جستجوی استاد راهنمای دانشگاهی

Maciej Kruszynaمشاهده پروفایل

استاد

• Transport Infrastructure
• Transport Modeling
• Urban Mobility
• +۷ مورد دیگر

Prof. Maciej Kruszyna is a faculty member at the Faculty of Civil Engineering, Wroclaw University of Science and Technology, where he conducts research and publishes extensively in the domain of transport systems and urban infrastructure. His academic foundation includes an MSc (1996), PhD (1999), and habilitated Doctor degree (2014) in technical sciences with a focus on construction. His research interests span a wide range of topics in urban mobility and transport engineering, with a strong emphasis on transport infrastructure , modeling , mobility systems , and heuristic optimization methods such as Ant Colony Optimization. He specializes in applying computational intelligence to solve complex urban transport challenges, particularly in public transit planning, railway safety, and smart city innovations. The recent trend in his publications highlights the application of bio-inspired algorithms to evaluate and design sustainable transport solutions, including underground railway systems, public transport networks, and intelligent level crossing mechanisms. His work bridges civil engineering with computational modeling to enhance urban sustainability and safety. No scientific awards are listed in the provided text. There is no information available about student supervision or research grants. However, his frequent co-authorship with researchers like Mariusz Korzeń and Michał Zawodny suggests active collaboration within a research team focused on transport systems at his institution. He is involved in interdisciplinary research connecting civil engineering, environmental health, and smart city technologies.

• Complex Photonics
• Nonlinear Dynamics
• Optical Communications
• +۴ مورد دیگر

Dr. Apostolos Argyris is an Associate Professor at the Department of Physics, University of the Balearic Islands (UIB), and a member of the Institute for Cross-Disciplinary Physics and Complex Systems (IFISC), a joint UIB-CSIC institute. He holds the Spanish I3 certification with three research merits (sexenios), four teaching merits (quinquenios), and seven trienios of academic experience. His academic background includes: B.Sc. in Physics from Aristotle University of Thessaloniki (1999) M.Sc. in Physics (Microelectronics & Optoelectronics) from University of Crete (2001) Ph.D. in Informatics & Telecommunications from National and Kapodistrian University of Athens (2006) His research focuses on complex photonic systems and nonlinear dynamics, with specific interests in coupled laser networks, chaotic oscillators, neuromorphic information processing, unconventional optical communications, photonic computing, optical chaos applications, and physical random number generation. His work combines theoretical models with experimental photonics to develop next-generation computing and communication technologies. Publication analysis reveals a dominant focus on photonic neuromorphic computing, optical reservoir systems, high-speed fiber communications, and interdisciplinary physics frameworks. Recent works demonstrate increasing emphasis on hardware implementations of machine learning concepts using photonic substrates and silicon devices. Awards and recognitions include: TR35 Young Innovators Award 2006 from MIT Technology Review ERICSSON Award of Excellence in Telecommunications (2006) He leads research projects including: INFOLANET (National Project 2023-2026): Information processing with coupled laser networks POST-DIGITAL Plus (EU Commission 2025-2029): Post-digital computing training network As principal investigator of the consolidated research group 'Fotónica Compleja y Sistemas Neuroinspirados' (FoCo-SiNeu), he directs laboratory activities in neuromorphic photonics and complex systems. He currently supervises doctoral candidates in the Physics PhD program and teaches undergraduate/graduate courses including Medical Physics, Complex Photonics, and General Physics Laboratory.

• Machine Learning
• Deep Learning
• Wireless Communications
• +۵ مورد دیگر

Ashit Kumar Dutta is an Associate Professor in the Department of Computer Science at King Saud University's College of Computer and Information Sciences. With over 40 publications spanning 2020-2025, his research bridges artificial intelligence with practical applications in healthcare, wireless communications, and cybersecurity. His collaborative work involves extensive partnerships with Saudi researchers and institutions, particularly in King Saud University's healthcare technology initiatives. Dr. Dutta's research interests focus on cutting-edge applications of machine learning and deep learning across multiple domains. His primary expertise lies in developing AI-driven solutions for healthcare challenges including cardiovascular disease detection, brain tumor segmentation, ALS diagnosis, and osteosarcoma identification using medical imaging. He also specializes in next-generation wireless communications, particularly 6G resource allocation, vehicular networks, and Internet of Things applications. His cybersecurity work emphasizes malware detection and network security using bio-inspired optimization techniques. The interdisciplinary nature of his research demonstrates a strong commitment to solving real-world problems through computational approaches. Analysis of his recent publications reveals a clear trend toward increasingly sophisticated AI architectures applied to healthcare challenges, with particular emphasis on federated learning approaches that maintain data privacy. His work on 6G communications shows growing sophistication in handling complex resource allocation problems across multiple dimensions. The consistent publication output across multiple high-impact venues demonstrates both productivity and recognition within his fields of expertise. Dr. Dutta maintains an active research program with significant contributions to both theoretical and applied aspects of computer science. His work on healthcare applications demonstrates particular promise for real-world implementation, with several papers focusing on practical deployment of AI solutions in medical settings. His expertise in both wireless communications and healthcare technology positions him uniquely to address emerging challenges in connected health systems.

• Computer Science
• Artificial Intelligence
• Medical Image Analysis
• +۳ مورد دیگر

Xi Wu is a faculty member at Chengdu University of Information Technology , affiliated with the School of Computer Science . He holds a PhD from Sichuan University (2012, College of Electronic and Information Engineering). Current Research Focus: Medical imaging, computer vision, and deep learning applications in healthcare Key Themes: PET image reconstruction, radiotherapy dose prediction, GANs, diffusion models, and facial expression recognition His recent work explores transformer architectures , semi-supervised learning , and uncertainty-aware models for tasks like tumor segmentation and multi-organ analysis. Publications emphasize cross-domain adaptation and multi-modal medical imaging .

Nils Bauschمشاهده پروفایل

مدرس

• Embedded Systems
• Additive Manufacturing
• Multi-Criteria Decision-Making (MCDM) Methods
• +۵ مورد دیگر

Nils Bausch is a Course Leader in the Department of Science and Engineering at Southampton Solent University. He holds a PhD from the University of Portsmouth and a Diplom Ingenieur (FH) in Mechatronics from FH Aachen. His academic roles include teaching engineering modules across foundation, undergraduate, and postgraduate levels, with a focus on project supervision and applied engineering. Affiliations : Southampton Solent University; Department of Science and Engineering Professional Memberships : Chartered Engineer (CEng), Member of Institution of Engineering and Technology (MIET), Fellow of the Higher Education Academy (FHEA) Research interests span embedded systems, additive manufacturing, corrosion detection, nuclear power plant control, and AI-driven technologies. Nils has secured grants from GCRF, EPSRC, and Innovate UK, and has authored over 40 peer-reviewed publications. His work includes studies on intelligent systems for powered wheelchairs, corrosion monitoring of offshore wind turbines, and advanced control methodologies for nuclear reactors. Key Research Themes : Smart home and assistive technologies Sensor systems and IoT applications Robust control engineering for critical infrastructure Material degradation analysis in marine environments Recent articles focus on wavelet-based control systems for nuclear reactors, corrosion detection in offshore wind turbines, and bio-inspired UAV control algorithms. Awards include prestigious engineering certifications reflecting his industry-academia collaboration. Nils serves as an external examiner for UK higher education programs and actively contributes to professional registration processes through the IET.

Ashish Deshpandeمشاهده پروفایل

استاد

• Robotics and Intelligent Mechanical Systems
• Biomechanical and Biomedicine Engineering
• Advanced Design and Manufacturing
• +۳ مورد دیگر

Ashish Deshpande is a Professor at the University of Texas at Austin, holding the Carroll D. Simmons Centennial Teaching Fellowship and Cockrell Family Regents Chair in Engineering. He is affiliated with the Department of Mechanical Engineering within the Cockrell School of Engineering. His research focuses on Robotics and Intelligent Mechanical Systems, Biomechanical Engineering, and Advanced Manufacturing, emphasizing exoskeleton design, human-robot interaction, and rehabilitation robotics. His work integrates biomechanical principles with robotic systems to enhance rehabilitation therapies, particularly for stroke patients and individuals with neuromuscular impairments. Key projects include the Harmony exoskeleton, BaRiFlex gripper, and novel bio-inspired actuators. He explores topics like stiffness modulation, kinematic control, and energy efficiency in wearable robotics. Recent publications (2023–2025) highlight advancements in exoskeleton design, control algorithms for multi-joint systems, and human-centric robotic interfaces. His research bridges engineering and clinical applications, aiming to improve motor recovery and functional independence through innovative robotic solutions. Dr. Deshpande's contributions also include frameworks for adaptive motor learning, curriculum design in robotic training, and methodologies for assessing human-robot interaction dynamics. His work addresses challenges in variable stiffness actuation, soft robotics, and sensor integration for precision control.

Alfredo Alexander-Katzمشاهده پروفایل

استاد

• Self-assembly
• Bio-inspired soft materials
• Active matter systems
• +۵ مورد دیگر

Alfredo Alexander-Katz is the Michael (1949) and Sonja Koerner Professor of Materials Science and Engineering at MIT, leading the Alexander-Katz Research Group. His work focuses on self-assembly processes in biological and bio-inspired soft materials, combining analytical theory, simulations, and experiments. Key research areas include designer 3D self-assembly of copolymers, bio-inspired random heteropolymers, and active soft matter dynamics. Education: B.S. in Physics (National Autonomous University of Mexico, 1998), Ph.D. in Physics (University of California, Santa Barbara, 2004). Postdoctoral training at Ludwig Maximilian University (Munich) and École Supérieure de Physique et Chimie Industrielle (Paris). Over 100 publications, including seminal works on blood clotting mechanisms and polymer electrolyte membranes. Awards include the 2013 Early Career Award from the U.S. Department of Defense and MIT's 2021 Committed to Caring honor. Research emphasizes interdisciplinary approaches spanning materials science, biophysics, and nanotechnology. Current projects include developing shear-responsive materials, computational tools for polymer design (e.g., PolyPal), and bio-inspired nanomaterials for biomedical applications.

Qian Maoمشاهده پروفایل

استادیار

• Deep Learning
• Cyber Security
• Wireless Networks
• +۳ مورد دیگر

Qian Mao is an Assistant Professor in the Department of Math/Computer Sci. at Whitworth University, joined in 2020. Specializes in Deep Learning, Cyber Security, and Wireless Networks. Holds dual Ph.D.s in Electrical Engineering (University of Alabama) and Traffic Information Engineering & Control (Tongji University). Research focuses on intelligent wireless networks, network coding, UAV communication systems, and steganography. Active in publishing on topics like deep learning applications, jamming countermeasures, and UAV protocols. Education: Ph.D. in Electrical Engineering (UA), Ph.D. in Traffic Information Engineering (Tongji), M.S. (Shanghai Ship & Shipping Research Institute), B.S. (Nanjing University of Aeronautics and Astronautics) Research interests blend machine learning with network systems, particularly in optimizing UAV swarm networks and securing wireless communications. Key contributions include adaptive transport layer control strategies and steganographic techniques. Over 20 peer-reviewed publications since 2015, with recent work exploring bio-inspired multi-beam transmission and ARMA model-based social media forecasting. Publications highlight interdisciplinary approaches to network security, data hiding, and autonomous systems. Current focus includes DL-driven network traffic analysis and UAV protocol design for computation-heavy applications.

Kwabena Boahenمشاهده پروفایل

استاد

• Neuromorphic Engineering
• Neuroscience
• Artificial Intelligence
• +۴ مورد دیگر

Kwabena Boahen is a Professor of Bioengineering and Electrical Engineering at Stanford University, with a courtesy appointment in Computer Science. He is affiliated with the Wu Tsai Neurosciences Institute, the Bio-X Institute, and the System X Alliance. His research bridges neurobiology, computer science, and electronics, focusing on neuromorphic engineering to model brain functions. He founded the Brains in Silicon Lab, developing silicon chips that emulate neural behavior efficiently. Notable contributions include the Neurogrid platform and the Braindrop architecture. Boahen holds multiple awards, including the Packard Fellowship and NIH Pioneer Award, and has led interdisciplinary research initiatives like the Brainstorm Project. He advises numerous graduate students and teaches courses on neuromorphics and bioengineering systems. Education: PhD in Computation and Neural Systems from Caltech (1997). Prior to Stanford, he was at the University of Pennsylvania (1997–2005), holding the Skirkanich Term Junior Chair. His work spans over 100 publications, emphasizing energy-efficient neural models and silicon implementations of brain-inspired systems. Research interests include neuromorphic engineering, neural network design, and the intersection of neuroscience with artificial intelligence. Recent work explores dendrocentric learning and embodied AI frameworks. He has pioneered methods for scaling neural simulations to functional brain sizes while maintaining biophysical accuracy. His publications highlight advancements in neuromorphic hardware, computational neuroscience, and interdisciplinary applications. Awards reflect recognition for innovations in neurogrid technology and contributions to neuroAI. Advising spans bioengineering, neuroscience, and biomedical data science PhD programs.

• Computer Graphics
• 3D Modeling
• Computer Animation
• +۷ مورد دیگر

Marie-Paule Cani is a Professor of Computer Science at École Polytechnique (Institut Polytechnique de Paris), where she serves as Dean of the Master of Science and Technology program and leads the STREAM research team at LIX Laboratory (CNRS/IP Paris). Her research bridges computer graphics, HCI, and AI, focusing on expressive 3D modeling, animation, and virtual environments. Education: 1987: M.Sc. in Computer Science, École Normale Supérieure & University Paris XI 1990: Ph.D. in Computer Graphics, University Paris XI 1995: Habilitation in Computer Science, Institut National Polytechnique de Grenoble Research Interests: She pioneers user-centered tools for 3D content creation, combining gesture-based interfaces (sketching, sculpting) with knowledge-enhanced procedural models. Key areas include implicit surfaces, physical simulation, AI-driven animation, and accessible tools for non-experts. Her work enables intuitive design of complex shapes, terrains, and dynamic scenes. Publication Trends: Recent work (2023–2025) emphasizes AI-integrated graphics, including controllable natural phenomena (volcanoes, erosion), sketch-based bio-visualization, reinforcement learning for animation, and real-time character control. Cross-disciplinary applications span geology, biology, and cinematography. Awards & Honors: ACM Steven A. Coons Award (2023) French Academy of Sciences (2020) ACM SIGGRAPH Academy (2019) ERC Advanced Grant EXPRESSIVE (2012–2017) CNRS Silver Medal (2012) Leadership & Grants: She founded research teams (STREAM, Imagine, Evasion) and secured major funding: ERC Advanced Grant, Google-École Polytechnique AI Chair (2018–2021), Horizon 2020 project CLIPE (2020–2024), and Hi!Paris Creative AI Fellowship (2021–2024). She mentors researchers in geometric modeling, animation, and AI. Labs & Teams: Directs the Modeling, Simulation & Learning pole at LIX (2019–2023). Founded STREAM (Structure Representation for Animation/Modeling) and Imagine (Inria/Grenoble teams), advancing real-time graphics and procedural content.

• Data Science
• Vehicular Edge Computing
• Resource Allocation
• +۵ مورد دیگر

Sandra Sampaio is a Lecturer in Information Management at the University of Manchester, actively contributing to research in data science and intelligent transportation systems. Her work bridges technical computing with practical applications in environmental sustainability and traffic management. Dr. Sampaio's research focuses on vehicular edge computing, resource allocation algorithms, and data wrangling techniques . Her work demonstrates particular expertise in applying computer vision to environmental monitoring and developing anomaly detection systems for traffic management. Her research portfolio shows a consistent trajectory toward solving complex problems at the intersection of data science and real-world transportation challenges. Analysis of her recent publications reveals a strong emphasis on practical applications of AI in transportation systems , with multiple papers addressing resource allocation in vehicular networks and edge computing environments. Her work shows increasing sophistication in handling spatial-temporal data patterns and developing efficient computational approaches for real-time traffic analysis. DRES ME - Data science to Recycle textiles for Environmental Sustainability - Manchester Engagement Study (2022) Dynamic Resource Management for Intelligent Transportation System Applications (2022) Dr. Sampaio has supervised multiple research projects and students, with evidence of collaborative work across disciplines. Her research has received notable external funding and recognition, including significant awards related to environmental sustainability and transportation systems. She maintains active collaborations with researchers across multiple institutions, particularly with Pedro Sampaio at the University of Manchester.

Erikas Simanaitisمشاهده پروفایل

پژوهشگر

• Robotics
• Control Systems
• Intelligent Systems

Erikas Simanaitis is a Doctoral Assistant at the Laboratory of Intelligent Systems (LIS) within the School of Engineering at the Swiss Federal Institute of Technology Lausanne (EPFL), actively pursuing his Doctoral program in robotics, control, and intelligent systems. His research centers on Robotics, Control Systems, and Intelligent Systems, with emphasis on autonomous robotic platforms and adaptive control algorithms. The Laboratory of Intelligent Systems specializes in evolutionary robotics, bio-inspired control systems, and machine learning applications for physical robots, operating at the intersection of mechanical engineering and artificial intelligence. Based at the MED 1 1612 facility on EPFL's Lausanne campus, Mr. Simanaitis contributes to LIS's experimental research in soft robotics and swarm intelligence. His work supports the laboratory's mission to develop next-generation robotic systems capable of complex decision-making in unstructured environments.

David Gruberمشاهده پروفایل

استاد

• Marine Biology
• Animal Communication
• Biofluorescence
• +۱۲ مورد دیگر

David Gruber is a Distinguished Professor of Biology and Environmental Sciences at the City University of New York, with affiliations at Baruch College and the CUNY Graduate Center. He is also the Founder and President of Project CETI, a nonprofit interdisciplinary initiative focused on decoding sperm whale communication using advanced machine learning and robotics. His work bridges marine biology, climate science, animal communication, and bio-inspired technology. Education and Professional Background: Ph.D. in Biology (specific institution not mentioned in text) Postdoctoral training likely in marine molecular biology or biophysics (inferred from research) National Geographic Explorer and Emerging Explorer (2014) Principal Investigator, Project CETI (Audacious Project, 2020) Research Interests: David Gruber's research is deeply interdisciplinary, focusing on the intersection of marine life and technology. He investigates biofluorescence and bioluminescence across diverse species—from corals and eels to sharks and sea turtles—discovering over 200 glowing organisms. His lab explores the molecular basis of these phenomena, identifying novel fluorescent proteins with potential biomedical applications. A major focus is animal communication , particularly in sperm whales, where he applies AI and natural language processing to decode vocalizations. He also studies coral resilience to climate change and deep-sea ecosystems. Recent Research Trends: Gruber’s recent publications reveal a strong shift toward integrating artificial intelligence with marine bioacoustics. His team uses convolutional neural networks to classify sperm whale clicks and identify individuals with high accuracy. There is a growing emphasis on unsupervised machine translation to interpret non-human communication, suggesting a future where interspecies dialogue may be possible. His work increasingly combines soft robotics, genomics, and real-time underwater sensing to enable non-invasive study of fragile deep-sea life. Scientific Awards and Recognition: National Geographic Emerging Explorer (2014) Multiple National Geographic Grants (2010–2020) Audacious Project Funding for Project CETI (2020) Leader in the global movement for ocean conservation and interspecies communication Advising and Grants: As a principal investigator and professor, Gruber mentors students and early-career scientists in marine biology, genomics, and bio-inspired technology. He has secured significant funding from National Geographic and other sources to support deep-sea exploration, coral research, and whale communication studies. His grants emphasize innovation in wildlife technology , including the development of gentle, on-whale sensors and soft robotic samplers. These projects often involve collaboration with engineers, computer scientists, and conservationists, reflecting his commitment to interdisciplinary science. Labs and Teams: Gruber leads a multidisciplinary research group that collaborates with the Harvard Microrobotics Laboratory, the Dominica Sperm Whale Project (led by Shane Gero), and institutions worldwide. His lab develops cutting-edge tools such as the 'shark-eye camera' and soft robotic grippers for delicate marine organisms. Project CETI brings together over 50 scientists from more than 15 institutions, forming one of the largest collaborative efforts in cetacean communication research.

• Computational Neuroscience
• Bio-inspired Artificial Intelligence
• Spiking Neural Networks
• +۱۳ مورد دیگر

Thomas Nowotny is a Professor of Informatics at the University of Sussex, School of Engineering and Informatics. He is Co-Director of Sussex AI and Head of the AI Research Group, with a research focus on computational neuroscience and bio-inspired artificial intelligence. His work bridges theoretical neuroscience with practical applications in machine learning, neuromorphic computing, and robotics. His primary research interests include: Spiking Neural Networks and neuromorphic computing GPU acceleration of brain simulations (GeNN framework) Information processing in insect olfactory systems Machine learning for electronic noses Bio-mimetic controllers for autonomous robots Hybrid computer-brain experimentation His recent publications demonstrate a strong trend in developing and applying advanced computational methods to model biological neural systems, particularly in insects, and leveraging these models to advance energy-efficient AI. Key themes include gradient learning in spiking networks, neural mechanisms of navigation and olfaction, and high-performance simulation tools. His work frequently appears in top journals such as Nature Machine Intelligence , Nature Communications , and Frontiers in Computational Neuroscience . Nowotny has secured significant research funding from major bodies including EPSRC, BBSRC, the European Union (Human Brain Project), Leverhulme Trust, and HFSP. His grants support projects on embodied cognition, neuromorphic computing, insect-inspired navigation, and memory consolidation. He leads a research group, supervises students, and is actively involved in the global computational neuroscience community as President of the Organization for Computational Neuroscience (OCNS). His technical contributions include the development of the GeNN simulation framework and associated tools like PyGeNN and Brian2GeNN, which enable efficient GPU-accelerated neural network simulations.

• Computational Intelligence
• Serious Games
• Machine Learning in Games
• +۵ مورد دیگر

Darryl Charles is a Professor of Artificial Intelligence and Games at the School of Arts & Humanities , Ulster University, specializing in computational intelligence applied to serious games, virtual reality, and connected health. He has over 80 peer-reviewed publications and authored the book Biologically Inspired Artificial Intelligence for Computer Games . Member of Computer Science Research Institute Fellow of the Higher Education Academy Active in SDGs related to health and education Research Interests: His work spans intelligent interactive storytelling , machine learning in games , user modeling , cloud computing , and connected health , with recent focus on natural user interfaces for rehabilitation and learning motivation. Scientific Awards: Catalyst Invent Finalist (2020) iCURE Business Accelerator (2020) Intertrade Ireland Seedcorn Finalist (2018/2019) ICVRAT/ICDVRAT Prizes (2014-2016) Academic Leadership: Served as External Examiner at Glasgow School of Art (2019-2023), University of West of Scotland (2008-2014), and other institutions.