جستجوی استاد راهنمای دانشگاهی

Hayden Kwok Hay SOمشاهده پروفایل

دانشیار

• Reconfigurable Computing
• FPGA-Based Systems
• Computer Architecture
• +۷ مورد دیگر

Prof. Hayden Kwok Hay SO is an Associate Professor at the University of Hong Kong (HKU), affiliated with the Department of Electrical and Electronic Engineering. He currently serves as Acting Director of the School of Innovation and previously co-directed the Computer Engineering Program. His research focuses on reconfigurable computing systems, FPGA-based architectures, and their applications in AIoT, medical imaging, and high-performance computing. He holds a B.S., M.S., and Ph.D. in Electrical Engineering and Computer Sciences from UC Berkeley (1998–2007). Prof. So has been recognized with awards such as the IEEE-HKN Teaching Award (2021), Croucher Innovation Award (2013), and multiple teaching excellence awards. He leads the Computer Architecture & System Research Lab (CASR) and co-founded the Joint Lab on Future Cities (JLFC). His work spans FPGA overlay architectures, graph processing systems, and hardware-software co-design for efficient computing. Key research contributions include advancements in FPGA-based reconfigurable systems, sparse dataflow architectures, and medical imaging accelerators. He has secured grants for projects like 'Advanced machine vision guided aquatic surface vehicles' and 'Efficient and Productive Parallel Data Processing in Hybrid FPGA-CPU Clusters.' Prof. So has advised numerous students and researchers, contributing to over 150 peer-reviewed publications. His current projects explore AI hardware acceleration, neuromorphic computing, and FPGA-driven solutions for big data challenges.

• Big Data
• Business Analytics
• Healthcare Analytics
• +۴ مورد دیگر

Haipeng Shen is a Professor of Innovation and Information Management at HKU Business School, The University of Hong Kong, serving as Associate Dean (EMBA and IMBA) and holding the Patrick S C Poon Professorship in Analytics and Innovation. He chairs the Business Analytics and Innovation program and joined HKU in 2015 after previously holding a professorship at the University of North Carolina at Chapel Hill. His academic credentials include: PhD in Statistics, The Wharton School of Business, University of Pennsylvania, 2003 MA in Statistics, The Wharton School of Business, University of Pennsylvania, 2000 BS in Mathematics, School of Mathematical Sciences, Peking University, 1998 Professor Shen's research focuses on data-driven decision making under uncertainty, with expertise spanning big data analytics, business analytics, healthcare analytics, and service engineering. He develops advanced statistical and machine learning methodologies to solve complex operational problems in call centers, optimize stroke care protocols, and enhance financial risk modeling, emphasizing real-time applications in high-stakes environments. Analysis of his recent publications reveals a consistent interdisciplinary approach bridging operations research, statistics, and domain-specific knowledge. His work demonstrates strong methodological innovation in time-series forecasting for service systems, risk assessment frameworks for medical complications, and covariance structure analysis for financial markets, with direct translational impact on business operations and clinical outcomes. His scientific contributions have been recognized with prestigious awards including: Most Influential Publication Award from China Stroke Association (2018) Fellow of the American Statistical Association (2015) Best Advisor of the Year Award from Academy of Asian Business (2018) Elected Member of International Statistical Institute (2015) Cluster Chair for Big Data Analytics at INFORMS International (2015) As an academic leader, Professor Shen has secured significant research funding from organizations including The Xerox Foundation and National Institute on Drug Abuse. He serves as Associate Editor for Management Science, Journal of the American Statistical Association, and Technometrics, while mentoring graduate students in statistical methodology and applied analytics. His current initiatives position HKU Business School at the forefront of healthcare innovation through big data analytics, driving collaborations with medical institutions to transform stroke care and hospital operations in Asia.

Bruno C.d.S. Oliveiraمشاهده پروفایل

دانشیار

• Programming Languages
• Modularity
• Functional Programming
• +۱ مورد دیگر

Dr. Bruno C.d.S. Oliveira is an Associate Professor at the University of Hong Kong's School of Computing and Data Science (SCDS), Department of Computer Science. He holds a DPhil from the University of Oxford (2008). Prior to his current position since 2013, he served as Research Professor at Seoul National University (2009-2011) and Senior Research Fellow at the National University of Singapore (until 2013). His research interests focus on Programming Languages , Modularity , Functional Programming , and Object-Oriented Programming . His work emphasizes foundational aspects like type systems, language design, and extensibility mechanisms. Notable articles include studies on type class implementations, functional graph programming, and meta-theoretical frameworks for programming language constructs. His research has been published in top venues such as POPL, PLDI, ECOOP, and ICFP. No scientific awards are explicitly mentioned in the provided text. Advising records and grant details are not listed, though his academic homepage at http://www.cs.hku.hk/~bruno may contain additional information.

Qiuyu Luمشاهده پروفایل

استادیار

• Ecological HCI
• Computational Design
• Bio-inspired & Biomimetic Design
• +۳ مورد دیگر

Dr. Qiuyu (Luca) Lu is an Assistant Professor (Presidential Young Scholar) at the School of Design of The Hong Kong Polytechnic University and Director of the Interbeing Lab , which focuses on designing intelligence for mutualism between humans, nature, and machines. He holds a Ph.D. in Design and a B.Eng. in Mechanical Engineering from Tsinghua University. Ph.D. in Design, Tsinghua University B.Eng. in Mechanical Engineering, Tsinghua University His research bridges Ecological HCI, Computational Design , and Bio-inspired Engineering , creating sustainable interactive systems that leverage natural processes. Recent projects include: RoboMoRe (2025): LLM-driven robotic morphology optimization Degrade to Function (2024): Programmable eco-degradable interfaces Sustainflatable (2023): Ambient energy harvesting for morphing devices His work has been exhibited internationally at Ars Electronica and the Milan Triennale . Scientific recognition includes a Best Paper Honorable Mention at UIST 2023. Dr. Lu is actively recruiting PhD students and postdocs across disciplines, including design, computer science, mechanical engineering, and materials science, with research tracks in: Experimental Track: Interactive hardware prototyping Computational Track: AI-aided design tools Design Track: User experience frameworks

Shenghua Gaoمشاهده پروفایل

دانشیار

• Spatio-temporal Data Analysis
• Machine Learning
• Database Systems
• +۴ مورد دیگر

Professor Shenghua Gao is an Associate Professor at the School of Computing and Data Science of the University of Hong Kong (HKU), concurrently serving as Assistant Director for Shanghai Initiatives. He holds a PhD from Nanyang Technological University. His research focuses on integrating machine learning, spatio-temporal data analysis, and database systems to address challenges in mobility prediction, traffic management, and geospatial representation learning. He has contributed significantly to trajectory modeling, indexing frameworks for multi-dimensional data, and the application of large language models (LLMs) in spatio-temporal contexts. Key research interests include: Spatio-Temporal Data Science: Developing frameworks for efficient processing and analysis of point cloud, trajectory, and traffic data. Machine Learning for Databases: Innovating indexing algorithms (e.g., BMTree, MAST) and query optimization techniques leveraging ML. Trajectory and Mobility Prediction: Creating personalized models for next-location prediction and transfer learning across regions. Geographic AI (GeoAI): Enhancing road network representation and urban function inference using physics-guided and foundation models. Recent work highlights include the ST-LLM+ framework for traffic prediction, the MAST system for point cloud analytics, and the exploration of City Foundation Models for urban challenges. His publications span top venues in databases (SIGMOD, VLDB) and AI/data science (ICML, NeurIPS). While no awards are explicitly mentioned, his prolific output and leadership roles indicate significant academic contributions. He is actively involved in teaching and supervising research in the School’s undergraduate and postgraduate programs, including MSc(AI) and MPhil/PhD tracks.

Yi-Teng Shihمشاهده پروفایل

استادیار

• Design Cognition
• Design Media
• Design Education
• +۵ مورد دیگر

Yi-Teng Shih is an Assistant Professor at the School of Design, The Hong Kong Polytechnic University, with expertise in design cognition, design media, and design education. He holds a PhD in Architecture from the University of Newcastle, Australia, and a PGCHE in Higher Education from the University of Nottingham, UK. Education: PhD (University of Newcastle, Australia), PGCHE (University of Nottingham, UK) His research explores the intersection of design cognition, computer-aided design, and user experience, with a focus on enhancing learning outcomes through collaborative design competitions and mental imagery analysis. His work has been published in journals like Design Studies and The Design Journal . Recent publications highlight trends in: Neuroscience-informed design teamwork (2025) Educational frameworks for ADHD children (2024) Conceptual metaphor in product language (2024) Digital and analog media in design education (2021–2017) Scientific Awards: THE EDTECH AWARDS 2025 – Finalist Animal Dough Hair Playset (IDEA, 2021) Baby Friendly Bathroom Fitting Series Design (European Product Design Award Gold, 2018) Best Conference Paper Award (2025) Business Casual Headset (IDA Design Awards Gold, 2018) He has supervised numerous award-winning design projects and collaborated with companies such as Brookstone, RadioShack, and FORA, securing twelve patents. His activities include organizing the PolyU Toy Invention Program (2023–2024) and delivering invited talks on design education.

Yi Maمشاهده پروفایل

استاد

• Computer Vision
• High-Dimensional Data Analysis
• Intelligent Systems
• +۳ مورد دیگر

Yi Ma is a Professor of Computer Science at the University of Hong Kong (HKU), serving as Chair of Artificial Intelligence and Director of HKU's School of Computing and Data Science (HKU CDS) and the Musketeers Foundation Institute of Data Science (HKU IDS). He holds a joint faculty position in the Department of Electrical Engineering and Computer Sciences at UC Berkeley. His academic journey includes roles at UIUC (2000-2011), Microsoft Research Asia (2009-2014), and ShanghaiTech University (2014-2017). He earned his PhD from UC Berkeley in 2000, with earlier degrees from Tsinghua University. Research focuses on computer vision, high-dimensional data analysis, and intelligent systems, with contributions to robust face recognition, sparse representation, and deep learning principles. Key publications include works on ReduNet, low-dimensional models, and generalized PCA. He has been Program Chair for ICCV 2013 and General Chair for ICCV 2015. Recent activities include keynote speeches at international conferences (e.g., Future Science Prize Symposium 2024, PRCV 2024) and leadership in initiatives like the Conference on Parsimony and Learning (CPAL 2024). Awards include IEEE, ACM, and SIAM Fellowships, along with best paper and Marr prizes. Education : Bachelor’s in Automation and Applied Mathematics, Tsinghua University (1995) Master’s in EECS and Mathematics, Tsinghua University (1997) PhD in EECS, UC Berkeley (2000) Awards : NSF Career Award (2004) ONR Young Investigator Award (2005) David Marr Prize (ICCV 1999) IEEE/ACM/SIAM Fellowships Labs & Initiatives : HKU IDS and CDS Berkeley Artificial Intelligence Research (BAIR)

Gu Minمشاهده پروفایل

دانشیار بالینی

• Orthodontics
• Craniofacial Orthopedics
• Sleep-Disordered Breathing
• +۴ مورد دیگر

Dr. Gu Min is a Clinical Associate Professor in Orthodontics at the Faculty of Dentistry, The University of Hong Kong. She serves in the Department of Paediatric Dentistry & Orthodontics and has been actively contributing to orthodontic research and education. Her clinical and research expertise focuses on craniofacial orthopedics with special emphasis on airway analysis and pediatric sleep-disordered breathing. Dr. Gu holds multiple advanced degrees including BDS (Wuhan), MDS (Orth) (Sichuan), AdvDipOrth (HK), MOrth RCSEd, PhD (HK), and FDS RCSEd. Her educational background demonstrates strong foundation in both clinical dentistry and research methodology. Her primary research interests center around orthodontic treatment of pediatric sleep disordered breathing, 3D technology-assisted orthodontic diagnosis and treatment, and craniofacial regeneration. She has pioneered work in upper airway analysis using advanced imaging techniques and has published extensively on facial asymmetry assessment and digital orthodontics applications. Her research bridges the gap between traditional orthodontics and modern digital technologies, with particular focus on how craniofacial morphology relates to airway function. Analysis of her recent publications reveals a strong trend toward 3D imaging applications in orthodontics, with increasing focus on airway analysis in relation to sleep-disordered breathing, facial asymmetry quantification, and digital workflow development. Her work demonstrates consistent progression from basic cephalometric analysis to advanced 3D imaging techniques and their clinical applications. Best Presentation Award at 2024 Annual Scientific Meeting, Faculty of Dentistry, HKU Award of the Faculty Annual Scientific Meeting, Faculty of Dentistry, HKU (2022) Finalist in the CTOR Award for Student Excellence in Orthodontics Research (2021) 1st price at QUEST5.0 Graduate Dental Science Extravaganza IDEA 2021 (2021) First Place at The 33rd IADR-SEA Division Annual Scientific Meeting (2019) Dr. Gu has been principal investigator and co-investigator on multiple research grants, including General Research Fund projects on AI-assisted orthodontic-orthognathic surgery planning and 3D tooth tracking. She serves on several professional committees including the Committee on the Use of Live Animals in Teaching and Research at HKU. Her knowledge exchange activities include numerous media appearances where she discusses orthodontic treatments and their relationship with children's sleep disorders. As an active member of the European Orthodontic Society, World Federation of Orthodontics, and The Royal College of Surgeons of Edinburgh, Dr. Gu maintains strong international connections in her field. She also serves as a trainer for Specialty Boards in both Paediatric Dentistry and Orthodontics for The College of Dental Surgeons of Hong Kong.

• Algorithms
• Combinatorial Optimization
• Discrete Metric Spaces
• +۷ مورد دیگر

Hubert Tsz-Hong Chan is an Associate Professor in the Department of Computer Science, School of Computing and Data Science at The University of Hong Kong. He earned his PhD in 2007 from Carnegie Mellon University under the supervision of Anupam Gupta, followed by post-doctoral research at the Max-Planck-Institut für Informatik (2007-2009). Education PhD in Computer Science, Carnegie Mellon University, 2007 Research Interests Dr Chan's research lies at the intersection of algorithms , combinatorial optimisation , discrete metric spaces , and security & privacy . A recurring theme is the design of provably efficient approximation algorithms for geometric and graph-theoretic problems under realistic or adversarial settings. Representative contributions include polynomial-time approximation schemes (PTAS) for TSP and Steiner Forest in doubling metrics, spectral analysis of hypergraph Laplacians, and foundational work on differential obliviousness and oblivious RAM. Publications & Trends With more than 80 peer-reviewed papers in premier venues such as JACM , SIAM Journal on Computing , Algorithmica , FOCS , SODA , EUROCRYPT , ASIACRYPT , CCS , and WWW , his recent output (2018-2021) demonstrates a shift toward privacy-preserving algorithms, differential obliviousness, and socially-aware optimisation models, often combining rigorous theory with practical datasets like Netflix and Twitter. Scientific Awards IPDPS 2019 Best Paper Award WWW 2018 Honorable Mention Students & Mentoring Dr Chan has successfully graduated 17 PhD and MPhil students and currently mentors 7 PhD candidates and 1 MPhil student. His graduates have secured academic and industry positions worldwide, and their theses frequently build on his funded projects. Research Funding & Labs Since 2012 he has been Principal Investigator on 12 competitive grants from the Hong Kong Research Grants Council (RGC), totalling more than HK$8 million, spanning topics from privacy-preserving aggregation to Byzantine-resilient federated learning. While no dedicated laboratory name is advertised, his group operates within the Security & Privacy and Algorithms Labs in the Department of Computer Science.

Sze Yim Binh Felixمشاهده پروفایل

دانشیار

• Sign Language Documentation
• Sign Language Typology
• Information Structure
• +۷ مورد دیگر

Prof. Felix Sze (Sze Yim Binh) is an Associate Professor at the Department of Linguistics and Modern Languages , The Chinese University of Hong Kong . She holds a PhD in Linguistics from the University of Bristol and has been a leading figure in sign language research and Deaf community empowerment in the Asia-Pacific region. Education: BA & MPhil from CUHK, PhD from University of Bristol Her research focuses on sign language documentation (Hong Kong, Macau, Sri Lankan, Indonesian, Japanese varieties) and linguistics analysis of grammatical structures including word order and non-manual markers. She specializes in bimodal-bilingual acquisition by deaf/hard-of-hearing children in Cantonese and Hong Kong Sign Language, developing assessment tools like the HKSL Sentence Repetition Test . She also investigates sign language's cognitive benefits for hearing infants and elderly populations. Prof. Sze's recent publications analyze polar questions and negation markers, word order typology, and interpretation training frameworks. She leads major projects like the Hong Kong Sign Language Browser and Asian SignBank , creating educational resources for Deaf communities including sex education and medical terminology databases. Her work combines rigorous sign language corpus development with practical applications in education, healthcare, and technology, including AI-driven sign recognition systems like SignTown . She has presented at major international conferences including TISLR, Sign Language Acquisition Conference, and World Federation of the Deaf Congress.

David Philip Thierfelderمشاهده پروفایل

استادیار

• Sign Linguistics
• Experimental Linguistics
• Psycholinguistics
• +۳ مورد دیگر

David Philip Thierfelder serves as an Assistant Professor at The Chinese University of Hong Kong (CUHK), affiliated with the Centre for Sign Linguistics and Deaf Studies. His academic foundation includes a PhD in Applied and Educational Linguistics from the University of Melbourne (2020). His educational background features: PhD in Applied and Educational Linguistics, University of Melbourne, 2020 Dr. Thierfelder pioneers experimental investigations into linguistic processing among Hong Kong Sign Language (HKSL) users through advanced neurocognitive methodologies. His research integrates eye-tracking and event-related potentials (ERPs) to dissect cognitive mechanisms in both deaf and hearing sign language communities, bridging Sign Linguistics with Cognitive Neuroscience. This work reveals critical insights into neural specialization for visual-gestural languages and challenges spoken-language-centric models of linguistic processing. Prior to his doctoral studies, he contributed extensively to CUHK's Centre for Sign Linguistics and Deaf Studies through the Asia Pacific Sign Linguistics Research and Training Program, functioning as teacher, researcher, and certified sign language interpreter. This dual expertise in empirical research and community engagement positions him uniquely at the intersection of theoretical linguistics and practical deaf education. No scientific awards or grants are documented in available sources. Similarly, student supervision details remain unspecified in current institutional records.

Ting Kei Pongمشاهده پروفایل

استاد

• Continuous optimization
• Convex relaxations
• First-order methods
• +۳ مورد دیگر

Ting Kei Pong is a Professor in the Department of Applied Mathematics at the Hong Kong Polytechnic University, where he has been employed since August 1, 2014. His research focuses on continuous optimization, with particular expertise in convex relaxations and first-order methods for large-scale optimization problems. Dr. Pong received his Bachelor's degree in 2004 and MPhil degree in 2006 from the Department of Mathematics at the Chinese University of Hong Kong. He completed his PhD in 2011 from the Department of Mathematics at the University of Washington under the supervision of Professor Paul Tseng, with co-advisement from Professors Maryam Fazel and Rekha Thomas after Professor Tseng's disappearance. His postdoctoral training included positions at the University of Waterloo (2011-2013) and the University of British Columbia (2013-2014) as a PIMS postdoctoral fellow. His research interests span Continuous Optimization , with current focus on convex relaxations and first-order methods for large-scale problems. He also investigates constraint qualifications for convex optimization, statistical computation, and robust optimization. His work bridges theoretical foundations with practical applications in areas such as compressed sensing, sensor network localization, and machine learning. Dr. Pong's publication record demonstrates consistent high-impact contributions to optimization theory. His recent work (2022-2025) shows a strong focus on convergence analysis, error bounds for conic optimization problems, and development of efficient algorithms for nonconvex optimization. His research often combines theoretical analysis with practical implementation, as evidenced by the availability of code for many of his publications. He serves as Associate Editor for Mathematics of Operations Research (since 2019) and on the editorial boards of Computational Optimization and Applications, Pacific Journal of Optimization, and Open Journal of Mathematical Optimization. Dr. Pong actively mentors students and postdocs, currently supervising PhD students Yanbo Wang and Hao Zhang, and postdoc Jiefeng Xu. His former students have secured positions at institutions including the University of Texas Arlington, University of Hong Kong, and Sun Yat-Sen University. His advising reflects his research expertise, with students working on topics in nonconvex optimization, compressed sensing, and matrix factorization. He maintains an active research schedule, regularly presenting at major optimization conferences including ICCOPT, ISMP, and SIAM Optimization. His upcoming talks in 2025 demonstrate continued research productivity in error bounds for log-determinant cones and single-loop proximal-conditional gradient methods.

Yuk Huiمشاهده پروفایل

استاد

• Philosophy of Technology
• Philosophy of Biology
• Speculative Philosophy
• +۲ مورد دیگر

Yuk Hui is Professor of Philosophy at Erasmus University Rotterdam, where he is affiliated with the Erasmus School of Philosophy. He is a prominent figure in contemporary philosophy of technology, serving as convenor of the Research Network for Philosophy and Technology since 2014 and as a juror of the Berggruen Prize for Philosophy and Culture since 2020. Professor Hui completed his doctoral studies under the French philosopher Bernard Stiegler at Goldsmiths College, University of London, and later obtained his Habilitation in philosophy from Leuphana University in Germany. His academic journey reflects a deep engagement with European philosophical traditions while maintaining a critical perspective informed by his Chinese heritage. Hui's research focuses on the philosophy of technology, particularly exploring alternative technological trajectories beyond Western modernity. His work centers on the concept of 'cosmotechnics,' which examines how different cultural traditions conceptualize the relationship between techne and cosmos. He investigates how Chinese philosophical thought might offer alternative frameworks for understanding technology in the Anthropocene. His research spans comparative philosophy, examining connections between Chinese and European philosophical traditions, with particular attention to thinkers like Wang Bi, Mou Zongsan, Kant, Hegel, Simondon, and Stiegler. Professor Hui's scholarly contributions have been recognized with the SCM Distinguished Research Award (2022) and the Humanities and Social Sciences Prestigious Fellowship (2022-2023). His publications span multiple languages and address critical questions at the intersection of technology, philosophy, and culture. As convenor of the Research Network for Philosophy and Technology, Hui has organized significant academic events, including symposia commemorating Lyotard's 'The Postmodern Condition' and 'Les Immatériaux.' His work bridges theoretical inquiry with practical concerns about the direction of technological development in the 21st century. Professor Hui's research program centers on developing a pluralistic understanding of technology that acknowledges diverse cultural approaches to technics. His current work explores planetary thinking, algorithmic contingency, and the relationship between machines and ecology, seeking alternatives to the dominant technological paradigm.

• 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.

• 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.