جست‌وجوی استاد و پژوهشگر

• Defects in semiconductors
• Carrier transport in semiconductors
• Semiconductor junctions
• +۵ مورد دیگر

Francis Chi Chung Ling serves as an Associate Professor in the Department of Physics within the Faculty of Science at The University of Hong Kong (HKU). His academic journey began at HKU where he earned his B.Sc., M.Phil., and Ph.D. degrees. He maintains professional affiliations as C.Phys., M.IEEE, and F.Inst.P., and conducts research at Room 417, Chong Yuet Ming Physics Building. Office: CYP 417 Contact: 3917 5248 / 2559 9152 Email: ccling@hku.hk ORCID: https://orcid.org/0000-0003-4757-1065 Professor Ling's research spans multiple critical areas in semiconductor physics and materials science. His primary focus centers on defect characterization and engineering in semiconductors, particularly examining how defects influence electrical, optical, and magnetic properties. His work with positron annihilation spectroscopy provides atomic-scale insights into vacancy defects, while his investigations into deep level transient spectroscopy and carrier transport mechanisms advance fundamental understanding of semiconductor behavior. His laboratory maintains international collaboration with the positron beam line at Helmoltz Zentrum Dresden Rossendorf in Germany. Analysis of his 207 publications reveals a strong concentration on zinc oxide (ZnO) systems, silicon carbide (SiC), and other wide bandgap semiconductors. His recent work shows increasing focus on energy applications including photovoltaics, neuromorphic computing elements, and battery materials. The publications demonstrate consistent methodology combining experimental characterization with theoretical analysis, particularly emphasizing defect engineering approaches to modify material properties. Faculty Excellent Service Award: Faculty of Science, HKU (2008) Best Poster Award: ICMAT 2007, Singapore Faculty Knowledge Exchange Award 2024 for SiC Power Devices collaboration Professor Ling has supervised over 35 research postgraduate students across MPhil and PhD programs, with recent graduates focusing on SiC devices, ZnO-based materials, and 2D semiconductor structures. His grant portfolio includes significant funding as Principal Investigator on 17 projects totaling over HK$8 million, with recent major awards including HK$1.26 million for 'Bipolar Degradation in SiC Devices Suppressed by Proton Implantation' (2023) and HK$804,000 for 'Optimising the Performance of SiC Devices Through the Control of Atomic Scale Deep Level Defect' (2021). He leads the Material Physics Laboratory within HKU's Experimental Condensed Matter and Material Science Group, specializing in defect characterization and engineering of functional materials. The laboratory maintains specialized equipment for deep level transient spectroscopy, temperature-dependent Hall measurements, and luminescence spectroscopy, with international access to positron beam facilities in Germany.

• Condensed Matter Physics
• Physics

Shunqing Shen serves as Professor and Chair of Condensed Matter Physics within the Department of Physics at the Faculty of Science, The University of Hong Kong. He completed his academic foundation with a B.Sc., M.Sc., and Ph.D. from Fudan University. His research specialization centers on Condensed Matter Physics, investigating the electronic, magnetic, and structural properties of solid and liquid matter. This field drives advancements in quantum materials, superconductivity, and nanoscale phenomena with applications spanning semiconductor technology to quantum computing. His work bridges theoretical frameworks with experimental methodologies to uncover emergent material behaviors under extreme conditions.

• Cold Atomic Gases
• Quantum Many-Body Systems
• Transport Properties in Quantum Gases
• +۴ مورد دیگر

Professor Shizhong Zhang is a faculty member at the Department of Physics , Faculty of Science , The University of Hong Kong . He joined HKU in August 2012 after earning a B.S. from Tsinghua University (2003) and a Ph.D. in physics from the University of Illinois at Urbana-Champaign (2009). His work bridges atomic physics and condensed matter theory , focusing on cold atomic gases and strongly correlated systems . Education B.S., Tsinghua University (2003) Ph.D., University of Illinois (2009) Professor Zhang's research explores the quantum behavior of interacting particles at ultra-low temperatures , with a focus on transport properties of cold atomic gases and their implications for understanding correlated materials . His studies often leverage precision control from atomic physics to investigate many-body and few-body phenomena . Recent publications highlight advancements in quantum gases with spin-orbit coupling , unitary Fermi systems , and nonlinear spin dynamics . Key themes include integrability effects on viscosity , effective range analysis , and dimensional crossovers in interacting geometries. He has supervised numerous PhD and MPhil students in condensed matter theory, quantum computing, and computational physics. His leadership extends to grants like the RGC Research Fellow Scheme (2022) and General Research Fund projects , alongside roles in the Physical Society of Hong Kong as Honorary Secretary and campus coordinator. Professor Zhang is also engaged in knowledge exchange , including public lectures and collaborative research with international institutions. His teaching portfolio includes advanced courses in classical mechanics , statistical mechanics , and solid-state physics .

• Biomedical Science
• AI for Drug Discovery
• Aptamer-based Precision Medicine

Professor YU Yuanyuan serves as an Assistant Professor within the Teaching and Research Division of the School of Chinese Medicine at Hong Kong Baptist University, integrating traditional Chinese medicine frameworks with contemporary biomedical research methodologies. Her scholarly focus spans three interconnected domains: Biomedical Science as the foundational discipline Artificial Intelligence applications for accelerating drug discovery pipelines Aptamer-based Precision Medicine for targeted therapeutic development This tripartite research approach pioneers computational techniques to modernize pharmaceutical development within Eastern medical contexts while maintaining scientific rigor. No scientific awards or professional honors were referenced in available materials. Similarly, institutional records contain no documented information regarding graduate student supervision, research grant acquisitions, or laboratory team affiliations.

• Computational Chemistry
• Protein Chemistry
• Drug Discovery
• +۲ مورد دیگر

Henry H. T. Chan serves as an Instructor in the Department of Chemistry at Hong Kong Baptist University's Faculty of Science, where he conducts research and teaching in chemical sciences. His contact email is hthenrychan@hkbu.edu.hk and he communicates fluently in Cantonese, Putonghua, and English. His research focuses on Computational Chemistry, Protein Chemistry, Drug Discovery, NMR Spectroscopy, and Chemical Education, integrating theoretical modeling with experimental approaches for molecular analysis and educational innovation. These interdisciplinary interests bridge pharmaceutical development, structural biochemistry, and pedagogical methodologies in chemistry education.

• Machine Learning
• Non-parametric Methods
• Computational Methods
• +۶ مورد دیگر

Yifan Chen is an Assistant Professor in the Department of Computer Science and affiliate faculty in the Department of Mathematics at Hong Kong Baptist University's Faculty of Science. He joined HKBU in Fall 2023 after completing his PhD in Statistics from the University of Illinois Urbana-Champaign in 2023 under the guidance of Prof. Yun Yang. His educational background includes: B.S. in Statistics from Fudan University (2018), advised by Prof. Juan Shen and Prof. Chenghong Zhang Ph.D. in Statistics from University of Illinois Urbana-Champaign (2023), advised by Prof. Yun Yang Dr. Chen's research focuses on developing efficient algorithms for machine learning, with particular emphasis on non-parametric models and neural networks featuring intensive matrix operations. His work bridges statistical theory with practical computational challenges in modern machine learning systems, especially those involving Transformers (language models) and Graph Neural Networks (GNNs). He approaches machine learning from both theoretical and applied perspectives, seeking to understand statistical structures while addressing real-world computational constraints. His publication record shows consistent output in top-tier venues including ICML, NeurIPS, KDD, and EMNLP, with recent work spanning graph coarsening, optimal transport, efficient language model fine-tuning, and causal inference. His research demonstrates strong mathematical foundations combined with practical applications in AI systems. Among his notable achievements: NSFC Young Scientists Fund (2025) GDSTC General Program funding (2024) RGC Early Career Scheme proposal grant (2024) ICML 2023 Grant Award ($1,500) Dr. Chen actively mentors students through his research group, supervising PhD students and visiting research assistants. He has successfully guided students who have gone on to PhD programs at institutions including Institute of Science Tokyo, HKU, Fudan, and NUS. His teaching includes COMP 7070 Advanced Topics in Artificial Intelligence and Machine Learning, which covers core machine learning concepts for AI application research, and COMP 2027 Applied Linear Algebra for Computing. His research group focuses on efficient machine learning algorithms, with current projects spanning graph neural networks, optimal transport, language model efficiency, and causal inference. He collaborates with researchers from institutions including UIUC, Fudan University, and industry labs like Amazon Alexa AI.

Jingcun Caoمشاهده پروفایل

استادیار

• Mobile App Ecosystem
• Online Education
• Health Care
• +۹ مورد دیگر

Jingcun Cao is an Assistant Professor at the University of Hong Kong, where he joined in 2020. He holds a Ph.D. in Marketing from Indiana University, an M.A. in Economics and Business from the same institution, and a B.S. in Computational Mathematics from Xiamen University. He also completed visiting programs at the University of Chicago Booth School of Business and National Tsing Hua University. His research addresses mobile app ecosystems, online education, healthcare, digital marketing, and environmental policy. Methodologically, he specializes in causal inference, applied machine learning, randomized field experiments, and econometrics. His collaborations with tech firms focus on business intelligence and big data analytics. Teaching responsibilities include courses such as Big Data Marketing (MKTG 3530), Introduction to Marketing (MKTG 2501), and executive education modules in MarTech, Business Analytics, and Brand Management. His publications analyze trends in digital platform governance, deep learning applications for consumer behavior, socioeconomic impacts of policy interventions, and mobile app monetization strategies. Research consistently integrates multidisciplinary approaches to solve industry-relevant problems. He is currently recruiting Research Assistants and holds pending patents for machine-learning algorithms related to marketing analytics.

• Humanities
• Artificial Intelligence

Professor Ahti-Veikko Pietarinen serves as a full-time faculty member at Hong Kong Baptist University within the Faculty of Arts and Social Sciences, specifically in the Department of Religion and Philosophy. His research integrates Humanities with Artificial Intelligence , reflecting a unique interdisciplinary focus where philosophical inquiry intersects with computational methodologies. This dual expertise suggests contributions to areas such as logic-based AI systems and the ethical implications of machine intelligence within cultural contexts. No scientific awards, student advisement records, or publication details were documented in the provided source material.

• Control Theory
• Estimation and filtering theory
• Complex dynamical distributed networks
• +۳ مورد دیگر

Daniel W. C. HO is a Chair Professor of Applied Mathematics and Associate Dean (Undergraduate Education) at the College of Science, City University of Hong Kong. He has been with City University of Hong Kong since 1989, having previously served as a Research Fellow at the University of Strathclyde, Glasgow, UK from 1985 to 1988. Prof. Ho received first class honours in BSc, MSc, and PhD degrees in mathematics from the University of Salford, Greater Manchester, UK in 1980, 1982, and 1986, respectively. His academic journey began with foundational work in control theory and has evolved into a distinguished career spanning over three decades. Prof. Ho's research interests span multiple domains in control theory and systems engineering. His primary focus areas include Control Theory , Estimation and filtering theory , Complex dynamical distributed networks , Multi-agent networks , Nonlinear singular systems , and Stochastic systems . His work bridges theoretical advances with practical applications, particularly in networked control systems, cybersecurity for cyber-physical systems, and distributed optimization. Prof. Ho has made significant contributions to the understanding of synchronization phenomena in complex networks, resilient control under cyber attacks, and quantized control systems with communication constraints. His research has evolved from classical control theory to address contemporary challenges in networked and distributed systems, reflecting the changing landscape of control engineering. Prof. Ho's publication record shows a strong emphasis on secure control systems under cyber attacks, distributed optimization with communication constraints, event-triggered control schemes, quantized control systems, and synchronization of complex networks. His work demonstrates a consistent progression from theoretical foundations to addressing practical implementation challenges in cyber-physical systems, with increasing focus on security aspects in recent years. Prof. Ho has received numerous prestigious awards and honors throughout his career. He was named a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) in 2017 and elevated to IEEE Life Fellow status in 2024. He was awarded the Chang Jiang Chair Professorship by the Ministry of Education, China in 2012. Prof. Ho has been recognized as a Highly Cited Researcher for eleven consecutive years from 2014 to 2024, and is among the Top 2% of most highly cited scientists globally from 2020 to 2024. He received the Best Paper Award from The 8th Asian Control Conference in 2011 and the Teaching Excellence Award from City University of Hong Kong in 2020 for his innovative teaching approaches. Prof. Ho has held significant editorial responsibilities, serving as Subject Editor of the Journal of Franklin Institute, Co-Editor in Chief of Franklin Open, Associate Editor of IEEE Transactions on Neural Networks and Learning Systems, Asian Journal of Control, and Action Editor of Neural Networks. He has also served on the editorial boards of several other prestigious journals, contributing to the advancement of his field through scholarly communication. His leadership extends beyond research and teaching as Associate Dean (Undergraduate Education) of the College of Science at City University of Hong Kong, where he plays a key role in shaping the educational experience for science students.

Jonathan J. Wylieمشاهده پروفایل

استاد

• Fluid Mechanics
• Granular Materials
• Suspension Mechanics
• +۲ مورد دیگر

Prof. Jonathan J. Wylie serves as a Professor at City University of Hong Kong, holding a PhD from King's College, University of Cambridge, UK. His academic trajectory includes a Junior Research Fellowship at King's College, followed by research appointments at Cornell University, Woods Hole Oceanographic Institution, and the University of Toronto prior to his current position. His research expertise spans fluid mechanics , granular materials , suspension mechanics , and mathematical modeling of geophysical systems , with seminal contributions to viscous thread dynamics and coupled partial differential equations. His interdisciplinary work bridges industrial applications with fundamental physics. Analysis of his recent publications reveals dominant research threads in granular flow intermittency , thermal effects in viscous filaments , and mathematical neuroscience . His methodology consistently combines asymptotic analysis with computational modeling to address complex multiphysics problems, demonstrating strong cross-disciplinary collaboration between physics, engineering, and life sciences. His distinguished scientific recognition includes: Junior Research Fellowship from King's College, Cambridge Wylie has secured major research funding from the National Science Foundation (USA), Australian Research Council, and Hong Kong's Research Grant Council. As associate editor of the IMA Journal of Applied Mathematics , he actively shapes scholarly discourse. His extensive publication record in high-impact journals like Journal of Fluid Mechanics and Physical Review E demonstrates sustained research productivity without explicit mention of advisees in available materials. While specific laboratory facilities aren't documented, his international collaborations with institutions across North America, Europe, and Asia indicate participation in global research networks addressing industrially relevant fluid dynamics challenges.

SONG Junمشاهده پروفایل

استادیار

• Artificial Intelligence
• Geographic Information Systems
• Environmental Science
• +۵ مورد دیگر

Dr. SONG Jun serves as a Research Assistant Professor in the Department of Geography at Hong Kong Baptist University and is an active member of the Smart Society Lab. His work bridges artificial intelligence with geographical and environmental challenges, focusing on practical urban sustainability solutions. His academic credentials include: Ph.D. from Imperial College London (2017-2021) M.Sc. and B.Sc. from Southwest Jiaotong University, China (2010-2016) Dr. SONG pioneers AI-driven geographical analysis , environmental monitoring systems , and smart city infrastructure . His research develops machine learning frameworks for air pollution mapping, methane monitoring optimization, and pandemic exposure reduction through IoT networks. Key methodologies integrate deep learning with spatiotemporal data to address climate resilience in Chinese urban contexts. His 2021-2023 publications reveal a strong trajectory in applying computer vision to transportation systems and neural networks to environmental sensing. The work spans climate science, public health, and urban informatics, with notable emphasis on carbon management and pandemic response infrastructure in China. Major recognitions include: China Youth Entrepreneurship Award (2017) Cloud-Guizhou Young Scientist Award (2018) AI Challenger Award (2018) As Associate Editor for IEEE Transactions on Emerging Topics in Computational Intelligence, Dr. SONG contributes to academic discourse while serving on the Beijing-Tianjin-Hebei Big Data Association's Environment Protection Committee and the Yangtze River Delta Carbon Neutrality Strategic Development Committee. His Smart Society Lab initiatives focus on real-world AI deployment for sustainable urban development.