جست‌وجوی استاد و پژوهشگر

• Control Theory
• Artificial Intelligence
• Robotics
• +۵ مورد دیگر

Dr. Hamid Abdi is a Senior Lecturer in Engineering Management at the School of Engineering, Deakin University. He holds a PhD from Deakin University (2011) and has over 20 years of combined academic and industrial experience in control systems, robotics, and engineering education. His research focuses on control theory (time-delay systems, fault tolerance), robotics (dynamics, teleoperation), and industrial automation (SCADA, PLC systems). He has supervised 12+ doctoral/master students and led projects in energy systems, medical robotics, and IoT applications. Education: BEng/MEng (Control Engineering, Sharif University, 1998-2000), PhD (Deakin University, 2011). Professional affiliations include Senior Membership in IEEE and collaboration with Colorado State University. Research interests span AI on hardware systems, dynamical systems modelling, entrepreneurship in engineering, and optimisation. Recent projects include robotic ultrasound systems (HaptiScan), energy storage control software, and haptic teleoperation for medical diagnostics. His work has led to multiple awards, including the Alfred Deakin Best Thesis Medal (2013) and VC Staff Award (2015). Teaching areas: Process control, robotics, entrepreneurship, signal processing Grants: $542,594 in industry-funded research (e.g., Telstra, Energys Australia) Labs/Teams: Institute for Intelligent Systems Research and Innovation, Centre for Intelligent Systems Research

• Machine Learning
• Ensemble Learning
• Feature Selection
• +۴ مورد دیگر

Gavin Brown is a Professor of Computer Science at the University of Manchester, affiliated with the Data Science Institute and the Machine Learning and Optimisation group. His research focuses on machine learning theory, ensemble methods, feature selection, and hardware-accelerated learning. He holds roles in interdisciplinary initiatives like the Centre for Digital Trust and Society, EnnCore project (privacy-preserving neural architectures), and the Robotics and Artificial Intelligence Centre. Education: PhD in Computer Science from the University of Birmingham (2003), with a thesis on 'Diversity in Neural Network Ensembles'. Research interests span theoretical foundations of machine learning, including bias-variance decomposition, ensemble diversity, and algorithmic stability. Applications include healthcare (e.g., outlier detection in vital signs), robotics (low-cost prediction hardware), and ethical AI (conceptual guarding of neural networks). He has pioneered work on feature selection for resource-constrained systems and neuromorphic computing. Recent articles emphasize unifying ensemble theory, hardware-efficient learning (FPGA-based feature selection), and clinical applications of machine learning. Projects include EnnCore (privacy-preserving AI), RAI Centre (robot-AI ethics), and Data Visualisation for clinical trials. He leads or co-leads 8 major projects, including £multi-million initiatives in digital trust, robotics, and AI. Supervised 24 doctoral students, with a focus on interdisciplinary work combining theory and applied machine learning.

• Spacecraft Systems Engineering
• Orbital Aerodynamics
• Space Debris Mitigation
• +۳ مورد دیگر

Dr. Peter Roberts is a Reader in Spacecraft Engineering at The University of Manchester's Mechanical and Aerospace Engineering department. His work focuses on orbital aerodynamics, spacecraft systems, and sustainable space technologies. He leads projects like the EU-funded DISCOVERER initiative, advancing Very Low Earth Orbit (VLEO) missions. Key achievements include the Icarus drag sail on TechDemoSat and the SOAR mission demonstrating drag-reducing materials. Roberts has secured grants from ESA, UKSA, and DARPA, coordinating large consortia. His research addresses space debris mitigation, aerodynamic materials, and atmospheric interactions. He advises on sustainable space practices, contributing to UN SDGs related to environmental protection. Notable awards include the 2022 Engineer's C2I Aerospace Award for DISCOVERER. Roberts collaborates internationally, including with Stuttgart University, and mentors over 15 postgraduate researchers. His labs and teams focus on experimental gas physics, spacecraft design, and VLEO mission systems.

• Internet of Things
• Machine Learning
• Cybersecurity
• +۳ مورد دیگر

Wahid Whaiduzzaman is a Research Professor at Torrens University Australia, affiliated with the Design and Creative Technology Centre for Artificial Intelligence Research and Optimisation (AIRO). He focuses on interdisciplinary research at the intersection of artificial intelligence, cybersecurity, and healthcare technologies. His work emphasizes AI-driven solutions for medical diagnostics, IoT-enabled systems, and renewable energy optimization. Research interests include machine learning applications in healthcare imaging (e.g., cancer detection, eye disease classification), cybersecurity for large language models, and anomaly prediction in solar photovoltaic systems. He actively collaborates on global research projects and is currently accepting PhD students. No scientific awards are explicitly listed in the provided information. His contributions span 59 peer-reviewed publications across journals like Future Internet, Sensors, and Computation, demonstrating expertise in both theoretical and applied AI domains.

• Micro-scale drug delivery
• 3-D printing of pharmaceuticals
• Microneedle transdermal systems
• +۴ مورد دیگر

Associate Professor Lifeng Kang is a pharmaceutical scientist at the University of Sydney School of Pharmacy , Faculty of Medicine and Health. He leads the Kang Lab which develops micro-scale and 3-D-printing technologies for drug delivery and regenerative medicine, and teaches undergraduate and postgraduate pharmacy courses. Education & career: BSc & MSc – China Pharmaceutical University (Nanjing, China) PhD – National University of Singapore (2006, drug delivery) Post-doctoral fellow – Massachusetts Institute of Technology (2007-2009, NUS-OPF Fellowship) Lecturer & Programme Director – National University of Singapore (2009-2017) Lecturer → Senior Lecturer → Associate Professor – University of Sydney (2017-present) Visiting Scholar – Stanford University (2019) Research focus: Microfabricated drug-delivery systems, 3-D printing of personalised medicines, dissolvable and hydrogel-forming microneedles, transdermal vaccination and cosmeceuticals, silk-fibroin and peptide biomaterials, organoid models for toxicology, and machine-learning-guided formulation design. Publications & impact: 86 peer-reviewed articles (65 first/corresponding), >4,600 citations, H-index 40, listed in Stanford/Elsevier global top-2 % scientists 2022-2024. Recent work appears in Nature Nanotechnology , Advanced Drug Delivery Reviews , Journal of Controlled Release , Analytical Chemistry and Biomaterials Advances . Innovation & translation: 10 patent families (5 granted, 3 licensed to industry); doctoral students have spun out two start-ups in 3-D-printed pharmaceuticals and microneedle devices. Current grants target osteoarthritis pain, skin depigmentation, paediatric IV stability and needle-free vaccination. Leadership & service: Vice-Chair (ANZ) Dissolution Research Presentation International 2023; 2nd-Year BPharm Coordinator; editorial boards of Advanced Drug Delivery Reviews , Frontiers in Pharmacology , Journal of Pharmacy and Pharmacology , Nano Convergence and others; reviewer for 40+ journals. Teaching & supervision: 14 years’ experience, primary supervisor of 15 PhD/MPhil students and >50 honours/project students; teaches drug delivery, formulation science and pharmaceutical analysis; research interest in mastery learning and formative assessment.

• Bayesian Search and Optimization
• Evolutionary Algorithms
• Multi-objective Optimization
• +۴ مورد دیگر

Dr Alma Rahat is an Associate Professor of Data Science at Swansea University, affiliated with the School of Mathematics and Computer Science. He specializes in Bayesian search and optimization, evolutionary algorithms, and multi-objective optimization. His work focuses on solving computationally expensive problems with applications in engineering, healthcare, and education. Education: BEng (Hons) in Electronic Engineering from the University of Southampton (UK), PhD in Computer Science from the University of Exeter (UK), and a Postgraduate Certificate in Teaching in Higher Education from Swansea University. He is a Fellow of the Higher Education Academy (FHEA). Research Interests: Dr Rahat’s expertise includes data-driven evolutionary optimization, surrogate-assisted methods, and active learning. He has contributed to pandemic response modeling for the Welsh Government and the UK Health Security Agency, leveraging machine learning and parameter optimization. His work on healthcare decision-making systems and educational assessment tools demonstrates a commitment to interdisciplinary applications of optimization. Key Contributions: He leads the Surrogate-Assisted Evolutionary Optimization (SAEOpt) workshop at GECCO and is a member of the IEEE Computational Intelligence Society Task Force on Data-Driven Optimization. His research bridges academic theory and industry needs, with patents and publications in top journals and conferences like IEEE Transactions and ACM. Grants: £750k from Welsh Government (Co-PI/Co-I), £230k EPSRC grant (EP/W01226X/1 as PI). Awards: Best Paper in Real-World Applications Track at GECCO, Patent for industrial fluid separation technology. Supervision: Currently guiding PhD students across AI, healthcare, education, and environmental modeling. His supervision emphasizes Bayesian methods and human-in-the-loop systems. Lab/Teams: Active in Swansea’s Computational Foundry, collaborating on projects like beach change forecasting and clinical decision support systems.

Hongjie Maمشاهده پروفایل

عضو هیئت علمی

• Artificial Intelligence
• Embedded Systems
• Operational Research
• +۷ مورد دیگر

Dr. Hongjie Ma is a Senior Research Fellow at the University of Portsmouth , affiliated with the School of Electrical and Mechanical Engineering and the Centre for Operational Research and Logistics . With over a decade of experience, his work bridges Artificial Intelligence and Embedded Systems , focusing on smart industrial applications and energy optimization. His research interests include: AI-based abnormal detection AI-based decision optimisation Embedded systems for machine learning Smart industrial sensors Operational Research Logistics Recent publications span combustion engineering , fuel cell technology , and autonomous driving frameworks . His work has garnered over 500 citations and includes contributions to REF 2021 impact case studies. Key scientific awards include the IEEE Leadership Award . He supervises PhD students and has secured grants from Innovate UK , EPSRC , and Horizon Europe . He chairs the IEEE Smart World Congress and serves as guest editor for journals like the Journal of Marine Science and Engineering .

• Structural Engineering
• Structural Dynamics
• Earthquake Engineering
• +۲ مورد دیگر

Nikos Nanos is a Senior Lecturer at the University of Portsmouth , affiliated with the School of Civil Engineering and Surveying within the Faculty of Technology. He holds a PhD in Earthquake Engineering and Structural Dynamics, an MSc in New Technologies in Antiseismic Engineering Design, and a BEng (Hons) in Civil Engineering. Research Focus: Structural Engineering, Earthquake Engineering, Soil Structure Interaction, and Optimisation Algorithms Expertise: Structural Dynamics, Seismic Assessment, and Construction Optimization His recent work explores low-cost MEMS sensors for environmental monitoring, modular construction with lean thinking, and post-disaster housing solutions. He supervises PhD students in seismic structural response, concrete behavior, and soil-structure interaction, leveraging advanced facilities like the Seismic Table testing bed and Heavy Structures Lab . Interdisciplinary collaborations span Computing, Business, and Engineering disciplines, emphasizing data agnostic methodologies and cross-disciplinary innovation . Key projects include structural health monitoring, seismic vulnerability assessments, and BIM-based parametric optimization. Students: Supervises research in seismic structural response, concrete behavior, and structural monitoring. Labs & Facilities: Oversees the University of Portsmouth's Seismic Table testing bed, Heavy Structures equipment, and in-house FEA capabilities.

Sinan Khwandahمشاهده پروفایل

مدرس

• Wireless Communications
• Renewable Energy Engineering
• 5G Networks
• +۶ مورد دیگر

Dr. Sinan Khwandah is a Lecturer in Electronic Engineering at Solent University, affiliated with the School of Engineering, Design and Manufacture. His research focuses on wireless communications, renewable energy systems, and 5G network optimization. He holds a PhD from Brunel University London (2015) and additional master’s degrees in Wireless Communication Systems (2011) and Automation (2009). Education: PhD: System Optimisation and Radio Planning for Future LTE-Advanced (Brunel University London, 2015) MSc: Wireless Communication Systems (Brunel University London, 2011) MSc: Automation and Computer Networks (Damascus University, 2009) Research interests include energy-efficient 5G architectures, AI-driven renewable energy systems, and interference management in heterogeneous networks. His work spans publications on MIMO systems, femtocell deployment, and network mobility optimization. He has contributed to collaborative research bids and international partnerships. Teaching focuses on wireless systems, electronic circuits, and renewable energy technologies, with involvement in curriculum development and inclusivity initiatives. He has served on program committees for IEEE conferences and reviewed publications for events like ICDMCIT-23.

• Civil Engineering
• Optimisation
• Applied Mathematics
• +۳ مورد دیگر

Aly-Joy Ulusoy is an Imperial College Research Fellow in the Department of Civil and Environmental Engineering at Imperial College London, affiliated with the Faculty of Engineering and the Grantham Institute. Her research focuses on optimisation methods for the design and control of water distribution networks, integrating adaptive systems, hydraulic modeling, and resilience analysis. She holds a Ph.D. (2021) and M.Sc. (2016) from Imperial College London, and an M.Sc. from École Supérieure d’Électricité, France (2016). Previously, she worked as a postdoctoral researcher in Dr. Ivan Stoianov's InfraSense Labs. Education: Ph.D. in Civil and Environmental Engineering, Imperial College London (2021) M.Sc. in Civil and Environmental Engineering, Imperial College London (2016) M.Sc., École Supérieure d’Électricité, France (2016) Her research interests span optimisation algorithms for water network control, adaptive hydraulic systems, data-driven hydraulic modeling, and resilient infrastructure design. Recent work emphasizes dynamically adaptive networks for pressure management, fault localization, and integration of AI for demand forecasting. She explores multi-objective optimization techniques to balance operational efficiency and resilience in water distribution systems. Key research trends include: (1) distributed optimization for real-time control under time-coupling constraints, (2) interpretable AI for water demand prediction, and (3) principled approaches for model maintenance using principal component analysis. Her work bridges theoretical optimisation with practical water infrastructure challenges. Advising and grants: No specific advisees or grants listed. Affiliated with InfraSense Labs, focusing on smart infrastructure and sensor networks. Active in developing methodologies for network resilience under uncertainty. Ongoing projects include adaptive MPC strategies for burst incident management and design-for-control frameworks for dynamically adaptive systems.

Sheng Chenمشاهده پروفایل

استاد

• Wireless Communication Systems
• Machine Learning for Signal Processing
• Underwater Robotics
• +۳ مورد دیگر

Professor Sheng Chen at the University of Southampton holds a prestigious academic rank in the Electronics and Computer Science department. His research interests span wireless communication systems, machine learning for signal processing, underwater robotics, and digital twin technology. IEEE Fellow Royal Academy of Engineering Fellow Chartered Engineer Research Focus: Professor Chen specializes in advanced wireless communication systems including MIMO technologies, channel estimation techniques, and next-generation 6G protocols. His work extends to industrial cybersecurity applications and underwater stereo matching algorithms. Recent Contributions: His latest publications demonstrate expertise in memristor-based signal processing circuits, label distribution learning using renormalization group theory, and innovative interference mitigation strategies in dynamic TDD systems. Current research projects: Optimising control system integrity (Royal Academy of Engineering), NEWCOM (European Union)

• Nonlinear Partial Differential Equations
• Geometric Analysis
• Riemannian Manifold Learning
• +۷ مورد دیگر

Vahideh Vahidifar is a Research Fellow in the Department of Mathematics at the University of Sussex's School of Mathematical and Physical Sciences, holding a Global Talent Endorsement from EPSRC/UKRI. Her academic journey includes a PhD from Iran University of Science and Technology (2018-2022) and a Research Associate position at Iran's National Elites Foundation (2020-2022). Her research spans the intersection of pure mathematics and applied computational fields, with core expertise in Nonlinear PDEs , Geometric Analysis , and Geometric Deep Learning . Key interests include Riemannian Manifold Learning, Graph Neural Networks, Calculus of Variations, and applications in Material Sciences. Her work connects abstract mathematical frameworks with practical robotics and AI systems. Analysis of her 12 recent publications (2021-2025) reveals a strong focus on gradient estimates for nonlinear parabolic/elliptic equations on metric measure spaces, with significant contributions to Ricci flow theory and geometric analysis. Parallel work applies mathematical principles to surgical robotics, particularly tremor detection and Leap Motion-controlled systems. Global Talent Endorsement by EPSRC/UKRI (2022) Vahidifar maintains active international collaborations across the UK, Canada, and USA. Her robotics research demonstrates practical translation of mathematical frameworks into medical device control systems, particularly in surgical robotics where she has developed novel approaches using Leap Motion sensors and Kalman filtering. Current work bridges geometric analysis with emerging AI architectures like Graph Neural Networks. She leads research in geometric foundations of machine learning while maintaining strong ties to mechanical engineering applications, particularly in smart materials and continuum mechanics. Her laboratory work integrates theoretical mathematics with physical robotics systems for surgical applications.

Peter Matherمشاهده پروفایل

مدرس ارشد

• Signal Processing
• Electronics Engineering
• Renewable Energy Systems
• +۶ مورد دیگر

Dr. Peter Mather is a Senior Lecturer in the Department of Engineering at the School of Computing and Engineering, University of Huddersfield. He leads the Complex Pathway program and is affiliated with the Centre for Efficiency and Performance Engineering and the Secure Societies Institute. His research spans analogue/digital electronics, sensor networks, and sustainable technology. PhD in 'Performance optimisation of VLSI circuits' (University of Huddersfield, 1995) MEng/BEng Electronics Course Leader since 2003 Research focuses on non-linear ADC development , partial discharge sensor networks , weapon detection , renewable energy systems , and optical coding via FPGA . His work contributes to UN SDGs for sustainable energy and security technologies. Recent publications analyze WLAN architectures, chaotic ADCs, and radiometric localization techniques. Scientific contributions include: 15+ publications in 2021 (3) and 2020 (2) with Scopus citations Expertise in wireless sensor networks, pulse position modulation, and visible light communication KTP award for radiation detection innovation (2018) He supervises PhD students in signal measurement and FPGA-based optical coding schemes, leveraging expertise in VHDL implementation and Sigma-Delta ADCs.

Alessandro Checcoمشاهده پروفایل

استادیار

• Crowdsourcing
• Human Computation
• Distributed Systems
• +۷ مورد دیگر

Alessandro Checco is an Assistant Professor in the Computer Science Department at University of Rome La Sapienza. His research focuses on crowdsourcing, distributed systems, and privacy-preserving technologies, bridging theoretical computer science with practical applications that consider human factors in technological systems. He has established himself as a significant contributor to the field of human computation and privacy-aware systems. His educational background includes: 2020: Fellowship of Higher Education from The University of Sheffield, Higher Education Academy 2015: Ph.D. in Mathematics from Hamilton Institute (Design of decentralised algorithms applied to channel/code selection and convex optimisation for throughput fairness of 802.11 networks) 2010: M.Sc. in Mathematical Engineering from University of Roma "Tor Vergata" (110/110 with great distinction) 2009: Erasmus Scholarship at Universiteit Gent, Department of Telecommunications 2007: B.Sc. in Mathematical Engineering from University of Roma "Tor Vergata" (110/110 with great distinction) Checco's research spans multiple areas at the intersection of computer science and social implications of technology. He is particularly interested in Crowdsourcing for Human Computation, Distributed Private Recommender Systems, Information Retrieval, Data Privacy, Distributed Systems, User Data Obfuscation in Web Systems, Societal and Economic Analysis of Online Work, Crowd Workers Unionisation, and Algorithmic Bias. His work often examines how technological systems can be designed to respect user privacy while maintaining functionality, and how crowd work can be structured to be more equitable for workers. His recent publications demonstrate a clear evolution in research focus, beginning with foundational work in wireless networks and distributed algorithms, then shifting toward human computation and privacy-preserving systems. His most recent work increasingly addresses the societal implications of crowd work, including investigations into crowd worker unionization and cooperative models. Several publications examine gender bias in algorithmic systems, reflecting growing attention to fairness and ethical considerations in his field. Among his notable achievements: All That Glitters is Gold-An Attack Scheme on Gold Questions in Crowdsourcing (Best Paper Award) Checco has secured significant research funding and led important projects including the H2020-funded FashionBrain project as Research Director and the EPSRC-funded BetterCrowd project as Research Associate. His work on the FashionBrain project demonstrates his ability to lead large-scale, interdisciplinary research initiatives. He has also received the Technology Innovation Development Award (TIDA) from Science Foundation Ireland. His research has practical applications across multiple domains including recommendation systems (BLC: Private Matrix Factorization Recommenders), peer review assistance using AI, smart farming technologies, and cooperative models for crowd workers (CrowdCO-OP). He has developed frameworks for understanding worker behavior in crowdsourcing platforms and created methods for improving quality control in human computation systems.

• Aerospace Engineering
• Flight Mechanics and Control
• Airworthiness and Certification
• +۶ مورد دیگر

Manuela Battipede is Associate Professor of Flight Mechanics & Control at the Politecnico di Torino , Department of Mechanical and Aerospace Engineering (DIMEAS). Since 2002 she has led research and teaching in aerospace guidance, airworthiness, neural-network-based virtual sensors, and trajectory optimisation, coordinating EU H2020 and Clean Sky projects, industrial airworthiness certification contracts, and supervising PhD students in aerospace engineering. Education & Academic Career Joined Politecnico di Torino as a confirmed Associate Professor (Prof.ssa Associata Confermata). Visiting Researcher, West Virginia University, USA (April–September 2002). Research Interests Her work integrates control theory , flight mechanics , and artificial-intelligence-based sensing to enhance safety and efficiency of air and space vehicles. Key themes include: 4-D trajectory optimisation for climate-neutral aviation. Certifiable virtual air-data systems using neural networks. Flutter suppression and intelligent flight control for fixed-wing and rotary-wing aircraft. Low-thrust orbital mechanics, collision avoidance, and end-of-life disposal for satellites. Lighter-than-air platforms and VTOL hybrid drones for earth-observation and fire-monitoring missions. Scientific Awards & Recognition PoCN – Proof of Concept Network (2015), AREA Science Park, Italy. Regular evaluator for SESAR Joint Undertaking, EU H2020, and European Commission programmes. Doctoral Advising & Funding Since 2011 she has served on the PhD board of the Aerospace Engineering doctorate at Politecnico di Torino, currently supervising: Giorgio Antonio Orlando (39th cycle, 2023–) Gabriele Tarascio (39th cycle, 2023–) She has been Scientific Director of >20 competitively funded projects (EU Clean Sky MIDAS, ESA, MIUR-PRIN, EASA certification contracts, etc.) and commercial consultancy contracts exceeding €3 M. Laboratories & Teams Battipede leads the Modelling, Simulation and Control of Aircraft research group at DIMEAS, managing real-time hardware-in-the-loop test rigs, CubeSat development platforms, and an integrated multi-aircraft simulation laboratory for education and industrial validation.