جست‌وجوی استاد و پژوهشگر

Fahad Ahmadمشاهده پروفایل

مدرس

• Machine Learning
• Cybersecurity
• Medical Informatics
• +۶ مورد دیگر

Fahad Ahmad is a Lecturer in the School of Computing within the Faculty of Technology at the University of Portsmouth. He holds affiliations with the Portsmouth AI and Data Science Centre, Centre for Cybercrime and Economic Crime, and Portsmouth Centre for Advanced Materials and Manufacturing. His research focuses on machine learning applications in healthcare, cybersecurity, and quantum computing. He supervises PhD students in topics like quantum machine learning for securing IoT medical devices. Key research areas include: Medical imaging diagnostics using deep learning (e.g., echocardiograms, X-rays) Cybersecurity for financial systems and SDN-NFV networks Quantum key distribution for post-quantum security AI-driven health management systems Recent work emphasizes: Human activity recognition through machine learning Cancer subtype classification using RNA expression data Emotional empathy modeling in intelligent agents His articles span healthcare technology, cybersecurity frameworks, and hybrid AI architectures. He actively contributes to international conferences and journals, with over 60 peer-reviewed publications. Research collaborations include institutions in Pakistan and the UK.

Nasser Kehtarnavazمشاهده پروفایل

استاد

• Signal and Image Processing
• Machine Learning
• Deep Learning
• +۴ مورد دیگر

Nasser Kehtarnavaz is an Erik Jonsson Distinguished Professor and Director of the Embedded Machine Learning (EML) Laboratory at the University of Texas at Dallas's Erik Jonsson School of Engineering and Computer Science. He holds a PhD from Rice University (1987) and has over 40 years of academic and industrial experience. His research focuses on signal/image processing, machine learning, biomedical applications, and real-time embedded systems. He has authored/co-authored 11 books and over 450 publications, and supervised 37 PhD and 35 MS students. Leadership roles: Editor-in-Chief of Journal of Real-Time Image Processing , SPIE Conference Chair, IEEE Fellow (2013), AAIA Fellow Industrial collaborations: Texas Instruments, AT&T Bell Labs, US Army TACOM Research Lab Key contributions: Smartphone-based signal processing labs, hearing aid amplification algorithms, and FPGA-based embedded systems Research interests include real-time implementation on embedded processors, biomedical signal analysis, and smartphone-based laboratories. He has pioneered educational tools like anywhere-anytime labs using smartphones for signal processing education. Recipient of numerous awards including IEEE Region 5 Professional Leadership Award (2015), Outstanding Engineering Educator Award (2013), and community recognition from SPIE (2020-2021). His funded projects (62 as PI/Co-PI) span healthcare tech, energy systems, and semiconductor manufacturing. Director of the EML Lab and previously the Signal and Image Processing Lab. Teaches graduate courses like Machine Learning and Pattern Recognition and undergraduate courses in signals and systems.

Rickey Dubayمشاهده پروفایل

استاد

• Control Systems
• Robotics
• Advanced Manufacturing
• +۲ مورد دیگر

Rickey Dubay is Professor and Director of Graduate Studies in Mechanical Engineering at University of New Brunswick. His research spans control systems, robotics, and advanced manufacturing, with particular focus on unmanned marine vehicles. Research areas include: complex control systems, robotic learning control, intelligent systems, and unmanned vehicle control. He leads projects on 3D trajectory tracking for marine vehicles and cognitive robotic strategies for autonomous systems. He has supervised 7 PhD and 23 Master's graduates, with 3 PhD and 4 Master's students currently. His research includes patented innovations in nonlinear control methodologies and complex profile tracking, and he co-founded Eigen Innovations Inc. Course instruction includes advanced topics: Model-based Control Methods, System Identification, and Optimal Control Methods.

Spitas Vasiliosمشاهده پروفایل

استاد

• Gear Dynamics
• Additive Manufacturing
• Mechanical Design Optimization
• +۷ مورد دیگر

Spitas Vasilios is a Professor at the National Technical University of Athens (NTUA), affiliated with the School of Mechanical Engineering and the Department of Mechanical Engineering & Automatic Control. His research focuses on gear dynamics, additive manufacturing, computational modeling, thermal systems, and educational pedagogy in engineering. He leads projects involving advanced gear technologies, material science applications, and sustainable energy systems. His work integrates experimental, analytical, and numerical methods to address challenges in mechanical design and industrial applications. Key research areas include optimizing gear performance through bio-inspired surface texturing, developing novel clutch systems, and enhancing 3D printing precision. He explores interdisciplinary topics like energy-efficient Ericsson engines and hyper-damping systems. His contributions to engineering education emphasize active learning strategies and project-based curricula. His recent publications analyze magnetic gear dynamics, additive-manufactured components, and educational innovations. He collaborates on international projects, such as the HEV Ventilator initiative, merging biomedical and mechanical engineering.

Vivek Ranadeمشاهده پروفایل

استاد

• Process Intensification
• Chemical Reactor Engineering
• Multiphase Flows
• +۶ مورد دیگر

Prof. Vivek Ranade is a Bernal Chair Professor of Process Engineering at the Bernal Institute, University of Limerick, and a Professor of Chemical Engineering at Queen's University Belfast. He leads research in multiphase reactors, process intensification, and sustainable energy/water technologies. His work spans applications in energy, water, and fine chemicals sectors, with contributions to industrial flow modeling, CFD, and digital twins. Education: B.Tech in Chemical Engineering (1983) and PhD (1988) from the Institute of Chemical Technology, Mumbai. Postdoctoral research at ETH Zurich (1988–1990). Served as Deputy Director at CSIR-National Chemical Laboratory (NCL) until 2016. Holds adjunct roles at the Institute of Chemical Technology and Academy of Scientific and Innovative Research. Research Interests: Multiphase flow dynamics, reactor engineering, process intensification, hydrodynamic cavitation, and sustainable technologies. Co-founded Tridiagonal Solutions and VIVIRA Process Technologies to commercialize innovations. Awards: Shanti Swarup Bhatnagar Prize (2004), Swarnajayanti Fellowship, Fellowships from IChemE, Indian National Science Academy, and multiple academies. Advising: Guided over 20 PhD students; involved in industrial collaborations and start-ups. Labs/Teams: Leads the Multiphase Reactors group at UL and QUB, and collaborates on projects like the MAGIC initiative for specialty chemicals.

Leif Nilssonمشاهده پروفایل

دانشیار

• Statistical Learning
• Defect Detection
• Occupational Health
• +۵ مورد دیگر

Leif Nilsson is an Associate Professor at the Department of Mathematics and Mathematical Statistics, Umeå University. His research focuses on statistical learning methods for industrial quality control and occupational health risk assessment. Statistical learning for defect detection Exposure modeling for occupational hazards Biostatistical analysis of health outcomes Recent work applies probabilistic classifiers and spline smoothers to automate surface finish inspection. He also investigates exposure variability in hand-arm vibration and its health impacts through epidemiological studies. Nilsson collaborates with clinical teams on stress recovery interventions and contributes to methodological developments in biological monitoring. His statistical expertise spans Bayesian modeling, resampling techniques, and spatio-temporal data analysis.

Ammar Al-Baziمشاهده پروفایل

دانشیار

• Operations Research
• Supply Chain Management
• Simulation and Optimization
• +۳ مورد دیگر

Dr. Ammar Al-Bazi is an Associate Professor in Operations and Supply Chain Simulation at Aston Business School, part of the College of Business and Social Sciences at Aston University. He holds a PhD in Simulation and Optimization from Teesside University and an MSc in Statistics and Operational Research from the University of Baghdad. He is a Senior Fellow of the Higher Education Academy (SFHEA) and has led multiple funded projects, including those supported by Innovate UK and the European Regional Development Fund (ERDF). His research focuses on applying simulation, optimization, AI, and digital technologies to solve real-world challenges in logistics, energy, and manufacturing. Education: PhD in Simulation and Optimization, Teesside University (UK) MSc in Statistics and Operational Research, University of Baghdad (Iraq) BSc (Honors) in Operational Research, Al-Mansour College University (Iraq) Research Interests: Simulation and optimization techniques for supply chain management Energy efficiency and demand-side management Transportation and logistics optimization (including drones) Artificial Intelligence applications in manufacturing and healthcare Risk mitigation and disruption management in operations Recent Article Trends: Dr. Al-Bazi's recent work emphasizes digital twin technology, IoT integration in energy systems, and resilience in supply chains. His studies often combine machine learning with traditional optimization methods to address challenges like emissions prediction, consumer behavior modeling, and pandemic logistics. Awards and Roles: Senior Fellow of the Higher Education Academy (SFHEA) External Examiner for PhD programs at multiple universities Editorial board member of journals like Supply Chain Analytics and Journal of Information and Communication Technology Grants and Funding: £39,751 (Innovate UK) for dynamic railway contaminant control barriers £202,308 (KTP, Innovate UK) for collaboration with The Birmingham Assay Office Multiple KEEN and KTP projects focusing on SME performance improvement Advisory and Teaching: He supervises PhD students on topics like behavioral decision-making in healthcare logistics and renewable energy integration. He teaches courses in operations management, simulation for project management, and business analytics.

Mudassir M. Rashidمشاهده پروفایل

استادیار

• Process Control
• Biomedical Engineering
• Pharmaceutical Engineering
• +۲ مورد دیگر

Mudassir M. Rashid serves as Assistant Professor of Chemical Engineering and Director of the Pharmaceutical Engineering Program at Illinois Institute of Technology's Armour College of Engineering. His work bridges chemical engineering fundamentals with cutting-edge applications in biomedical systems and pharmaceutical manufacturing. His academic credentials include: Ph.D. in Chemical Engineering from McMaster University, Hamilton, Canada (2016) B.Eng. in Chemical Engineering from McMaster University, Hamilton, Canada (2011) Dr. Rashid's research program centers on three interconnected domains: Data-driven modeling and control for biological/chemical systems, specializing in recursive identification and adaptive control of nonlinear time-varying processes with variable delays Diabetes technology development through metabolic modeling, simulation of physiological pathways, and automated closed-loop insulin delivery systems Pharmaceutical manufacturing innovation via process analytical technology for real-time monitoring, control, and optimization of drug production quality attributes His methodology integrates advanced control theory with practical healthcare and industrial applications, demonstrating particular expertise in artificial pancreas systems and pharmaceutical process optimization. Analysis of his 15 most recent publications (2016-2019) reveals a dominant research trajectory in adaptive control systems for diabetes management, constituting over 80% of his output. Key themes include glucose prediction algorithms, plasma insulin estimation techniques, and disturbance-handling strategies for meals/exercise within artificial pancreas frameworks. The remaining publications address economic model predictive control applications in chemical batch processes and metallurgical systems, showcasing methodological versatility across biomedical and industrial contexts. No scientific awards are documented in the provided materials. While specific advising activities and grant funding details are absent from the source text, his leadership of the Pharmaceutical Engineering Program indicates significant academic administrative responsibilities. Dr. Rashid directs the Pharmaceutical Engineering Program at Illinois Tech, though the source material does not specify dedicated laboratory facilities or research team structures beyond his program oversight role.

• Health Informatics
• Fraud Detection
• Cybersecurity
• +۶ مورد دیگر

Dr. Fletcher Lu is an Associate Professor in the Department of Information Technology at the Faculty of Business and Information Technology, Ontario Tech University. His academic journey includes a PhD in Artificial Intelligence (specializing in Machine Learning) and a Master of Mathematics in Scientific Computation, both from the University of Waterloo. He also holds a Bachelor of Math in Computer Science from the same institution. His postdoctoral research at the Canadian Institute of Chartered Accountants (CIAC) focused on insurance fraud detection. His education includes: PhD in Artificial Intelligence, University of Waterloo Master of Mathematics in Scientific Computation, University of Waterloo Bachelor of Math in Computer Science, University of Waterloo Dr. Lu’s research interests span health informatics, fraud detection (including cybercrime and insurance fraud), and the application of machine learning and numerical analysis to business and health challenges. He has developed mobile technology applications to improve youth fitness and pioneered adaptive fraud pattern analysis in health insurance data. His work intersects with cybersecurity, data analytics, and gaming, emphasizing real-world collaborations with organizations such as Manulife Financial, the Canadian Department of National Defence, and Medavie Blue Cross. His recent publications highlight trends in supply chain resilience, optimization methodologies, and disruption risk analysis. These include studies on EV infrastructure planning, stochastic distribution networks, and Benders decomposition strategies for reliable systems design. Dr. Lu has received significant awards, including: First place at CORS 2014 Practice Prize Third place at INFORMS 2013 interactive poster sessions His research has been funded by the National Science Foundation, Ontario Partnership for Innovation and Commercialization, and NSERC. He is affiliated with the Business Analytics & AI Research Group, contributing to decision-making systems and data-driven solutions for business and health sectors.

• Environmental Biotechnology
• Wastewater Treatment Processes
• Quantum Computing Applications
• +۶ مورد دیگر

Po-Heng (Henry) Lee is an Associate Professor in the Department of Civil and Environmental Engineering at Imperial College London, part of the Faculty of Engineering. His research focuses on wastewater engineering, environmental biotechnology, and quantum computing applications in microbial systems. He leads the Industrial Biotechnology Hub, Microbiome Network, and Quantum Engineering, Science and Technology initiatives. Dr. Lee holds a PhD from Iowa State University (2010) and earlier degrees from institutions in Taiwan. His academic career includes roles at Hong Kong Polytechnic University (2012-2018) and Inha University (2010-2012) before joining Imperial College in 2019. His research integrates quantum information theory with environmental engineering, exploring electron transfer mechanisms, anaerobic digestion optimization, and water reuse in AI/semiconductor contexts. Techniques include quantum computing platforms (IBM Qiskit, Xanadu), meta-omics, and Gaussian Bosonic Sampling. Key application areas include enhancing antibiotic and nitrogen removal via microbiome-conductive material interactions, smart chemical dosing for industrial cooling systems, and optimizing full-scale wastewater plants. His work bridges quantum mechanics and microbial ecology to address sustainability challenges. Dr. Lee's lab develops innovative solutions for resource recovery, greenhouse gas reduction, and bioplastic production. Major collaborations focus on AI-driven process control and semiconductor manufacturing wastewater treatment.

Xiaochun Liمشاهده پروفایل

استاد

• Scifacturing (science-driven manufacturing)
• Nanotechnology Enabled Metallurgy
• Scalable Nanomanufacturing
• +۲ مورد دیگر

Xiaochun Li is a Professor at the Department of Mechanical and Aerospace Engineering within the College of Engineering at the University of California, Los Angeles. Holding the Raytheon Endowed Professorship in Manufacturing Engineering, his work bridges materials science and advanced manufacturing technologies. Education: PhD (Mechanical Engineering, Stanford University, 2001), MS (Industrial, System and Welding Engineering, Ohio State University, 1997), BS (Mechanical Engineering and Applied Physics, Tsinghua University, 1992) Research Focus: Dr. Li specializes in science-driven manufacturing (scifacturing), leveraging nanotechnology to revolutionize metallurgy and scalable nanomanufacturing. His work explores smart manufacturing systems, additive manufacturing techniques, and nanoparticle-enabled phase control to overcome traditional material processing limitations. Publication Trends: His research spans nanoparticle integration in metals, fusion-based manufacturing innovations, and sensor-embedded process monitoring. Topics include unconventional welding methods, solidification control, composite synthesis, and thermal behavior analysis, reflecting interdisciplinary expertise in materials science, mechanical engineering, and nanotechnology. Scientific Recognition: Awards include the prestigious SME Frederick W. Taylor Research Medal (2025), ASME William T. Ennor Manufacturing Technology Award (2022), and Fellowships from ASME, SME, and the International Society of Nanomanufacturing. His NSF CAREER Award (2002) and multiple AFS honors highlight early-career impact. Laboratory: Dr. Li leads the Scifacturing Laboratory , which develops science-driven manufacturing solutions that address critical challenges in materials processing and industrial scalability.

Riku Ala-Laurinahoمشاهده پروفایل

پژوهشگر

• Digital Twin
• Cyber-Physical Systems
• Industrial Automation
• +۳ مورد دیگر

Riku Ala-Laurinaho is a Researcher at Aalto University's Department of Energy and Mechanical Engineering, with a focus on Digital Twin technologies and Industrial Automation. He holds a Master's (2019) and Bachelor's (2018) in Engineering and Technology from Aalto University. His research interests span Digital Twins in industrial contexts, Cyber-Physical Systems, IoT applications, and data-centric systems. He explores semantic-enhanced industrial metaverse frameworks and collaborative design paradigms. Recent work emphasizes context-aware systems, torsional vibration analysis tools, and Human-Centric Manufacturing processes. His publications (16+), including high-impact articles in Journal of Manufacturing Systems and SoftwareX , reflect a focus on industrial innovation. METEX award (2020) Contributions to 5+ open-source datasets (e.g., OpenTorsion, A!ex autonomous car dataset) His advising includes 1 supervised thesis, with grant details pending.

Eddie Ballمشاهده پروفایل

استاد

• RF Engineering
• Wireless Systems Design
• Millimeter-Wave Communications
• +۵ مورد دیگر

Professor Eddie Ball is a Professor of Radio Frequency Engineering at the University of Sheffield's School of Electrical and Electronic Engineering, and a UKRI Future Leaders Fellow (2021-2028). He leads the Electromagnetics, Wireless Hardware & RF Devices research theme and directs the EPSRC Millimetre Wave Measurement Laboratory. His expertise spans RF circuit/system design, SDR, and millimeter-wave technologies, with a focus on IoT applications and hardware manufacturing. Qualifications: Ph.D., University of Sheffield (2024) M.Eng (1st class), University of York (1996) Chartered Engineer Research Interests: Novel RF circuit/system design Millimeter-wave transceivers and antennas RF-MMIC and SiGe design IoT radio systems and blockchain integration Low-cost, high-performance wireless protocols Teaching: Creator and instructor for EEE6239: Radio Transceiver System & Circuit Design 2nd-year course leader for VHF Synthesiser for Wireless Communications Labs/Teams: EPSRC Millimetre Wave Measurement Laboratory Future Millimetre Wave RF Transceiver Architectures Project

• Computer Modelling and Simulation
• Operations Management
• Supply Chain Management
• +۳ مورد دیگر

Dr. Terrence Perera is a Teaching Professor in the Operations Management and Decision Sciences (OMDS) department at the University of Sheffield's Management School. With over 30 years of experience in teaching, research, and consultancy, he specializes in computer modeling/simulation, operations management, and supply chain management. He leads modules such as 'The Intelligent Organisation,' 'Internationalisation Challenge,' and 'Business Intelligence' in undergraduate and MBA programs. His work integrating Qlik into teaching earned him the 2025 Qlik Education Ambassador title, while his Internationalisation Challenge module was shortlisted for a postgraduate employability award by AGCAS. Education: BSc and PhD qualifications. Research Interests: Focus on Industry 4.0 integration, simulation in healthcare (e.g., neonatal unit analysis), supply chain data management, and sustainability initiatives. He has secured five EPSRC grants and managed Knowledge Transfer Partnership projects with firms like BAE Systems and Siemens. Professional Recognition: Recipient of the 2025 Qlik Education Ambassador award and AGCAS shortlist. His consultancy spans sectors including healthcare, manufacturing, and logistics. Teaching & Advising: Supervises student dissertations, develops case studies from industry collaboration. His modules emphasize real-world applications of analytics and modern technologies. Grants & Projects: Five EPSRC grants, multiple KTP projects focused on manufacturing systems and ERP. Collaborations include Sheffield Children’s Hospital and Fosters Bakery.

Wenbin Liمشاهده پروفایل

مدرس ارشد

• Robotics
• Computer Vision
• Machine Learning
• +۴ مورد دیگر

Dr. Wenbin Li is a Senior Lecturer (Associate Professor) in Robotics at the University of Bath's Department of Computer Science. He leads the Pering Laboratory (Perceptual Intelligence Laboratory), affiliated with the AI & Machine Learning and Visual Computing groups. Previously, he held postdoctoral positions at Imperial College London (2016-2018) and UCL (2014-2016), and earned his PhD from the University of Bath in 2013, with earlier degrees from Imperial College London (MSc, 2009) and Xidian University (B.Eng, 2008). His research focuses on unified autonomous systems, including multi-sensory localization/mapping, dynamic motion capture, and uncontrolled scene understanding with applications in manufacturing and professional capture. Key areas include Robotics, Computer Vision, Graphics, and Machine Learning. He actively supervises doctoral students in these fields and has funded PhD openings. Dr. Li has been involved in major initiatives such as the My World - Strength in Places Fund (2021–2027), SLAM with Reinforcement Learning (2022–2023), and the CAMERA MC2 Award (2019–2023). His work aligns with UN Sustainable Development Goals, particularly in advancing technology for societal benefit. Recent publications emphasize aerial robotics, autonomous systems, and computer vision applications, including UAV package delivery reviews, Bayesian optimization for balloon station-keeping, and generative models for intrinsic image decomposition.