جست‌وجوی استاد و پژوهشگر

Elhadj Benkhelifaمشاهده پروفایل

استاد

• Cloud/Edge Computing
• Bio-Inspired Computing
• Cybersecurity
• +۷ مورد دیگر

Elhadj Benkhelifa is a full Professor of Computer Science and Digital Innovations at Staffordshire University, leading the Head of Professoriate role to advance university strategies. He founded the Smart Systems, AI and Cybersecurity Research Centre (SSAICS), directing 15 staff and 23 PhD students. Previously, he held roles at Cranfield University and the University of the West of England. His interdisciplinary research focuses on cybersecurity, cloud/edge computing, bio-inspired systems, and AI applications in healthcare and digital transformation. He is a Visiting Professor at Universities of Suffolk, Lyon3, and Paris 8, and chairs the IEEE UK&I Section's Education & STEM office. Education includes a PhD in Artificial-Life (Bio Inspired Evolvable and Self-Healing Systems) from UWE Bristol Robotics Lab, alongside postgraduate certifications in research supervision and higher education. His work bridges academia and industry, addressing challenges in cybersecurity, IoT, and healthcare through applied research. Research interests span cloud computing paradigms, semantic technologies, and AI ethics, with over 150 publications. His recent articles emphasize AI-driven cybersecurity solutions, quantum computing applications, and medical diagnostics using deep learning. He actively contributes to open-access publishing and advises on national cybersecurity strategies. Awarded Fellow of the UK Higher Education Academy, he leads impactful projects including malware detection systems, semantic knowledge graphs for public health, and blockchain-based authentication frameworks. His teaching spans undergraduate to PhD levels, with over 100 supervised projects. He also serves on advisory boards for cybersecurity initiatives and Staffordshire Police's evidence-based practices.

Mohamed Sedkyمشاهده پروفایل

استاد

• Computer Vision
• Video Analytics
• Cyber-Physical Systems
• +۴ مورد دیگر

Professor Mohamed Sedky holds the position of Professor of Cyber-Physical Systems at Staffordshire University. He previously founded SKM Communication Systems and served as a lecturer at the Arab Academy for Science and Technology before joining Staffordshire in 2003. His roles include MSc Computer Science Deputy Award Leader and BSc Internet of Things Award Leader. He leads research at AVA Technologies Ltd, focusing on real-time video analytics algorithms such as Spectral-360®, which addresses security, safety, and business intelligence applications. His patented work in object detection and change detection has been globally recognized. He teaches modules like Fundamentals of Computer Networks and Router Security Technologies. Education: BEng (Hons) Electro-Physics and Communications, Alexandria University (1996) MSc Communications and Electronics, Arab Academy for Science and Technology (2002) PhD Computer Vision, Staffordshire University (2009) PGC Research Supervision, Staffordshire University PGC Higher and Professional Education, Staffordshire University Research Interests: Object recognition/segmentation Video surveillance systems IoT forensic processes AI in healthcare and smart environments Commercial Ventures: Founder of Spectral-360® technology Lead Researcher at AVA Technologies Ltd Consultant for Serco, Centralweighing, and WMTN Labs & Projects: Developed AVA Technologies' Detect/Protect/Count/Summarise solutions Designed OpenSHS (Open Smart Home Simulator) Conducted feasibility studies for buried utility detection and industrial inspection His research bridges academia and industry through patented innovations in video analytics and IoT systems, addressing challenges in security, healthcare, and smart infrastructure.

• Database Information Management
• Big Data Management Systems
• Data Structures
• +۳ مورد دیگر

John Tsaknakis is an Associate Professor at the Department of Electrical and Computer Engineering, School of Engineering, University of Peloponnese. He holds a PhD in Computational Geometry and Multidimensional Data Structures from the University of Patras (2004), following a diploma in Computer Engineering and Informatics (1996). His research focuses on Information Management in Databases, Big Data Systems, Data Structures, and Knowledge Mining in Web-based contexts. Since 2004, he has contributed to numerous research and development projects, particularly in software systems and data management. His work spans theoretical advancements and practical applications, including AI-driven labor market analysis, energy demand forecasting, and interoperable social protection frameworks. Research interests include database optimization, computational geometry, and leveraging big data for societal challenges. His publications reflect a blend of technical innovation and real-world problem-solving, with recent work addressing pandemic impacts on employment and AI’s role in reducing gender disparities. He is accessible in Building K on Mondays and Tuesdays, 8:00–9:00 AM, though prior arrangement is recommended. Dr. Tsaknakis collaborates on international projects, such as World Bank initiatives in social protection systems, and maintains active involvement in academic administration and teaching. His contributions to the field are further highlighted through his curriculum vitae and ongoing engagement in the academic community.

Ramana Pidapartiمشاهده پروفایل

استاد

• Multidisciplinary Design Innovation
• Computational Biomechanics
• Design Informatics
• +۱ مورد دیگر

Ramana Pidaparti is a Professor at the University of Georgia's College of Engineering, specializing in multidisciplinary design innovation, computational biomechanics, design informatics, and STEM education. He earned his Ph.D. in Aeronautics & Astronautics from Purdue University and employs project-based, collaborative, and experiential teaching strategies. His professional affiliations include fellowships with the American Association for the Advancement of Science, Royal Aeronautical Society, American Society of Mechanical Engineers, and American Institute of Aeronautics and Astronautics. Research interests span: Multidisciplinary design optimization Computational modeling of biological systems Educational technology integration in STEM Bio-inspired engineering solutions Recent publications (2023-2025) focus on AI applications in robotics, biomechanics, and middle-school education, with emphasis on knowledge-transfer frameworks, biomaterial characterization, and 3D learning modules. Awards recognize contributions to aerospace and mechanical engineering sciences.

• Machine Learning
• Image Processing
• Artificial Intelligence
• +۱۲ مورد دیگر

Dr. Zhong Hu is a Professor in the Department of Mechanical Engineering at South Dakota State University. He holds a Ph.D. and B.S. in Mechanical Engineering from Tsinghua University, China. Ph.D. in Mechanical Engineering | Tsinghua University, Beijing, China B.S. in Mechanical Engineering | Tsinghua University, Beijing, China His research spans diverse areas including machine learning/image processing applications in materials science, multiscale material modeling (quantum mechanics to finite element analysis), composite/nanocomposite design, materials characterization, mechanical strength evaluation, and optimization of metal forming and autofrettage processes. Recent publications focus on molecular dynamics simulations for thermal/mechanical properties of nanocomposites, machine learning-driven LiDAR classification, and finite element analysis of pressure vessels. Collaborative work also addresses graduate education strategies and sustainable materials research. 2025: CNT-epoxy thermal conductivity simulations 2025: Machine learning for LiDAR-based tree classification 2024: Swage autofrettage stress analysis 2024: Bio-inspired protein-derived composites 2023: Biomimetic lattice structure optimization He serves on professional committees and is affiliated with organizations like ASME and Materials Research Society. His lab, the Materials Evaluation and Testing Lab, emphasizes computational/experimental synergy in material design.

KHOO Boo Cheongمشاهده پروفایل

استاد

• Fluid Mechanics
• Computational Fluid Dynamics
• Numerical Methods
• +۷ مورد دیگر

Professor KHOO Boo Cheong is a faculty member in the Department of Mechanical Engineering at the National University of Singapore (NUS), affiliated with the College of Design and Engineering. He holds a BA (Hons.) from the University of Cambridge (1980), an MEng from NUS (1984), and a PhD from MIT (1989). His research focuses on Computational Fluid Dynamics (CFD) , Numerical Methods , and Fluid Mechanics , with applications to aerodynamics, turbulence, and fluid-structure interaction. Recent work emphasizes machine learning integration in CFD, bio-inspired UAV design, and icing mechanics for aerospace systems. Key research trends include advancing high-fidelity simulations for complex flows (e.g., turbulence modeling, cavitation suppression), optimizing fluid-structure systems (e.g., lightweight shells, train aerodynamics), and developing novel experimental techniques (e.g., light field PIV, wind spectra analysis). His contributions bridge theoretical CFD innovations with practical engineering challenges in transportation, renewable energy, and robotics. Professor Khoo collaborates on projects involving pressure gain combustion systems , ventilated supercavitating models , and quantum algorithms for fluid dynamics . His lab’s work often combines advanced numerical modeling with experimental validation, addressing real-world issues like wind effects on trains, ice accretion on airfoils, and autonomous navigation systems.

Tim Andersenمشاهده پروفایل

استاد

• Computer Science
• Bioinformatics
• Data Storage
• +۷ مورد دیگر

Tim Andersen is a Professor in the Computer Science Department at Boise State University. He holds a Ph.D. in Computer Science from Brigham Young University (1999) and previously worked as Chief Scientist at IArchives, developing OCR and image processing algorithms. His research focuses on interdisciplinary areas including nucleic acid-based data storage, blockchain applications in AI, machine learning optimization, and bio-inspired computational models. Education : Ph.D. in Computer Science, Brigham Young University, 1999 Research Interests : Dr. Andersen’s work spans molecular data storage (e.g., DNA-based memory systems), computational security protocols leveraging blockchain, optimization of neural network training, and bioinformatics applications such as probe design and protein docking. He pioneered methods for encoding digital information in nucleic acids and developed algorithms for enhancing AI model trustworthiness through decentralized verification. Publications Trends : Recent work emphasizes nucleic acid memory optimization (2023–2025), blockchain integration in AI security (2023–2024), and legacy contributions to OCR algorithms and evolutionary computation (1995–2000s). His research often bridges computer science with molecular biology, addressing both theoretical and applied challenges in emerging technologies. Awards & Grants : Not explicitly listed in available texts, but his sustained contributions across multiple disciplines suggest substantial external funding and recognition in interdisciplinary computing. Advising & Curriculum Development : Co-developed the “Computer Science Professionals’ Hatchery” program, integrating inclusion/diversity initiatives into Boise State’s curriculum. Focus on preparing high-school teachers in computer science through sustainable models like IDoCode. Labs & Collaborations : Associated with Boise State’s computational biology and AI security research groups. Collaborates across disciplines to advance nucleic acid storage and blockchain-audited systems.

Zahra Derakhshandehمشاهده پروفایل

دانشیار

• Distributed Computing
• Algorithm Design and Optimization
• Bio-inspired Algorithms
• +۵ مورد دیگر

Zahra Derakhshandeh is an Associate Professor in the Department of Computer Science at California State University East Bay. She holds a Ph.D. in Computer Science from Arizona State University (2017), where she worked under Professors Andrea W. Richa and Christian Scheideler. Her research focuses on distributed computing, algorithm design, bio-inspired algorithms, programmable matter, and self-organizing particle systems. Notably, her work on 'Smart Paint' for universal coating problems has received media attention from MIT Tech Review and ACM TechNews. Dr. Derakhshandeh has extensive teaching experience, including instructing courses like Foundations of Algorithms (CSE 551) at Arizona State University and serving as a faculty member at multiple institutions in Iran. Her industrial experience includes roles as a software developer at eBay/PayPal and research positions in network security and data center projects. Her research trends span theoretical computing (programmable matter, self-organization) and educational technology (online learning dynamics, active learning strategies). Recent publications explore federated learning, student engagement in online environments, and interaction design in digital education systems. Dr. Derakhshandeh’s work emphasizes cross-disciplinary applications, bridging computer science theory with real-world systems like financial eligibility services and telecommunication infrastructure.

• Optimization
• Data Mining
• Machine Learning
• +۹ مورد دیگر

Ehsan Atefi is an Associate Professor in Mechanical Engineering at Manhattan University. He holds a Ph.D. from The University of Akron and a postdoctoral fellowship from The University of Pennsylvania. His research focuses on bio-inspired machine learning, optimization algorithms, and their applications in bio-medicine and sustainability. He has published over 20 peer-reviewed articles, including works in prestigious journals like Physical Review Letters and Advanced Functional Materials , with an h-index of 11. Dr. Atefi has secured grants from NREL, ACS Petroleum, and the Jasper Summer program. Education: Ph.D., The University of Akron Postdoctoral Fellowship, The University of Pennsylvania Research Interests: Optimization and Data Mining Sustainability and Energy Management Surface Characterization and Interfacial Tension Drug Deposition in Lung Airways Bio-inspired Algorithms Key Awards: ACS Petroleum Research Fund Collegiate Wind Competition (NREL) Jasper Summer Fellowship Grants & Advising: Directed over 20 graduate student projects Secured funding from NREL, ACS Petroleum, and Jasper Summer Supervised students in national competitions His research lab develops novel methods for tumor spheroid engineering and drug testing using aqueous two-phase systems, with applications in biomedical and materials science.

Zhiyuan Yanمشاهده پروفایل

استاد

• Coding Theory
• Wireless Communications
• VLSI Design
• +۴ مورد دیگر

Zhiyuan Yan is a Professor and Associate Chair in the Department of Electrical and Computer Engineering at Lehigh University. He holds a B.E. from Tsinghua University and M.S./Ph.D. degrees from the University of Illinois at Urbana-Champaign. His research focuses on coding theory, VLSI design, wireless communications, and embedded systems. He is a Senior Member of the IEEE and received the NSF CAREER Award in 2011. Educational Background: B.E., Electrical Engineering, Tsinghua University M.S., Electrical Engineering, University of Illinois at Urbana-Champaign Ph.D., Electrical Engineering, University of Illinois at Urbana-Champaign Research Interests: His work spans coding theory (including polar codes and LDPC codes), VLSI implementations for communication systems, and cybersecurity through physical unclonable functions (PUF). He explores neuromorphic computing, memristive neural networks, and hardware-efficient error correction techniques. His contributions include efficient decoder architectures and distributed storage solutions. Scientific Awards: 2011: NSF CAREER Award Advising & Grants: While specific student names aren't listed, his research has been supported by multiple grants. His lab focuses on collaborative projects between academia and industry, emphasizing practical implementations of theoretical advancements. Lab & Teams: His research team develops cutting-edge VLSI systems, neural network accelerators, and secure communication protocols. Collaborations include work on memristive hardware and neuromorphic computing architectures.

• Computational Biology
• Computational Science
• Monte Carlo Methods
• +۵ مورد دیگر

Yaohang Li is a Professor in the Department of Computer Science at Old Dominion University (ODU), part of the College of Sciences. His research focuses on computational biology, computational science, Monte Carlo methods, and high-performance computing. He holds a Ph.D. in Computer Science from Florida State University (2003), an M.S. from Florida State (2000), and a B.S. from South China University of Technology (1997). Dr. Li has secured over $15M in research funding, including an NSF CAREER Award (2009) and multiple federal/state grants. His work spans protein structure modeling, bio-inspired algorithms, and parallel computing. Notable contributions include novel sampling approaches for protein modeling and GPU-accelerated optimization methods. He has authored/co-authored numerous peer-reviewed articles in journals like Journal of Computational Biology , IEEE Transactions , and Physical Review . Key Research Areas: Protein Loop Prediction, Parallel Tempering Algorithms, Grid Computing Security Grants: Includes $13.5M NOAA ISET Cooperative Center and $1M NSF Bio-inspired Control Systems Project Awards: 2009 NSF CAREER Award, 2005 Young Researcher Award (NCSU), and 2005 Ralph E. Powe Junior Faculty Enhancement Award. His lab collaborates on interdisciplinary projects such as the Consortium for Research Computing for Sciences (CRCSET) and develops tools like the Variational Autoencoder Inverse Mapper (VAIM) for QCD analysis. Advises on HPC systems and security in distributed computing environments.

• Fluid Mechanics
• Maritime Engineering
• Classical Physics
• +۳ مورد دیگر

Prof. Justin Leontini is a Professor in the Department of Mechanical and Product Design Engineering at Swinburne University of Technology, within the School of Engineering. He holds a PhD from Monash University and completed postdoctoral fellowships at the Centre National de la Recherche Scientifique (France), CSIRO, and Monash as an Australian Postdoctoral Fellow (2011). His research focuses on fluid dynamics, supercomputing simulations, and oscillatory flow applications in ocean energy, biomedical systems, and aerospace composites. Research interests include wave energy converters, high-frequency ventilation gas transport, fluid-structure interactions, and turbulence modeling. He collaborates with institutions like Murdoch Children's Research Institute, 4DMedicalR&D, and Boeing. His work addresses societal challenges such as coastal protection, renewable energy, and lung-protective ventilation protocols. Education: PhD (Monash University) Awards: Australian Postdoctoral Fellowship (2011, ARC) Grants: Over 15 grants, including ARC and industry partnerships on biofilm research, wave energy arrays, and coastal engineering. Teaching: Supervised 17 PhD students in areas like fluid dynamics, composite materials, and renewable energy systems. Prof. Leontini is a member of the Australasian Fluid Mechanics Society and actively contributes to interdisciplinary research, bridging engineering, medicine, and environmental science.

• Neuromorphic Engineering
• Computational Neuroscience
• Brain-Inspired Computing
• +۲ مورد دیگر

Alessio Franci is Lecturer in Electrical Engineering and Computer Science at the University of Liege, where he co-founded the ULiege Neuroengineering Lab. His research bridges mathematics, neuroscience and engineering through brain-inspired computing paradigms. Funded by a WEL-T Starting Grant, his work develops neuromorphic controllers and biomorphic systems for robotics and intelligent sensing. Research explores: neurocomputational principles of decision-making; neuromodulation in adaptive systems; and degenerate coding in neural circuits. Publications apply nonlinear dynamics to opinion formation, neural coding, and neuromorphic hardware design, demonstrating consistent innovation in theoretical frameworks. Honors include the WEL-T Starting Grant supporting his investigations into neuronal degeneracy and physiological mechanisms. Current work emphasizes real-world applications in robotics through spiking neural controllers and embodied neuromodulation strategies.

Susmita Naskarمشاهده پروفایل

مدرس

• Mechanics of Metamaterials
• Deployable and Reconfigurable Structures
• Uncertainty Quantification
• +۲ مورد دیگر

Dr. Susmita Naskar is a Lecturer in the Faculty of Engineering & Physical Sciences at the University of Southampton. Her research focuses on multi-scale structural mechanics, advanced composites, and metamaterials, integrating additive manufacturing and computational design. She holds a doctoral degree from the University of Aberdeen, followed by postdoctoral research at Johns Hopkins University (USA) and visiting studies at the University of Oxford. Her work emphasizes sustainable materials for aerospace applications and machine learning-driven structural analysis. Dr. Naskar’s research interests include mechanics of metamaterials, deployable structures, uncertainty quantification, and scientific machine learning. She leads projects on lightweight hybrid metamaterials, bio-inspired metamaterials using reinforcement learning, and AI-driven infrastructure monitoring. Active collaborations span academia and industry, with a focus on carbon emission reduction and smart manufacturing techniques. She currently supervises PhD students in Engineering and Environmental Sciences and accepts applications from motivated candidates. Her research has been published in journals like Mechanics of Materials and Thin-Walled Structures , with ongoing work on programmable shape-morphing and piezoelectric metamaterials.

Alexander Schaumمشاهده پروفایل

استاد

• Process Analytics
• Control Engineering
• Bioprocess Engineering
• +۳ مورد دیگر

Prof. Alexander Schaum is the Head of Process Analytics at the Institute of Food Science and Biotechnology, University of Hohenheim, within the Faculty of Natural Sciences. His research focuses on advanced process analytics, control systems engineering, and bioprocess modeling, with applications in food science, environmental systems, and energy storage. He leads initiatives in model-based monitoring, optimal control of water networks, and synchronization dynamics in oscillator networks. Research interests include nonlinear control theory, population balance modeling, and data-driven analysis of complex systems. Recent work highlights process optimization in spray drying, urban flood forecasting, and bio-inspired feedback mechanisms for temperature regulation. Publications span 2023–2025, emphasizing computational methods and interdisciplinary applications. No specific awards or student advisement details were provided in the text.