonstrates a consistent research trajectory across actuarial science and reliability engineering domains. Their work frequently appears in top-tier journals including Insurance: Mathematics and Economics, Scandinavian Actuarial Journal, ASTIN Bulletin, and Naval Research Logistics. Recent publications show strong interdisciplinary connections between actuarial science, probability theory, and reliability engineering, with particular emphasis on risk modeling under asymmetric information and optimal system design. Dr. Zhang has received recognition for their scholarly contributions through publications in leading actuarial journals such as IME, SAJ, ASTIN Bulletin, and NAAJ, as well as operations research journals including EJOR, RESS, and NRL. As a Doctoral Supervisor, Dr. Zhang mentors PhD students in advanced research topics at the intersection of actuarial science, probability theory, and reliability engineering. Their research program addresses fundamental questions in risk modeling and system reliability, with potential applications in insurance, finance, and engineering systems.