جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Robotics
• Deep Reinforcement Learning
• +۳ مورد دیگر

Prof. Dr. Malte Schilling works at the University of Münster within the Department of Mathematics and Computer Science . His research focuses on the intersection of Artificial Intelligence , Robotics , and Neuroinformatics , with particular emphasis on Deep Reinforcement Learning and Modular AI Systems . He leads projects like Tutor.AI , a science-based learning assistant, and develops Predictive AI models for e-mobility in trucking . His recent publications highlight innovative approaches in biomimetic robotics , including decentralized controllers for hexapod locomotion and neuroWalknet architecture for context-dependent behavior. He also contributes to graph-based learning models for traffic prediction and explainable AI through counterfactual generation. Collaborative work spans institutions and disciplines, reflecting his interdisciplinary focus. Malte Schilling's research integrates principles from neuroscience and computational biology to enhance AI adaptivity. He applies these insights to robotic systems and real-world challenges like urban mobility prediction. His work demonstrates strong connections between theoretical computer science and practical AI implementations .

• Sensory control of locomotion
• Active sensing in insects
• Insect sense of touch
• +۳ مورد دیگر

Volker Dürr is a Professor of Biological Cybernetics at Bielefeld University , Faculty of Biology, and a member of the Center for Cognitive Interaction Technology (CITEC) . His work focuses on sensory control of locomotion , active tactile sensing in insects , and biomimetic modeling of movement systems. Education : Habilitation in Zoology (University of Cologne, 2008; Bielefeld, 2005), PhD in Biology (Bielefeld, 1998), Diploma in Biology (Tübingen, 1994) Academic Career : Professor at Bielefeld (2009-present), Junior Research Group Leader (University of Cologne, 2007-2009), Research Assistant (Bielefeld, 1998-2006) His research investigates how insects use antennal mechanosensory systems and proprioception to control locomotion in complex environments. Key themes include goal-directed movements , sensorimotor integration , and biomimetic robotics . Publications emphasize tactile sensing (15/23 articles), neural control of movement (9/23), biomechanical modeling (7/23), and cross-species locomotion analysis (4/23). Recent work explores virtual reality paradigms for locomotion studies and spiking neural networks for proprioceptive modeling.

Bhuvana Krishnaswamyمشاهده پروفایل

استادیار

• Wireless Networks
• Low-Power Wireless Systems
• Internet-of-Things (IoT)
• +۴ مورد دیگر

Bhuvana Krishnaswamy is an Assistant Professor at the Department of Electrical and Computer Engineering, University of Wisconsin–Madison, with an affiliation in Biomedical Engineering. She is an award-winning researcher and educator specializing in Communications, Networks, Privacy, and Security , blending wireless systems with biological applications. PhD, Georgia Institute of Technology (2018) MS, Georgia Institute of Technology (2013) BS, College of Engineering (2011) Her research spans Wireless Networks , Low-Power Systems , IoT , and Molecular Communication , focusing on scalable, efficient, and innovative network designs. She has pioneered frameworks like Cloud-LoRa and BYOG for LoRaWAN optimization, alongside bio-inspired systems such as PACT and molecular network protocols. Recent publications emphasize AI-driven bandwidth adaptation , battery-less communication , and satellite interference mitigation . Her work also intersects with environmental monitoring (e.g., soil CO2 sensing) and biomedical engineering. Scientific Awards : IEEE Senior Member (2024) NSF CAREER Award (2022) WARF Innovation Award Finalist (2020, 2019) Early Career Innovator Award (2023) N2Women Rising Star (2022) Bhuvana teaches courses like Introduction to Computer Engineering and Communication Networks , emphasizing the integration of research into pedagogy. Her lab collaborates on projects involving wireless systems, IoT, and molecular networks, supported by grants such as the NSF CAREER award.

Michael Papoutsidakisمشاهده پروفایل

استاد

• Automatic Control Systems
• Mechatronics
• Industrial Automation
• +۸ مورد دیگر

Professor Michael Papoutsidakis is affiliated with the Department of Industrial Design and Production Engineering at the University of West Attica. His academic career spans research in industrial automation, mechatronics, and intelligent control systems, with a focus on applications in hydraulic/pneumatic systems, robotics, and Industry 4.0 technologies. PhD from Bristol Robotics Laboratory (2004) MSc in Automatic Control Systems from University of the West of England (2004) Graduated from TEI Piraeus Automation Engineering (2000) His research interests include: Modeling of fluid power systems AI-driven control algorithms Smart logistics and ERP systems Embedded systems for motion devices Autonomous robotic platforms Wireless sensor networks in industrial applications Recent publications highlight his work at the intersection of 3D printing, robotics, and Industry 4.0, including advancements in digital twins, biomimetic manufacturing, and drone technology. His research emphasizes practical implementations for industrial and educational contexts. 2005 Patent for robotic training base 2025 Digital Twin Systems research 2024 UAV fuzzy control systems Contact: mipapou@uniwa.gr

• Optics
• Spectroscopy
• Diagnostic Imaging
• +۴ مورد دیگر

Vasilios Papadakis serves as an Assistant Professor at the University of West Attica with over two decades of international research and teaching experience spanning Delft University of Technology, Foundation for Technology and Research, University of Crete, and Hellenic Mediterranean University. His expertise centers on non-destructive testing, multispectral imaging, and diagnostic methodology development for material surface analysis under stress conditions. His academic foundation includes dual doctoral achievements: PhD in Spectral Tissue Imaging (Medical School, University of Crete) PhD in Organismal Behavior Observation via Machine Vision (Department of Biology, University of Crete) Dr. Papadakis' research integrates optical physics and engineering to pioneer diagnostic solutions. Core focus areas include: Spectroscopic characterization through Raman, infrared, and fluorescence techniques Material differentiation based on spectral signatures Optoelectronic device design for industrial information systems Dynamic surface analysis during stress exposure Analysis of his 150+ publications reveals dominant themes in Industry 4.0 implementation and sustainable manufacturing . Recent work demonstrates cross-disciplinary impact through 3D-printed infrastructure, biomimetic drone components, and machine learning-driven predictive maintenance systems—bridging theoretical mathematics with practical engineering solutions. As an educator, he teaches foundational engineering mathematics (Linear Algebra, Calculus) and specialized courses including Strength of Materials and Unmanned Aerial Systems. His pedagogical innovations feature low-cost robotics platforms like DuBot and sustainability integration through upcycled materials in mechatronics labs. He directs the Non-Destructive Testing and Systems Diagnosis Methodologies Laboratory , where his team develops imaging solutions for industrial quality control, with particular emphasis on stress-induced surface phenomena and embedded diagnostic systems for material science applications.

• Computational Neuroscience
• Biomechatronics
• Bio-inspired Robotics
• +۵ مورد دیگر

Dr. Hanno Gerd Meyer is a Postdoctoral Fellow at the Faculty of Engineering, University of Bielefeld, working with the Center for Cognitive Interaction Technology (CITEC) and the Research Group Biomechatronics since January 2016. His research focuses on understanding insect visual systems and developing bio-inspired camera systems for robotic platforms. Dr. Meyer received his PhD in Computational Neuroscience from Bielefeld University in February 2014 with his dissertation titled 'Representation of Visual Motion Information in the Fly Brain'. His academic background includes an International Master's program in 'Systems Biology of Brain and Behavior' (2008-2010) and undergraduate studies in Biology and Psychology (2003-2008), all at Bielefeld University. His research centers on how flying insects like flies and bees use their visual systems for course control, collision avoidance, and spatial navigation. Despite having relatively few neurons and poor spatial resolution compared to artificial systems, insect visual systems demonstrate remarkable speed, flexibility, and resource efficiency. Dr. Meyer's work aims to translate these biological principles into engineering applications for robotic vision systems. He collaborates with the Cognitronics group at CITEC to develop algorithms on dynamically reconfigurable hardware combined with low power microprocessors. These algorithms extract motion information from optic flow to enable robotic agents to perform visually-guided orientation behavior in unfamiliar terrain based on principles found in insect neurobiology. Dr. Meyer has been actively involved in research at Bielefeld University since 2010, progressing from Scientific Assistant positions in the Department of Neurobiology to his current Postdoctoral Fellowship. His work contributes to Bielefeld's Socio-Technical World strategic research area, which focuses on capabilities enabling agents like humans, robots, and AI to act and communicate in complex environments.

• Computer Science
• Cybersecurity
• Artificial Intelligence
• +۳ مورد دیگر

Selim Yilmaz is a faculty member at the Faculty of Engineering , Mugla Sıtkı Koçman University , serving in the Department of Software Engineering . With a PhD in Computer Engineering from Hacettepe University, he teaches courses including Deep Learning, Advanced Programming, and Information Security. His editorial roles span journals like PLOS ONE and Expert Systems With Applications . Research Interests : Selim Yilmaz focuses on Cybersecurity for Internet of Things Evolutionary Computation Machine Learning Applications Network Protocol Optimization Heuristic Algorithm Development Publication Trends reveal expertise in intrusion detection systems (IDS) for IoT environments, federated learning approaches, and evolutionary algorithm applications. His work spans interdisciplinary domains from dental diagnostics to industrial security. Scientific Contributions include Editorial board memberships (2016-2024) 11+ international conference presentations Key projects: CoCoIDS collaborative IDS framework Development of Electric Fish Optimization algorithm

Bartolomeo Montrucchioمشاهده پروفایل

استاد

• Computer Vision
• Quantum Computing
• Image Processing
• +۵ مورد دیگر

Bartolomeo Montrucchio is a Full Professor of Information Processing Systems (ING-INF/05) at the Department of Control and Computer Engineering (DAUIN) of the Polytechnic University of Turin. He is a member of the Interdepartmental Center Photonext - PoliTo Interdepartmental Center on Applied Photonics and serves as deputy director at the Interuniversity Center of Regional Interest for the Training of Secondary School Teachers (CIFIS) since July 2012. Additionally, he has held an adjunct professor position at the University of Illinois at Chicago during July 2008. Professor Montrucchio's research spans several cutting-edge areas with a primary focus on quantum computing, computer vision, and sensor networks. His work encompasses image processing, scientific visualization, parallel and distributed systems, and wireless sensor networks. He actively contributes to European research initiatives including the EQUO (European QUantum ecOsystems) project as Scientific Responsible. His research bridges theoretical computer science with practical applications across multiple industries. His publication record shows a strong trajectory toward quantum technologies, with numerous recent publications focusing on quantum machine learning, quantum algorithms for financial applications, and quantum applications in cybersecurity. His work demonstrates increasing emphasis on practical implementations of quantum computing in real-world scenarios, particularly in industrial settings and telecommunications. Best student paper award at BIOSIGNAL2002, conferred by EURASIP, Italy (2002) Associate Editor of IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2019-present) Professor Montrucchio actively supervises numerous PhD students working on quantum computing applications across various domains including finance, cybersecurity, traffic optimization, and industrial use cases. His teaching portfolio includes courses on Quantum Computing, Parallel and Distributed Computing, and Image Processing and Computer Vision across multiple degree programs including Computer Engineering, Biomedical Engineering, and Quantum Engineering. He leads multiple research projects funded by both competitive calls and commercial contracts, with a significant focus on quantum technologies since 2019. His patent portfolio includes several inventions related to tire manufacturing processes and visual rehabilitation for telemedicine.

Angelo Spognardiمشاهده پروفایل

دانشیار

• Information Security
• Social Media Fake Phenomena
• Network Security
• +۵ مورد دیگر

Angelo Spognardi is an Associate Professor in the Department of Computer Science at Sapienza University of Rome, leading the Network Security Lab group since March 2020. He teaches courses including Practical Network Defense and Programming Unit 2 for Computer Science and Cybersecurity programs. His research spans information security , with emphasis on fake phenomena in social media , fake content analysis in review systems, adversarial machine learning , and network security for resource-constrained devices . His work integrates bio-inspired models for bot detection and focuses on resilient metrics against disinformation campaigns. Recent publications explore LLM-powered bot detection and IPv6 security. He leads the Prebunking research project predicting coordinated inauthentic behaviors in social media. His lab promotes initiatives like CyberX Mind4Future , offering cybersecurity training with virtualized labs and hackathons. Master's students in Cybersecurity under his guidance achieve 100% placement with top salaries in Italy. Spognardi maintains active collaborations with the Sysma group at IMT Lucca and previously worked with DTU IoT Center and CNR's Institute of Informatics and Telematics. His industry impact includes frameworks like SafeDroid for Android malware detection and analyses of IoT broker vulnerabilities.

• Genetic Programming
• Evolutionary Algorithms
• Combinatorial Optimisation
• +۶ مورد دیگر

Dr. Edgar Galván is an Associate Professor in the Department of Computer Science at Maynooth University's Faculty of Science & Engineering. He is a leading expert in Genetic Programming (GP) and Evolutionary Algorithms, with a focus on semantic-based approaches, neutrality, and multi-objective optimization. His work spans applications in combinatorial optimization, gaming (e.g., Carcassonne), and software engineering, including neuroevolution for deep learning architectures. Current Affiliation: Maynooth University Previous Roles: Senior Researcher at University College Dublin, Trinity College Dublin, and INRIA Paris-Saclay Research interests include: Semantic-based Genetic Programming Multi-objective Evolutionary Algorithms Monte Carlo Tree Search Circular Economy Applications Privacy-Preserving Optimization Neuroevolution in Autonomous Systems His recent publications analyze semantic diversity in GP, neural architecture search, and privacy-aware swarm optimization. Key awards include being ranked among the top 1% of GP researchers by University College London (2020), a Marie Curie Fellowship (2014), and a Best Paper Award at ECTA 2015. Current Projects: REBUILD (Circular Economy Buildings, 2024-2027), VISION (Circular Business Models, 2023-2026) Previous Grants: Stochastic Bio-inspired Algorithms (2014-2017, €267k), circAI (2022-2023, €142k) Dr. Galván serves on program committees for IEEE, ACM, and Springer conferences, and as Scientific Adviser for institutions in Ireland, France, and Mexico. His work bridges theoretical GP analysis with real-world applications in energy optimization and AI.

• Robotics
• Artificial Intelligence
• Computational Neuroscience
• +۷ مورد دیگر

Robin Dietrich is a Researcher at the Department of Informatics 6 - Chair of Robotics, Artificial Intelligence and Real-time Systems at the Technical University of Munich . His work bridges computational neuroscience and robotics, focusing on translating neural mechanisms from mammalian brains into algorithms for mobile robot navigation. B.Sc. and M.Sc. in Computer Science Research on hippocampal temporal dynamics for neuromorphic SLAM Specializes in spiking neural networks for navigation and radar processing Research Interests : Robin's research explores the intersection of robotics, artificial intelligence, and computational neuroscience . His work specifically investigates spiking neural networks, FMCW radar data processing, and neuromorphic algorithms for autonomous systems. Recent projects focus on uncertainty quantification, evolutionary optimization, and multi-robot exploration using biologically inspired models. Publication Trends : Robin's publications (2019-2025) demonstrate a consistent focus on neuromorphic computing for robotic perception , with increasing specialization in spiking neural networks for radar processing and biologically inspired navigation algorithms . Key collaborations include contributions to multi-robot exploration metrics and hardware acceleration frameworks. Teaching Contributions : Robin has taught Digital Signal Processing and Real-Time Systems lectures since 2019, co-led seminars on Bio-inspired Data Processing , and supervised practical courses on Intelligent Mobile Robots using ROS.

Erhardt Barthمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Biological Vision

Prof. Erhardt Barth is the Deputy Director at the Institute of Neuro- and Bioinformatics (INB), University of Lübeck . His research focuses on Computer Vision and Machine Learning , drawing inspiration from biological vision systems to develop hybrid human-machine solutions. Education : PhD in Electrical Engineering (1994), Technical University of Munich Positions : Research Associate (Munich), Visiting Fellow (Melbourne), Klaus-Piltz Fellow (Berlin), NASA Vision Science Group member His work bridges computer vision and biological vision , exploring how neural mechanisms can inform algorithm design. Recent projects include deep learning applications in medical imaging (CT scans, radiographs) and bio-inspired neural architectures like FP-Nets and Min-Nets. Publications span medical diagnostics , image processing , and network efficiency . Key trends include explainable AI in healthcare, compact network design , and unsupervised learning techniques. Scientific distinctions : Recipient of the Schloessmann Award (Max Planck Society, 2000) Held prestigious Klaus-Piltz Fellowship (Institute for Advanced Study, Berlin) Prof. Barth has pioneered technology transfer initiatives, founding companies like GazeCom and gestigon while advancing automated diagnostic frameworks in clinical settings.

Mohammad Sadeghiمشاهده پروفایل

پژوهشگر ارشد

• Robotics
• Haptics
• Finite Element Method (FEM) Simulation
• +۳ مورد دیگر

Mohammad Sadeghi is a Research Fellow at the Institute of Mechatronics in Mechanical Engineering, Hamburg University of Technology, specializing in robotics, haptic systems, and sensor design. He holds a Dr.-Ing. degree and maintains active roles in research supervision and collaborative industry projects. His academic foundation includes: M.Sc. in Mechanical Engineering from Ferdowsi University, Mashhad, Iran B.Sc. in Mechanical Engineering from Birjand University, Birjand, Iran Dr. Sadeghi's research integrates robotics with medical applications, focusing on wearable exoskeletons for telerehabilitation, bio-inspired whisker sensors, and magnetoelectric actuator systems. His methodological approach combines finite element simulation, inverse optimization, and machine learning to solve challenges in human-robot interaction and precision sensing. Recent work demonstrates growing emphasis on mixed reality integration for industrial haptic feedback and minimally invasive surgical applications. Publication analysis reveals dual research thrusts: medical robotics (40% of recent output) featuring rehabilitation devices and surgical sensors, and magnetoelectric systems (35%) for bioimaging and precision actuation, complemented by biomaterials and manufacturing optimization studies. Recognition includes: Hamburg Innovation Call for Transfer award (2024) for surgical precision enhancement via whisker sensors He supervises six active theses on topics including magnet-based whisker sensors and mixed reality haptic feedback, with Kyrillos Adeeb's 2024 singularity-avoidance project completed. Industry collaborations with Schaeffler (robotic manufacturing), MBJ GmbH (solar robotics), and bAhead (liquid handling systems) demonstrate translational impact. His experimental work utilizes the institute's Haptics Lab and PHiLsLab for hardware-in-the-loop validation of autonomous systems.

Nejat YUMUŞAKمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Bioinformatics
• +۵ مورد دیگر

Prof. Nejat YUMUŞAK is a full Professor in the Department of Computer Engineering at Sakarya University's Faculty of Computer and Information Sciences, where he has built his academic career since 1995. His progression includes roles as Research Assistant (1993-1998), Assistant Professor (1998-2004), Associate Professor (2005-2011), and Professor (2011-present). Education PhD in Electrical-Electronics Engineering, Sakarya University (1995-1998) Thesis: Analysis of Power System Circuit Elements Using Artificial Neural Networks MSc in Electrical-Electronics Engineering, Dumlupinar University (1994-1995) Thesis: Calculation and Measurement of Transformer Parameters at High Frequencies BSc in Electrical-Electronics Engineering, Istanbul Technical University (1989-1993) Research Focus Prof. YUMUŞAK's research integrates artificial intelligence with multidisciplinary applications. Primary domains include: Bioinformatics & Medical AI : Developing deep learning models for COVID-19 mutation prediction, leukemia classification via blood smear analysis, and gastrointestinal anomaly detection using endoscopic data. Signal Processing & Security : Advancing acoustic event detection for security systems and vulnerability testing through intelligent fuzzing techniques. Optimization & Industrial Applications : Creating metaheuristic algorithms (e.g., enhanced Wild Horse Optimizer) for energy efficiency and Industry 4.0 digitalization. Publication Trends His recent articles (2022-2025) demonstrate strong emphasis on transformer architectures for virology, ensemble methods for medical diagnostics, and CNN/LSTM networks for genomic and acoustic data analysis. Over 50% of recent works focus on healthcare applications, particularly cancer and pandemic-related prediction models. Contact & Recognition Contact via nyumusak@sakarya.edu.tr or phone (0264) 264 58 94. His work has received 793 citations (Web of Science) with an H-index of 14.

Jose A. Boludaمشاهده پروفایل

دانشیار

• Computer Vision
• Hardware Design
• Image Processing
• +۴ مورد دیگر

Dr. Jose A. Boluda is an Associate Professor in the Department of Computer Engineering at the University of Valencia's School of Engineering. He holds a B.S. in Physics (Electricity, Electronics and Computer Science, 1992) and a Ph.D. (2000) from the same institution. With 6 teaching quinquenios and 4 research sexenios, his academic career spans over two decades. His research focuses on: Computer vision hardware design Smart vision sensors and neuromorphic computing Reconfigurable architectures (FPGA) High-speed motion analysis and change-driven processing Biomimetic visual sensing strategies He has authored over 50 international publications and participated in 15 research projects. His publications predominantly explore: Event-based vision sensors Hardware-accelerated image processing Neuromorphic engineering applications Real-time systems for robotics and 3D scanning Low-power circuit design for computer vision Awards include: Fernando Sapiña Award 2023 for Valencian teaching materials Fernando Sapiña Award 2021 for English teaching materials Fernando Sapiña Award 2021 for Valencian teaching materials He has directed 2 doctoral theses and supervised multiple master's projects. Research includes international collaborations at the University of Virginia, University of Macedonia, and Universitat Jaume I. His lab focuses on developing novel vision sensors and processing architectures.