جست‌وجوی استاد و پژوهشگر

Benjamin Wheatleyمشاهده پروفایل

دانشیار

• Orthopaedic biomechanics
• Musculoskeletal modeling
• Soft-tissue mechanics
• +۲ مورد دیگر

Benjamin Wheatley is an Associate Professor of Mechanical Engineering at Bucknell University, where he leads the Mechanics and Modeling of Orthopaedic Tissues Laboratory (MMOT Lab) . His research integrates experimental and computational biomechanics to understand soft-tissue and musculoskeletal mechanics, with applications spanning orthopaedics, rehabilitation engineering, and bio-inspired design. Education B.S. in Engineering, Trinity College, 2011 Ph.D. in Mechanical Engineering, Colorado State University, 2017 Research Interests Wheatley’s work centers on finite-element modeling and experimental characterization of biological soft tissues, particularly skeletal muscle, tendon, and bone. He investigates structure–function relationships in orthopaedic tissues, neuromuscular biomechanics, and bio-inspired protective structures such as bighorn sheep horns. Applications include improving prosthetic gait, understanding knee-joint loading, and designing impact-mitigating materials. Publication Trends Across more than 30 peer-reviewed articles since 2015, Wheatley’s scholarship exhibits two dominant trajectories: (1) high-fidelity computational modeling of skeletal muscle and orthopaedic tissues under multiaxial loading, and (2) experimental biomechanics studies combining motion capture, EMG, imaging, and mechanical testing. Recent work increasingly couples optimal-control theory with gait simulations to predict clinical outcomes for individuals with limb loss. Scientific Awards & Honors (none explicitly listed in provided text) Advising & Funding Wheatley actively mentors undergraduate and graduate researchers in the MMOT Lab; interested students are invited to attend weekly lab meetings after contacting him via email. Grant and funding details are not provided in the supplied text. Laboratory & Team He directs the Mechanics and Modeling of Orthopaedic Tissues Laboratory located in Academic East 302, Bucknell University. The lab emphasizes student-led collaborative research that bridges mechanical engineering, orthopaedics, and biology.

• information systems
• knowledge management
• open innovation
• +۷ مورد دیگر

Isabel Maria Pinto Ramos is an Associate Professor with Habilitation at the Department of Information Systems, School of Engineering, University of Minho , where she leads the ISTTOS R&D Lab and contributes to the Algoritmi Research Centre . She has held leadership roles including Head of Department of Information Systems and President of the Portuguese Association for Information Systems . Her career spans academic, research, and international collaboration roles, including a Visiting International Professor position at the University of Münster, Germany. Academic Leadership : Doctoral Programme Director (2014-2019), IFIP TC8 Chair (2019-2023), Vice President for Membership Services at Association for Information Systems (2022-2025) Research Themes : Innovation management, knowledge systems, digital transformation, crowdsourcing, organizational memory, gender in STEM, and technology's socio-cultural impacts International Engagement : Collaborations with Carnegie-Mellon, University of Agder, Georgia State, and Federal University of Santa Catarina through research projects and mobilities Scientific Recognition : IFIP Outstanding Service Award (2009) IFIP Silver Core Award (2013) IIAKM Lifetime Academic Achievement (2021) Editorial Contributions : Associate Editor for Communications of the AIS (since 2020), editorial board member for Enterprise Information Systems , International Journal of Knowledge Engineering , and Revista de Administração Mackenzie Project Involvement : ERASMUS+, Horizon 2020, FP7 programs with focus on digital workplaces, knowledge management, and organizational resilience Her scientific output demonstrates consistent exploration at the intersection of Information Systems and Organizational Innovation , with recent works focusing on Digital Transformation (2021-2025), Crowdsourcing Platforms (2009-2016), and Organizational Memory (2005-2014). The 2023-2025 publications particularly emphasize Smart City Resilience , Multigenerational Workforce Challenges , and AI Development Democratization .

Håvard Jenssenمشاهده پروفایل

استاد

• Bioactive Peptides
• Peptidomimetics
• Antimicrobial Agents
• +۳ مورد دیگر

Håvard Jenssen is a Professor in the Department of Chemistry at the University of Oslo, specializing in bioactive peptides and peptidomimetics within the Section for Chemical Life Sciences (Biomolecules, Bio-inspired Materials and Bioanalytics). His research focuses on antimicrobial applications against drug-resistant pathogens, with laboratory space in room Ø 202 at Sem Sælands vei 26. His primary research encompasses the design, synthesis, and mechanistic study of antimicrobial peptides and peptidomimetics targeting WHO priority pathogens including Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Candida auris. He investigates structure-activity relationships, membrane interactions, and resistance mechanisms using chemical biology, biophysical methods, and biological assays. His work bridges chemical synthesis with therapeutic applications in infectious disease. Recent publications (2024-2025) reveal dual research trajectories: antimicrobial peptoid development against multidrug-resistant pathogens and AI-driven medical imaging for hepatic vessel segmentation. This demonstrates an evolution from foundational anti-HSV peptide studies (2004-2006) toward broader antimicrobial applications and interdisciplinary collaboration with medical researchers. He actively participates in the Bio3 - Chemical Life Sciences research group at the University of Oslo, fostering collaborative work in chemical biology, biomolecular sciences, and translational research with clinical applications.

Geert A. Folkertsmaمشاهده پروفایل

مدرس

• Artificial Intelligence
• Autonomous Agent Systems
• Safe and Security Transport
• +۹ مورد دیگر

Geert A. Folkertsma is a Lecturer affiliated with the Digital Society Institute at the University of Twente, specializing in Robotics and Mechatronics. His work focuses on energy-aware robotic systems, autonomous vehicles, and biomimetic actuation technologies. Research Interests: Energy-efficient robotic architectures Biomimetic actuation and control Autonomous aerial and ground vehicles Embedded safety-critical systems Research Trends: His publications demonstrate expertise in applying bond graph modeling to UAV control, developing distributed robotic architectures with stability guarantees, and creating energy-aware actuation systems. Work spans aerospace robotics, dexterous manipulation, and bio-inspired design. Academic Contributions: Active in robotics education Developing simulation tools for autonomous systems Advancing energy-aware actuation for humanoid robots

• Bioactive heterocyclic compounds
• Photoredox/transition metal catalysis
• Late-stage functionalization
• +۷ مورد دیگر

Jørn H Hansen is a Professor in Organic/Medicinal Chemistry at the Department of Chemistry, UiT The Arctic University of Norway. He leads the Chemical Synthesis and Analysis (CSA) Group and contributes to the SusSTEMEd: Center for Sustainable STEM Education project. His research spans bioactive heterocyclic compounds, photoredox/transition metal catalysis, late-stage functionalization, small-molecule PET radiopharmaceuticals, and molecular sensors. Ph.D. in Organic Chemistry (Emory University, USA) M.Tech in Chemistry and Biotechnology (NTNU, Norway) His recent research focuses on green synthesis methods, marine-inspired antifoulants, and photoredox catalysis mechanisms. Publications highlight innovations in benzimidazole synthesis, halogen bonding, and computational/experimental synergy in catalysis. He has supervised numerous interdisciplinary projects in organic chemistry and environmental toxicology. 2024: Cryptophane synthesis for methane sensing 2023: Teaching reforms and antifouling compound libraries 2022: Marine pharmacophore-based enzyme inhibitors 2021: Water-compatible indole synthesis and halogen bonding studies 2020: Rapid quinoxaline synthesis and GnRH receptor antagonists Scientific awards include recognition as a Merited teacher . He teaches courses like KJE-3314 Organic Chemistry II and KJE-3308/8308 Organometallic Compounds in Organic Synthesis , emphasizing innovative assessment methods and student engagement.

Yun (Tom) Liuمشاهده پروفایل

دانشیار

• Bio-fluid mechanics
• Renewable energy
• Three-dimensional flow measurement
• +۴ مورد دیگر

Yun (Tom) Liu is an Associate Professor of Mechanical Engineering in the College of Engineering and Sciences at Purdue University Northwest. He joined PNW as an Assistant Professor in 2017 after earning his Ph.D. from Purdue University West Lafayette in 2016. Dr. Liu's teaching philosophy emphasizes experiential learning, using real-world examples to bridge theoretical concepts with practical applications, particularly during the pandemic when he developed innovative homemade lab equipment. Dr. Liu received his educational background from prestigious institutions: Ph.D. in Mechanical Engineering, Purdue University West Lafayette (2016) M.S. in Mechanical Engineering, University of Science and Technology of China (2011) B.S. in Mechanical Engineering, University of Science and Technology of China (2008) His research spans bio-fluid mechanics, renewable energy systems, three-dimensional flow measurement, optical diagnostics, and multiphase flow phenomena. Dr. Liu's work bridges traditional engineering with biological systems, demonstrated through studies on insect flight aerodynamics and bio-inspired designs. His solar energy research explores capturing radiation at higher altitudes where solar intensity is stronger above cloud cover. Dr. Liu's scholarly recognition includes: 2020 Proposal Submission Grant, Purdue University Northwest 2019 NSF-Major Research Instrument Grant 2019 Honorable Mention for Best Design Award, Global Space Balloon Challenge 2018 Catalyst Grant Award ($7,000), Purdue University Northwest Dr. Liu actively mentors students through research projects and the Aerosolar Engineering Club. He supervised six students who developed a weather balloon platform for solar radiation measurement, earning recognition in the Global Space Balloon Challenge among 400 universities. His teaching innovations include homemade wind tunnels using cardboard and computer fans during virtual learning, which were incorporated into PNW's Engineering Summer Camp. His laboratory work encompasses bio-fluid mechanics studies, solar energy capture systems, and advanced flow visualization techniques. Dr. Liu's interdisciplinary approach connects mechanical engineering with biology and environmental science, reflecting his belief that 21st-century engineering challenges require collaboration across diverse fields.

Hopfield Hintonمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Neural Networks
• +۳ مورد دیگر

John Hopfield and Geoffrey Hinton are distinguished academics who jointly won the 2024 Nobel Prize in Physics for their foundational contributions to machine learning and artificial neural networks. Their research established theoretical frameworks and scalable practical tools, bridging statistical mechanics and computational models inspired by biological neural networks. Research Interests: Their work integrates principles from theoretical physics (e.g., Ising model, Boltzmann equation) into artificial intelligence systems, enabling associative memory mechanisms and back-propagation algorithms critical to modern neural networks. They pioneered models like the Hopfield model and Boltzmann machine, which underpin advancements in AI and interdisciplinary applications such as protein structure prediction. Scientific Awards: Recipients of the 2024 Nobel Prize in Physics for discoveries enabling machine learning with artificial neural networks.

• Mathematical Modeling
• Sustainable Systems
• Computational Biology
• +۳ مورد دیگر

Elisa Benedetta Primavera Tiezzi serves as an Associate Professor in the Department of Information Engineering and Mathematical Sciences at the University of Siena, teaching Programming Fundamentals for Management Engineering and Mathematics undergraduate programs alongside Fuzzy and Real-Time Modeling for the Master's in Applied Mathematics. Her research integrates mathematical modeling with sustainability science and biological systems, emphasizing fuzzy logic applications in real-time environmental assessment and computational biology. Key contributions span emergy algebra for ecological accounting, hemostasis pathway modeling, and nutritional life cycle analysis in agro-food systems, demonstrating methodological innovation across theoretical and applied domains. Publication trends reveal consistent focus on sustainability metrics since 2011, evolving from emergy theory foundations toward contemporary work on food systems and biological modeling, with recent 2024 publications establishing computational frameworks for hemostasis and sustainable agriculture. Scientific awards: No awards were documented in source materials. Advising and grants: Student supervision details and research funding information were not provided in available texts. Labs and teams: No institutional affiliations with research laboratories or collaborative teams were specified.

Thomas Ihleمشاهده پروفایل

استاد

• Statistical physics of active matter
• Kinetic theory of swarms and flocks
• Soft condensed matter physics
• +۴ مورد دیگر

Prof. Thomas Ihle is a leading researcher at the University of Greifswald , heading the Soft Matter Theory group. His work bridges statistical physics , active matter , and computational modeling . Biology-inspired statistical and computational physics Statistical physics of active matter Kinetic theory of swarms and flocks Soft condensed matter physics Pattern formation far from equilibrium His research focuses on active matter systems , studying how energy uptake from the environment generates non-equilibrium phenomena like flocking, pattern formation, and memory effects. He uses kinetic theory and multi-particle collision dynamics to derive hydrodynamic equations and simulate complex liquids. Key trends in his recent publications include non-reciprocal interactions , exact collision operators , and hyperuniformity in active systems. Collaborations span institutions like Humboldt University Berlin , Northwestern University , and University of Gothenburg . Awards: Outstanding Referee 2017 (American Physical Society). Students: Mentored Jakob Mihatsch , Rüdiger Kürsten , and others in Master’s/Bachelor’s theses . Teaching includes a group seminar on active matter held every Friday.

Josefin Starkhammarمشاهده پروفایل

مدرس ارشد

• Marine Acoustics
• Biosonar
• Computer-Based Measurement Systems
• +۳ مورد دیگر

Josefin Starkhammar is a Senior Lecturer at the Division for Biomedical Engineering, Faculty of Engineering, Lund University. She serves as Principal Investigator for eSSENCE: The e-Science Collaboration, while also contributing to LU Profile Area: Natural and Artificial Cognition and LTH Profile Area: Engineering Health. Her research focuses on marine acoustics and biosonar with development of technological tools for bioacoustic studies. Acoustic finite element modeling Signal processing algorithms Underwater measurement systems Infrastructure non-destructive testing She teaches advanced computer-based measurement systems courses at LTH. Her research outputs span biological sciences, engineering, zoology, signal processing, and fluid mechanics. Current projects include 3D acoustic field propagation models for dolphin echolocation beam formation using in vivo CT imaging data. Josefin has received multiple awards including the Fred Fairfield Memorial Award (2007), Best Student Presentation (2008), and Outstanding Poster Presentation (2009). She actively participates in academic conferences like The COMSOL Conference 2023 and has served as external reviewer for PhD theses. Her work appears in journals such as the Journal of the Acoustical Society of America and JASA Express Letters.

Cristian Axenieمشاهده پروفایل

استاد

• Neural Networks
• Cognitive Computing
• Artificial Intelligence
• +۳ مورد دیگر

Prof. Dr.-Ing. Cristian Axenie serves as a Professor within the Faculty of Informatics at Nuremberg Institute of Technology, where he leads the Cognitive Neurocomputing research group. His institutional contact includes office room SP.488 and direct email correspondence. His research centers on cognitive neurocomputing, spanning neural networks, cognitive computing, artificial intelligence, machine learning, computational neuroscience, and neuroinformatics. This interdisciplinary focus aims to develop brain-inspired computing architectures that bridge biological cognition with artificial systems, emphasizing efficient neural modeling and adaptive learning frameworks. As an active faculty member, he contributes to both theoretical and applied research in neurocomputing, with his work influencing the development of next-generation intelligent systems through the integration of neuroscience principles and computational engineering.

Andrea Soltoggioمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Lifelong Learning
• +۱۱ مورد دیگر

Dr. Andrea Soltoggio is a Reader in Artificial Intelligence (Associate Professor) and Research Coordinator in the Computer Science Department at Loughborough University's School of Science. He holds a combined BSc and MSc in Computer Science from the Norwegian University of Science and Technology and Politecnico di Milano, and a PhD from the University of Birmingham. His academic journey includes research positions at EPFL, the University of Central Florida, and Bielefeld University where he served as Technical Coordinator for the FP7 European project AMARSi. His research focuses on creating AI systems that learn continuously like biological brains, with particular emphasis on lifelong learning, collaborative knowledge sharing, and energy-efficient AI. Dr. Soltoggio has made significant contributions to the development of algorithms that enable AI systems to share knowledge without centralized control, as demonstrated in his MOSAIC framework published in 2025 and his Nature Machine Intelligence paper on collective AI systems. His recent publications reveal a strong trend toward sustainable AI development, with multiple projects focused on reducing the energy footprint of machine learning systems. His work bridges neuroscience and AI, exploring how biological learning mechanisms can inform more adaptive artificial systems. The research spans from theoretical frameworks to practical applications in robotics, healthcare diagnostics, and edge computing. Fellow of the Higher Education Academy (FHEA) Published in Nature Machine Intelligence (2024) Lead researcher on multiple funded projects including FP7 AMARSi Regular media contributor on AI topics (BBC, The Conversation) Dr. Soltoggio actively supervises PhD students and postdoctoral researchers in the Computer Science Department, with current projects focusing on lifelong learning, neuromorphic computing, and sustainable AI. His research group collaborates with Loughborough Business School on digital decarbonization initiatives and maintains connections with international AI laboratories. The team has access to advanced computational resources including Nvidia A100 GPUs and various robotic platforms for experimental validation of their theories.

• Artificial Intelligence
• Computer Science
• Cellular Automata
• +۳ مورد دیگر

Tom Glover is an Assistant Professor in the Department of Computer Science within the Faculty of Technology, Art and Design at Oslo Metropolitan University. His office is located at Stensberggata 29, 0170 Oslo (Office number: SG204) with contact information including mobile: +47 975 38 894 and office: +47 672 37 712. Dr. Glover's research focuses on the intersection of cellular automata, artificial intelligence, and complex systems. His work spans theoretical computer science, artificial life, and practical applications in reservoir computing and control systems. His research group is part of the Innovation, Digital Transformation and Sustainability Research groups within the Department of Computer Science. Analysis of his publications reveals a consistent focus on cellular automata as computational models, with particular emphasis on their application in reservoir computing, network dynamics, and self-organizing systems. His work demonstrates how simple computational rules can generate complex behaviors with applications across multiple domains including control systems and biologically inspired computing. As an active researcher, Glover has published in reputable venues including the International Journal of Parallel, Emergent and Distributed Systems, Complex Systems, and proceedings from the Artificial Life Conference series. His recent work (2023-2024) shows continued development in sensitivity analysis of cellular automata and network topologies.

Otar Akanyetiمشاهده پروفایل

مدرس ارشد

• Bio-inspired Robotics
• Health Informatics
• Underwater Robotics
• +۳ مورد دیگر

Dr. Otar Akanyeti is a Senior Lecturer in the Department of Computer Science at Aberystwyth University. His research integrates engineering, physics, computer science, and biology to advance underwater robotics and health informatics. He holds a BSc in Electronic Engineering, an MSc in Embedded Systems and Robotics, and a PhD in robot learning from the University of Essex. He co-founded the Aberystwyth Stroke Research Group and leads projects on AI-driven healthcare interventions. His research focuses on two primary strands: 1) Bio-inspired Robotics , developing sensors and control systems for underwater autonomy using biological principles; and 2) Health Informatics , employing wearable technology and AI to improve stroke rehabilitation and chronic disease management. Current investigations include hydrodynamic imaging, collective intelligence for data mining, and predictive tools for neurorecovery. Akanyeti's recent publications emphasize interdisciplinary approaches, with articles spanning gait analysis using smartphone sensors, clinical outcome prediction in stroke, and biomimetic robotics. His work consistently bridges biomechanics, machine learning, and clinical applications. He leads multiple funded projects including 'Miscanthus AI' (plant phenotyping for Net Zero), 'Intelligent Exercise Practitioner for Stroke Survivors', and 'iNavigate' (brain-inspired navigation technologies). His lab utilizes advanced equipment like instrumented treadmills and eye-tracking systems.

• Cyber Security
• Critical Infrastructure Protection
• Machine Learning
• +۷ مورد دیگر

Konstantinos Demertzis is a Postdoctoral Researcher in Cyber Security of Critical Infrastructures at the School of Civil Engineering, Democritus University of Thrace. He also serves as Chief Information Security Officer at the Research & Informatics Directorate of the Greek Army and maintains research affiliations with National and Kapodistrian University of Athens. His academic journey includes PhD studies in Advanced Machine Learning and multiple Master's degrees spanning Mathematics, Cyber Security, Big Data, and Networking Technologies. PhD in Advanced Machine Learning (2017) - Democritus University of Thrace MSc in Mathematics (2020) - University of Crete MSc in Cyber Security and Big Data (2020) - University of Thessaly MSc in Networking Technologies (2012) - University of the Aegean BSc in Military Science (1996) - Academy of Non-Commissioned Officers Demertzis's research spans the intersection of machine learning, cybersecurity, and critical infrastructure protection. His work focuses particularly on developing intelligent systems for cyber defense of urban critical infrastructure, with applications in smart grids, environmental monitoring, and disaster response. His methodology often combines biologically inspired computational intelligence approaches with blockchain technology and federated learning frameworks. He has published extensively in high-impact journals with particular emphasis on anomaly detection, adaptive learning systems, and privacy-preserving architectures. His recent publications demonstrate a clear trend toward increasingly sophisticated integration of machine learning with critical infrastructure security. The 15 most recent papers show progression from foundational machine learning applications to complex, multi-layered security architectures incorporating blockchain, explainable AI, and cross-modal neural networks. His work consistently addresses real-world security challenges in industrial control systems, smart cities, and military applications. Windows Azure for Research Award Winner (2015-2016) Multiple Postgraduate Academic Excellence Scholarships Google Scholarship (2017-2018) Cisco CCNA Cyber Ops Scholarship (2017-2018) Best Research Paper Award at ISCRAM-med 2017 IBM Cloud Award (2017) Demertzis has advised multiple research projects including the Operational Programme 'Digital Convergence' and the Electoral Observatory Internet Research Programme. His technical expertise spans a wide range of cybersecurity domains including network security, blockchain applications, and AI-powered threat detection systems. He maintains active collaborations across academic and military institutions, with particular focus on protecting critical national infrastructure. His laboratory work primarily centers on the Lab of Forest-Environmental Informatics and Computational Intelligence, where he has developed intelligent models for environmental risk assessment and critical infrastructure protection. Current research directions include blockchained adaptive federated auto meta-learning architectures for cybersecurity and privacy in Industry 4.0 environments.