جست‌وجوی استاد و پژوهشگر

• Control Systems
• Dynamic System Modeling
• System Identification
• +۵ مورد دیگر

Professor Quanmin Zhu is a Professor in Control Systems at the School of Engineering, University of the West of England (UWE), Bristol, UK, holding this position since 2004. His academic career spans over four decades, including roles as Lecturer at Qiqihar University (China, 1983-1986), Post-doctoral Researcher at University of Sheffield (UK, 1989-1994), Lecturer at University of Brighton (UK, 1994-1997), and Lecturer/Reader at Aston University (UK, 1997-2004). His educational background includes: MSc in Engineering from Harbin Institute of Technology, China (1980-1983) PhD from University of Warwick, UK (1986-1989) Professor Zhu's research centers on dynamic system modeling, identification, control, and simulation, with pioneering contributions to nonlinear control systems, robust control methodologies, and U-model based control frameworks. His work bridges theoretical advances with practical applications in robotics, renewable energy systems, and industrial automation, emphasizing model-free and adaptive control solutions for complex nonlinear dynamics. Analysis of his 2021-2025 publications reveals a dominant focus on robust control for uncertain nonlinear systems, with significant contributions to sliding mode control, multi-agent coordination, and cyber-physical security. His research increasingly integrates machine learning techniques (e.g., actor-critic reinforcement learning) while maintaining core expertise in optimization-based control algorithms applied to UAVs, robotic manipulators, and wind energy systems. His professional honors include: Chartered Engineer (CEng) Fellow of the Institution of Engineering and Technology (FIET) Fellow of the Higher Education Academy (FHEA) As an academic leader, Professor Zhu serves as President/Founder of the International Conference on Modelling, Identification and Control (ICMIC), Editor/Founder of Elsevier's Book Series on Emerging Methodologies in Modelling and Control, and University Ambassador for UK-China educational collaboration. His research group secures substantial grants in control theory applications, with ongoing projects in U-model control platforms and international partnerships. He leads the Control Systems research group at UWE, driving innovation in the U-control platform and its industrial applications. His team maintains strong international collaborations, particularly with Chinese institutions, and actively develops the Elsevier Book Series as a key publication channel for emerging control methodologies.

Daniel Catchpooleمشاهده پروفایل

استاد

• Childhood Cancer Research
• Genomics
• Biomedical Data Science
• +۶ مورد دیگر

Professor Daniel Catchpoole serves as Deputy Head of School (Research) at the School of Computer Science, University of Technology Sydney (UTS), holding dual appointments at UTS and The Children's Hospital at Westmead. With over 20 years of research experience, he bridges computational sciences and pediatric cancer research through the Biomedical Data Science Lab in the Australian Artificial Intelligence Institute. His work integrates data analytics, artificial intelligence, and software development with molecular cancer biology to transform pediatric cancer treatment pathways. PhD in Cancer Cell Biology, University of New South Wales (1991-1995) Founding Fellow, Royal College of Pathologists Australasia (2010-present) Head, Children's Hospital at Westmead Tumour Bank (2001-present) Professor Catchpoole's research focuses on translational applications of genomics in childhood cancers, particularly acute lymphoblastic leukemia and neuroblastoma. His work combines high-throughput genomic technologies with advanced computational analysis to develop systems biology approaches for cancer patient assessment. Recent projects explore virtual reality applications for complex genomic data visualization and copper chelation therapies to enhance neuroblastoma immunotherapy. His research has received significant funding from Cancer Institute NSW, Sony Foundation, ARC, and NHMRC. His publication record spans biomedical data science, cancer genomics, and virtual reality applications in oncology. Recent work demonstrates leadership in 3D latent diffusion models for tumor segmentation, biobank economics, and innovative immunotherapies. His research consistently addresses the critical need for actionable knowledge from complex multidimensional biomedical data. Editorial Board Member, Cancers (2023) Associate Editor, Innovations in Digital Health, Diagnostics and Biomarkers (2019) Founding member and first President, Australasian Biospecimens Network Association Professor Catchpoole has supervised 17 Honours students (including 6 First Class Honours), 3 MSc students, and 12 PhD candidates across multiple institutions, with 6 current PhD students. His collaborative research bridges UTS's Faculty of Engineering and IT with The Children's Cancer Research Unit at The Children's Hospital at Westmead. Significant research funding includes Cancer Institute NSW grants, Sony Foundation VR projects, and ARC Discovery Projects focused on genomic data analysis and clinical decision support systems. His leadership extends to building frameworks for translational research, managing biobanks and clinical data linkages, and navigating governance requirements for cancer research. The Tumour Bank at Kids Research, CCRU, represents his long-standing commitment to pediatric cancer infrastructure development.

Luciano Lavagnoمشاهده پروفایل

استاد

• Field Programmable Gate Arrays (FPGA)
• High-Level Synthesis
• Indoor Positioning
• +۱۰ مورد دیگر

Luciano Lavagno is a Full Professor at the Department of Electronics and Telecommunications, Polytechnic University of Turin, with over two decades of academic and research contributions. His work bridges hardware acceleration, low-power electronics, and intelligent system design. Research Focus: Hardware-accelerated machine learning, high-level synthesis (HLS) for FPGA/ASIC, heterogeneous CPU/GPU/FPGA platforms Key Projects: SPACE (predictable acceleration), REBECCA (secure AI acceleration), HPC-National Center (quantum computing), and oral history preservation via "Ti racconto una storia" initiative His recent publications analyze CNN inference optimization, subgraph isomorphism, and superword-level parallelism exploitation. Lavagno supervises multiple PhD students working on FPGA acceleration, neural network hardware, and embedded systems. As Principal Investigator for national and EU-funded projects (PRIN, JTI-ECSEL, PNRR), he drives advancements in sustainable computing infrastructure. His patented technologies include MIx&Latch timing methodology, capacitive sensing innovations, and 5G acceleration frameworks.

Erin Bellمشاهده پروفایل

استاد

• Structural Engineering
• Civil Engineering
• Structural Health Monitoring
• +۸ مورد دیگر

Erin Bell is a Professor in the Department of Civil and Environmental Engineering at the University of New Hampshire . She holds a Ph.D. in Structural Engineering from Tufts University and has extensive experience in structural health monitoring, finite element modeling, and infrastructure sustainability. B.C.E., Georgia Institute of Technology M.S., Civil Engineering, Tufts University Ph.D., Structural Engineering, Tufts University Her research focuses on structural health monitoring, bridge condition assessment, and integrating AI techniques like artificial neural networks and deep reinforcement learning for infrastructure asset management. Recent work includes equitable maintenance strategies for aging bridges in flood-prone zones and tidal energy conversion for sustainable bridge monitoring systems. Key trends in her publications include the application of machine learning to structural analysis, finite element model calibration, and climate change adaptation in transportation infrastructure. She has led projects on deep reinforcement learning for bridge scour maintenance, modal-based uncertainty quantification, and multi-scale modeling of steel bridges. Grants and Collaborations : Erin Bell has secured funding from the National Science Foundation (NSF) , US Department of Energy (DOE) , and New Hampshire Department of Transportation . Notable projects include the Living Bridge initiative for tidal energy-powered smart infrastructure and statewide data exchange systems for bridge condition assessment.

• Structural Engineering
• Structural Health Monitoring
• Civil Engineering
• +۳ مورد دیگر

Dr. Andy Nguyen is a Senior Lecturer in the School of Engineering at the University of Southern Queensland. He holds a PhD from Queensland University of Technology (QUT), an MEng from the National University of Civil Engineering (NUCE), and a BEng from NUCE. His research focuses on structural health monitoring, integrating machine learning and deep learning techniques to assess infrastructure integrity. Key areas include damage detection in bridges, pavements, and buildings, as well as sustainable construction materials like bamboo. Nguyen leads projects such as the 'Next Generation Living Laboratory for Engineering Education and Engagement,' emphasizing real-world applications of technology in civil infrastructure. His work spans crack detection algorithms, finite element model updating, and vibration-based structural analysis. He collaborates on AI-driven solutions for autonomous vehicle object detection and smart maintenance planning. Nguyen’s contributions include over 50 peer-reviewed publications and active supervision of postgraduate research in composite materials and transport infrastructure. His research outputs highlight advancements in computational mechanics, sensor technologies, and data-driven methods for infrastructure resilience. Nguyen’s expertise bridges civil engineering challenges with cutting-edge machine learning, advancing both theoretical and applied solutions for sustainable and safe structures.

Abdullah Mueenمشاهده پروفایل

استاد

• Temporal Data Mining
• Blockchain Data Mining
• Social Media Mining
• +۵ مورد دیگر

Abdullah Mueen is a Professor and Associate Chair in the Department of Computer Science at the University of New Mexico (UNM), where he has been since 2013. Previously, he worked as a Scientist in the Cloud and Information Sciences Lab at Microsoft Corporation. Research Interests : His work focuses on Temporal Data Mining , with emphasis on efficiency , interactivity , and interpretability . Key areas include Blockchain Data Mining (e.g., BitLink for Bitcoin cluster analysis), Seismic Data Mining (e.g., PAW for aftershock detection), and Social Media Mining (e.g., DeBot for Twitter bot detection). Article Trends : His recent publications span four domains: Seismology : Algorithms for earthquake data analysis (e.g., focal depth inference, aftershock classification). Blockchain : Temporal linkage of Bitcoin addresses (BitLink) and cryptocurrency fraud detection. Traffic Safety : Multi-LiDAR data fusion for real-time road safety monitoring. Time Series Methods : Innovations like MASS similarity search and DAMP anomaly detection for massive datasets. Scientific Awards : ACM SIGKDD Test-of-Time Award (2022) UNM Provost Research Leader Award UNM School of Engineering Junior Faculty Research Excellence Award KDD 2012 Doctoral Dissertation Contest Runner-Up KDD 2012 Best Paper Award Advising and Grants : He has mentored 11 PhD students now employed at institutions like Microsoft, Meta, and Lawrence Livermore National Lab. His research is funded by NSF , NIH , DARPA , AFRL , NEC , Exxon , Microsoft , and LANL .

Ooi Beng Chinمشاهده پروفایل

استاد

• Database Systems
• Distributed Systems
• Blockchain
• +۶ مورد دیگر

Ooi Beng Chin is a Professor at the School of Computing , National University of Singapore (NUS). He holds concurrent roles as an adjunct Chang Jiang Professor at Zhejiang University, Visiting Distinguished Professor at Tsinghua University, and Director of NUS AI Innovation and Commercialization Centre in Suzhou, China. He earned his B.Sc. (1st Class Honours, 1985) and Ph.D. (1989) from Monash University, Australia. His research spans database systems, blockchain, machine learning, and large-scale analytics , focusing on system architectures, security, and cross-domain applications. Notable contributions include initiating the Apache SINGA distributed deep learning platform and developing Blockbench, the first blockchain benchmarking system. He also co-founded MZH Technologies (2018) for healthcare analytics. Key publications highlight his work in blockchain-database integration, AI for healthcare/finance, and 5G-enabled data systems. Awards include the ACM SIGMOD EF Codd Innovation Award (2020), Singapore President's Science Award (2011), and fellowships from SNAS, IEEE, ACM , and SAEng (2023). He leads the Singapore Blockchain Innovation Programme (SBIP) and contributes to industry collaborations with healthcare institutions and financial organizations. Fellow, Singapore National Academy of Science (SNAS) Fellow, IEEE Fellow, ACM Singapore President's Science Award, 2011 IEEE Kanai Award, 2012 NUS Outstanding Researcher Award, 2013 ACM SIGMOD EF Codd Innovation Award, 2020 Foreign Member, Chinese Academy of Sciences, 2023

Morteza Ghorbaniمشاهده پروفایل

پژوهشگر

• Environmental Engineering
• Fluid Mechanics
• Nanotechnology
• +۳ مورد دیگر

Dr. Morteza Ghorbani is a researcher and faculty member at Sabancı University's Faculty of Engineering and Natural Sciences (FENS), specializing in fluid mechanics and environmental engineering. He leads the AquaCav project, a collaborative effort with Oxford Brookes University, focused on developing sustainable water treatment solutions using hydrodynamic and acoustic cavitation. His research addresses global challenges such as PFAS pollution and wastewater management, with applications in biomedical devices and energy-efficient technologies. Key collaborations include projects funded by the International Science Partnership Fund (ISPF), leveraging his expertise in microfluidic systems and cavitation dynamics. Dr. Ghorbani's work combines experimental and numerical methods to optimize cavitation-based processes for environmental and biomedical applications. His contributions span from fundamental fluid dynamics studies to applied technologies like flexible cystoscopes and clot-on-a-chip platforms. Scientific achievements include the ISPF Research Collaboration Grant (2024) and advancements in PFAS removal, graphene exfoliation, and microalgae cultivation. His research group at Sabancı University explores interdisciplinary solutions at the intersection of engineering, nanotechnology, and sustainability.

Dmitri Perkinsمشاهده پروفایل

استاد

• Wireless Communications
• Mobile Networking
• Network Security
• +۴ مورد دیگر

Dmitri Perkins is a Professor at the Department of Computer Science and Electrical Engineering within the College of Engineering and Information Technology at the University of Maryland, Baltimore County (UMBC). He has held leadership roles including Senior Program Director at the National Science Foundation (2021-2024) and Lead Program Director for the NSF's Industry-University Cooperative Research Centers (2015-2019). His research spans wireless and mobile networking paradigms, including cognitive radio, sensor networks, and large-scale heterogeneous systems. Ph.D., Computer Engineering, Michigan State University (2002) M.S., Computer Engineering, Michigan State University (1997) B.S., Computer Science, Tuskegee University (1995) His research focuses on adaptive protocol design , spectrum management , and network security . Key areas include dynamic spectrum access , cross-layer optimization , and formal performance evaluation in wireless systems. Publications highlight innovations in cognitive radio networks , IoT protocols , and secure wireless communication . Recent publications emphasize machine learning for spectrum efficiency , edge computing in heterogeneous networks , and security frameworks for wireless systems. The 15 most recent works (2002-2018) demonstrate expertise in protocol design , network scalability , and spectrum optimization . NSF CAREER Award (2005) NSF Director's Award for Superior Accomplishment (2024) ONR Research Fellow, U.S. Naval Research Lab (2013-2014) He leads a research lab at UMBC offering RA positions in spectrum research , IoT/CPS systems , and wireless cybersecurity . Prior to UMBC, he served as Hardy Edmiston Endowed Professor at the University of Louisiana at Lafayette and held roles at the U.S. Naval Research Laboratory.

• IoT Systems
• Data Quality
• Fog Analytics
• +۷ مورد دیگر

John Byabazaire is a Research Fellow at the School of Computer Science, University College Dublin (UCD). He holds a PhD in Computer Science from UCD (2024), following a BSc (Gulu University, 2013) and MSc (Waterford Institute of Technology, 2018). His research focuses on IoT systems for data collection, remote sensing, AI-driven end-to-end system management, and fog analytics. He has held academic roles including Assistant Lecturer at Gulu University (2018–2019) and teaching roles at UCD since 2019, including Occasional Lecturer and Senior Teaching Assistant. His research spans smart agriculture, data quality in IoT, and education technology. Notable contributions include frameworks for yield mapping in precision agriculture, trust-based data validation in IoT, and machine learning approaches for livestock health monitoring. He has secured grants like the National ICT Initiatives Support Program (Uganda Government, 2019–2020). Teaching includes courses on cloud computing, web development, and distributed systems. His articles emphasize IoT data quality, agricultural analytics, and educational technology innovation. He actively promotes technology adoption in African education and agriculture sectors through collaborative projects.

Robert Laganièreمشاهده پروفایل

استاد

• Computer Vision
• Image and Video Analysis
• Visual Surveillance
• +۸ مورد دیگر

Robert Laganière is a Professor at the School of Electrical Engineering and Computer Science at the University of Ottawa, where he has been actively contributing to the fields of computer vision and image analysis. He is a member of the VIVA research laboratory and holds a Ph.D. and M.Sc. from INRS-Telecommunications in Montreal, as well as a bachelor's degree in Electrical Engineering from École Polytechnique de Montréal. Bachelor's in Electrical Engineering: École Polytechnique de Montréal (1987) Master's Degree: INRS-Telecommunications (1990) Doctorate: INRS-Telecommunications (1996) Professor Laganière's research focuses on computer vision, with particular expertise in image and video analysis, visual surveillance, embedded vision systems, and deep learning applications. His work spans fundamental research in feature detection and matching to practical applications in autonomous driving, human recognition, and real-time object tracking. He has made significant contributions to the development of algorithms for pedestrian detection, age and gender recognition, and 3D object localization. His publication trends reveal a consistent focus on practical computer vision applications with a strong emphasis on real-time performance and embedded implementation. Over the past decade, his research has evolved from foundational work in feature matching and homography estimation toward more complex applications in action recognition, human-computer interaction, and intelligent surveillance systems. His work consistently bridges theoretical computer vision with practical engineering constraints, particularly for mobile and embedded platforms. Best Paper Award, IEEE International Conference on Computer and Robot Vision (CRV 2014) Best Paper Award, CVPR Embedded Vision Workshop, Providence, RI, June 2012 Best Real-time Tracker, IEEE International Conference on Computer Vision (ICCV) Workshop on Visual Object Tracking (VOT2015) Professor Laganière has supervised numerous graduate students through the years, with a particular focus on practical applications of computer vision in surveillance, human recognition, and embedded systems. His research has been supported through industry partnerships with companies including CogniVue Corp, NXP, iWatchLife.com, Solink Corp, CBSA Canada, Ross Video, Thales, Habitat Seven, and YouI Labs. He has successfully translated his research into commercial applications through his founding of Visual Cortek (acquired by iWatchLife in 2009) and Tempo Analytics (founded in 2016). As a member of the VIVA research laboratory, Professor Laganière collaborates with colleagues on advanced computer vision projects, particularly those involving intelligent video analytics for security and commerce applications. His work on NAVIRE (Virtual Navigation in Remote Environments) demonstrates his commitment to developing practical solutions for real-world navigation challenges using image-based representations of real environments.

Hui Zhangمشاهده پروفایل

استاد

• Computer Science
• Networking
• Data-Driven Systems
• +۳ مورد دیگر

Hui Zhang is a Professor in the Computer Science Department at Carnegie Mellon University. His research focuses on data-driven networking systems, video streaming optimization, and network control frameworks. He has contributed to innovations in adaptive resource allocation, real-time analytics, and sustainable strategies for resource utilization. Key research themes include time-state analytics, network anomaly detection, and integrating machine learning for enhanced performance. His work addresses challenges in content delivery networks (CDNs), peer-to-peer systems, and environmental applications like waste management. Recent publications (2021–2024) highlight advancements in neural network-based prediction, timeline frameworks, and sustainable material science innovations. No scientific awards are mentioned in the provided text. His research emphasizes practical solutions for improving video quality of experience (QoE), network efficiency, and cross-disciplinary applications.

Chenhao Chuمشاهده پروفایل

استاد

• RF/mm-Wave Circuits
• Power Amplification
• AI-Assisted Design Synthesis
• +۴ مورد دیگر

Dr. Chenhao Chu is a Professor at ETH Zürich, holding the Professur für Elektronik (Professorship for Electronics). He specializes in RF/mm-Wave circuits, AI-driven design methods, and advanced power amplification technologies. His research focuses on energy-efficient, wideband systems, antenna-in-package solutions, and GaN-based applications for 6G and beyond. Education: Ph.D. in Electronic Engineering, University College Dublin (2022) M.Sc. in Electronic Information Engineering, City University of Hong Kong (2017) Research Interests: His work bridges AI and hardware design, emphasizing reconfigurable circuits , high-linearity power amplifiers , and mm-Wave phased arrays . Key areas include: AI-assisted rapid design synthesis III-V/Si co-design for mm-Wave Efficient antenna integration Dynamic load modulation techniques Awards: Award-winning researcher with distinctions including the First Place Best Student Paper Award (2022 Royal Irish Academy Colloquium) and multiple HEPA-SDC Competition Awards (2021-2022). Recognized for innovations in PA efficiency and design automation. Advising & Grants: Leading projects on 6G PA architectures and AI-driven RF design. Active in IEEE with contributions to conferences like IMS and ARFTG. No explicitly stated grants mentioned but widely cited in industry-academia collaborations. Labs & Teams: Associated with ETH Zürich's Electronics Laboratory, focusing on next-generation wireless systems. Collaborates internationally on 5G/6G infrastructure and mm-Wave innovations.

Travis Hortonمشاهده پروفایل

دانشیار

• Thermal Energy Conversion Systems
• Building Energy Utilization
• Renewable Energy Integration
• +۳ مورد دیگر

W. Travis Horton is an Associate Professor of Civil Engineering at Purdue University, with a courtesy appointment in Mechanical Engineering. He holds a Ph.D. from Purdue University and has over 20 years of academic and industry experience in thermal systems research. His affiliations include the Lyles School of Civil Engineering and the Ray W. Herrick Laboratories at Purdue, focusing on advanced thermal energy conversion systems and sustainable building technologies. Dr. Horton’s research emphasizes integration of HVAC systems with renewable energy, optimization of ground-source heat pumps, and innovative compressor/expander technologies. He leads projects on building energy modeling, combined heat and power systems, and waste heat recovery. His work bridges experimental facilities with computational models for system analysis and optimization. His teaching includes courses on building mechanical systems design and energy audits. He is a licensed Professional Engineer (Michigan) and holds universal refrigerant certification. Active in professional organizations like ASHRAE, his research has produced over 50 peer-reviewed articles since 2001, addressing thermal efficiency, energy systems integration, and sustainable building design.

Michael Stevensمشاهده پروفایل

مدرس ارشد

• Biomedical Engineering
• Advanced Manufacturing
• Digital Manufacturing
• +۶ مورد دیگر

Dr. Michael Stevens is a Senior Lecturer at University of New South Wales (UNSW) Canberra , where he focuses on advanced manufacturing and biomedical device control systems . His work bridges digital manufacturing for SMEs with smart artificial heart technologies , emphasizing industry collaboration and translational research. Specializes in physiological control systems for rotary blood pumps Develops unobtrusive fall detection systems for dementia patients Leads international projects on total artificial heart development Education : B.Eng (Medical - First Class Honours), Queensland University of Technology (2010) PhD in Physiological Control for Biventricular Assist Devices, University of Queensland (2014) Research Trends show consistent focus on: Machine learning for biomedical diagnostics (2018–2025) mmWave radar and thermal sensors in patient monitoring (2021–2024) Computational fluid dynamics in artificial heart modeling (2016–2024) Physiological control algorithms for rotary blood pumps (2011–2025) Scientific Awards : UNSW Scientia Education Award (2021) for contextual teaching Heart Foundation Runner-up for "Smart Artificial Hearts" pitch (2021) ARC PGC Supervisor Award (2017) for mentoring Grants & Supervision : Holds over $6 million in competitive funding including MRFF and ARC grants. Currently supervises 4 PhD students while maintaining industry partnerships with VitalCare and BiVACOR. Labs & Facilities : Works across UNSW Engineering labs and Graduate School of Biomedical Engineering platforms, including mock circulation loops and high-performance computing clusters for CFD simulations.