جست‌وجوی استاد و پژوهشگر

• Cybersecurity
• Intrusion Detection
• Anomaly Detection
• +۵ مورد دیگر

Grzegorz Kołaczek is a faculty member at the Faculty of Information and Communication Technology at Wrocław University of Science and Technology, affiliated with the Department of Computer Science and Systems Engineering . His research focuses on cybersecurity , intrusion detection , and security modeling with specific interests in Trust-based security frameworks IoT cybersecurity Anonymity protocols Fraud detection in digital systems . His recent publications emphasize the intersection of cybersecurity and emerging technologies , particularly in Internet of Things environments and e-commerce platforms. Key research trends include collaborative intrusion detection , adaptive user interfaces , and machine learning for threat analysis . Contact: grzegorz.kolaczek@pwr.edu.pl

• Collective Intelligence
• Multiagent Systems
• Knowledge Diffusion
• +۳ مورد دیگر

Marcin Maleszka is a researcher at the Faculty of Information and Communication Technology at Wrocław University of Science and Technology, specializing in collective intelligence , multiagent systems , knowledge diffusion , and knowledge integration . His work bridges computational models with social dynamics, focusing on group learning, recommendation systems, and secure data sharing. Current affiliation: Department of Applied Informatics, Wrocław University of Science and Technology Email: marcin.maleszka@pwr.edu.pl Office hours: Wednesday 13:30–15:00, Thursday 13:00–15:00, Saturday 16:45–17:45 His research explores how agent-based systems can model social collectives, optimize knowledge transfer, and enhance educational and healthcare technologies. Recent publications highlight applications in digital heritage , medical diagnostics , and urban mobility , with methodologies spanning GANs , ANNs , and agent modeling . Key publication trends include: Integration of Generative Adversarial Networks and Graph Neural Networks for heritage data Development of agent-based models for group learning Security mechanisms in peer-to-peer systems using attribute-based encryption Applications in medical imaging and traffic modeling Contact details: Address: ul. Z. Janiszewskiego 11/17, 50-372 Wrocław Room: C-3, 15 (Wrocław) and D-1, 30 (during Saturday office hours) Phone: +48 71 320 2938

James Jerson Ortiz Vegaمشاهده پروفایل

پژوهشگر

• Formal Methods
• Real-Time Systems
• Software Verification
• +۵ مورد دیگر

James Jerson Ortiz Vega is a researcher at the Research Center on Information Systems Engineering , Faculty of Computer Science, specializing in formal methods for real-time and distributed systems. His work focuses on timed automata, obstruction logic, and mutation testing. Key Projects: CFV: Federated Centre for Software Verification, THCS: Testing Highly-Configurable Systems, SEMIA: Semantics Enhanced Medical Imaging Architecture His research explores dynamic game reasoning for security protocols, timed automata reduction techniques , and probabilistic extensions of obstruction logic . Recent publications address coalition reasoning in multiagent systems and mutation testing for timed automata networks. He actively contributes to academic events, including organizing the FOCUS Research Seminar and presenting at the NASA Formal Methods Symposium (2017–2019). Collaborations span institutions like Perrouin Lab, Schobbens Research Group, and international teams in model-based systems verification.

Simone D’Amicoمشاهده پروفایل

دانشیار

• Autonomous Spacecraft
• Distributed Space Systems
• Space Technology Policy
• +۳ مورد دیگر

Simone D’Amico is a Science Fellow at the Hoover Institution and an Associate Professor of Aeronautics and Astronautics (with a courtesy appointment in Geophysics) at Stanford University. He serves as the W. M. Keck Faculty Scholar in the School of Engineering and directs the Stanford Space Rendezvous Laboratory , co-directs the Center for Aerospace Autonomy Research (CAESAR) , and leads the undergraduate aerospace engineering program at Stanford. Expertise: Autonomous spacecraft, distributed space systems, space technology policy Funding: NASA (Starling), National Science Foundation (VISORS, SWARM-EX) Advisory Roles: Four space startups focusing on SAR remote sensing, orbital lifetime prolongation, and space-based solar power Prior Affiliation: German Aerospace Center (research scientist and team leader) Research Interests center on autonomous satellite swarms, multiagent architectures, and responsible space policy. His work bridges aerospace engineering and geophysics, emphasizing sustainable space exploration and commercial-military space governance. Scientific Contributions include developing guidance, navigation, and control systems for distributed space missions. His recent publications address: 2025: Export control reforms and commercial space innovation 2024: Ethical frameworks for space preservation Awards highlight his technical and policy impact, including NASA honors, IEEE and AIAA best paper awards, and the Leonardo 500 Award.

• Artificial Intelligence
• Machine Learning
• Technoculture
• +۴ مورد دیگر

Ramon Sangüesa Sole is a Professor at Universitat Politècnica de Catalunya (UPC) within the School of Computer Science and Department of Computer Science . He is a member of the IDEAI-UPC (Intelligent Data Science and Artificial Intelligence Research Group) and KEMLG (Knowledge Engineering and Machine Learning Group). Fields of Interest : Artificial Intelligence, Machine Learning, Technoculture, Science Communication, Social Innovation Education : Doctor in Computer Science (UPC) His research focuses on integrating AI with social and environmental contexts, developing algorithmic transparency frameworks, and creating sociotechnical systems. Key projects include democratizing AI through citizen participation and applying machine learning to urban planning and educational innovation. His work emphasizes ethical considerations and interdisciplinary collaboration. Recent publications analyze topics like algorithmic transparency, urban AI applications, and student engagement technologies. Awards include the DISTINCIÓ JAUME VICENS VIVES for research excellence and the 8è Premi a la Qualitat en la Docència Universitària for educational innovation. Sangüesa leads projects in AI-driven design, environmental decision support systems, and personalized learning frameworks.

Hassan Zargarzadehمشاهده پروفایل

دانشیار

• Robotics
• Intelligent Control Systems
• Power Electronics
• +۷ مورد دیگر

Dr. Hassan Zargarzadeh is an Associate Professor in the Phillip M. Drayer Department of Electrical and Computer Engineering at Lamar University, specializing in Robotics and Intelligent Control Systems. His research spans multiagent systems, underwater robotics, wireless vehicle charging, and adaptive control algorithms. Ph.D. in Electrical Engineering, Missouri University of Science and Technology, 2012 M.S. in Electrical Engineering, Iran University of Science and Technology, 2009 B.S. in Electrical Engineering, Amir Kabir University, 2000 Dr. Zargarzadeh leads the Robotics and Intelligent Control Systems (RICS) Lab, focusing on: Advanced control methods for uncertain nonlinear systems Mechatronics and robotics design Power electronics and vehicle charging systems Swarm robotics and game-theoretic path planning His recent research trends include applying neural networks to autonomous systems, developing vision-based navigation for underwater robots, and optimizing wireless power transfer for electric vehicles. Collaborative projects span environmental monitoring, energy systems, and multiagent control. Scientific contributions include: Best presenter runner-up at ISC-supported research poster presentation, 2010 Top 3% M.S. student in Iran, 2008 National exam rankings in 1995 (top 100) and 2006 (top 800) Advising and grants: Advised 10+ graduate students in robotics and control $35,000 CAPM grant (2017) for bunker fuel optimization $25,000 CAWAQ grant (2016) for invasive species detection

Ulle Endrissمشاهده پروفایل

استاد

• Artificial Intelligence
• Collective Decision Making
• Computational Social Choice
• +۵ مورد دیگر

Ulle Endriss is a Professor of Artificial Intelligence and Collective Decision Making at the Institute for Logic, Language and Computation (ILLC) at the University of Amsterdam. He leads the COMSOC Group and is a member of both the Theoretical Computer Science research unit of the ILLC and the Centre for Explainable, Responsible and Theory-driven AI (CERTAIN). Endriss has held academic positions since 2005, progressing from Assistant Professor (2005-2011) to Associate Professor (2011-2019) and finally Full Professor since 2019. Endriss's research focuses on formal methods in AI, particularly in multiagent systems and knowledge representation, with special interest in computational social choice—the intersection of AI with economics and political science. His work spans voting theory, fair division, participatory budgeting, and game theory. He is actively involved in the ADDI project on digital democracy and regularly contributes to major AI conferences including AAMAS, IJCAI, and AAAI. His recent publications demonstrate a strong focus on computational social choice, with particular emphasis on voting systems, participatory budgeting mechanisms, and the theoretical foundations of collective decision making. His research combines theoretical rigor with practical applications in democratic processes and resource allocation problems. Runner-up for the Best Paper Award (2023) Best Paper Award (2016) Best Paper Award (2012) Best Paper Award (2005) Finalist for the Best Paper Award (2014) Finalist for the Best Paper Award (2008) IJCAI-JAIR Best Paper Prize 2016 Endriss regularly teaches courses on Computational Social Choice and Game Theory for MSc Logic and MSc AI programmes. He makes all his teaching materials openly available, consistent with his commitment to open access in both research and education. He has supervised numerous Master's theses that have led to published research. His work extends to outreach through platforms like Game-Academy.org and Pabuviz.org, which help explain complex voting concepts to broader audiences.

Dennis Grinwaldمشاهده پروفایل

پژوهشگر

• Probabilistic Machine Learning
• Distributed Deep Learning
• Explainable AI
• +۳ مورد دیگر

Dennis Grinwald is a doctoral researcher at the Technical University of Berlin affiliated with the Berlin Institute for the Foundations of Learning and Data (BIFOLD). He holds a Master of Science in Computer Science from TU Berlin (2022) and focuses on machine learning applications in collaborative multiagent systems, distributed deep learning, and explainable AI. His technical work includes open-source projects like Hanabi game-solving with reinforcement learning, DQN-based Lunar Lander automation, and speech command prediction using LSTMs. M.Sc. in Computer Science (2022, TU Berlin) Current focus areas: Probabilistic ML, distributed learning architectures, and XAI Active GitHub contributor (22 repositories, 8 followers) Notable projects: Hanabi multiagent reinforcement learning ML applications in natural sciences DQN for autonomous lunar lander environments LSTM-based speech command recognition

Marco Perez Hernandezمشاهده پروفایل

مدرس ارشد

• Multiagent Systems
• Distributed Artificial Intelligence
• Internet of Things
• +۵ مورد دیگر

Marco Perez Hernandez is a Senior Lecturer in the School of Computing and Creative Technologies at the University of the West of England Bristol. His research focuses on distributed intelligent systems, multiagent systems, and their applications in IoT environments and digital infrastructures. Specializes in agent-based control systems and network intent control Recipient of UWE’s Vice Chancellor Early Career Research Award 2022 His work explores the dynamics of complex networks of agents, designing algorithms for collective learning and self-organization. The research emphasizes reducing platform dependencies in MAS through container-based virtualization, enabling flexible and cost-effective deployment. Scientific awards include: UWE’s Vice Chancellor Early Career Research Award 2022 Projects: GLOW-Energy (EPSRC, Co-I) LLM Agents in coding (UWE CATE, PI) NGCDI (EPSRC & BT, Researcher)

Philip Brownمشاهده پروفایل

دانشیار

• Game Theory
• Multi-Agent Systems
• Cyber-Physical Systems
• +۹ مورد دیگر

Philip Brown is an Associate Professor in the Department of Computer Science at the University of Colorado at Colorado Springs. He received his PhD in Electrical and Computer Engineering from the University of California, Santa Barbara in 2018 under the supervision of Jason R. Marden. His research focuses on the intersection of technology and society, utilizing game theory, optimization, and multiagent systems to study incentive mechanisms, cybersecurity, and smart infrastructure. Current Projects: CAREER: Endogenous Information Design for smart transportation networks AFOSR YIP: Robust multiagent coordination with randomized algorithms Deriving satellite maneuver intent via game theory Past Projects: Socially Networked Autonomy: Autonomous vehicle routing COVID-19 Policy Optimization: Localized decision frameworks Value-Based Access Control: Path security mechanisms Dynamic Aviation Routing: Weather-aware path selection Research Areas: Dr. Brown's work spans game theory applications in cyber-social systems, robust network games, and strategic security modeling. He explores how financial/informational incentives shape crowd behavior in smart cities, cybersecurity vulnerabilities from mis-modeled attackers, and the paradoxes of altruism in transportation networks. Publication Trends: His recent articles focus on endogenous Bayesian games for information design, altruism dynamics in congestion games, security modeling for autonomous systems, and pandemic policy analysis. Key subfields include network robustness, incentive mechanisms, and human-machine interaction in infrastructure systems. Scientific Awards: NSF CAREER award (2025) UCCS Outstanding Teacher Award (2024) AFOSR Young Investigator Award (2022) CCDC Best PhD Thesis Award (2018) Best Paper awards at EAI GameNets, IEEE conferences Advising: Dr. Brown has advised 2 PhD graduates (Joshua Seaton & Brandon Collins) and multiple Master's/undergraduate researchers. His lab (DeSCon) investigates decision-making mathematics in infrastructure, epidemiology, and multiagent systems.

• Software Engineering
• Software Performance Engineering
• Geographic Information Systems (GIS)
• +۴ مورد دیگر

Dr. Eng. Tomasz Babczyński is a researcher at Wrocław University of Science and Technology, affiliated with the Faculty of Computer Science and Telecommunications and the Department of Technical Computer Science. Software Engineering (specializing in Software Performance Engineering) Geographic Information Systems (GIS) software Image processing and pattern recognition (focusing on handwritten document analysis) His research spans interdisciplinary applications of computer science, including: Railway systems dependability analysis (ERTMS/ETCS protocols) Historical landscape modeling using GIS Multiagent system performance evaluation for power systems Advanced techniques for line segmentation in handwritten documents Recent publications (2020-2024) demonstrate expertise in tensor voting algorithms, data heterogeneity challenges, and safety-critical system analysis. His work combines theoretical computer science with practical applications in transportation, energy, and historical information systems. Contact: tomasz.babczynski@pwr.edu.pl

Ilai Bistritzمشاهده پروفایل

استادیار

• Game Theory
• Distributed Control
• Multiagent Learning
• +۱۰ مورد دیگر

Dr. Ilai Bistritz is an Assistant Professor at the School of Industrial and Intelligent Systems Engineering and School of Electrical and Computer Engineering , Tel Aviv University , with a PhD in Electrical Engineering (2023) from Stanford University under Nicholas Bambos . His research bridges Game Theory , Distributed Control , and Multiagent Learning , focusing on decentralized decision-making in networked systems like autonomous vehicles , smart grids , and epidemic modeling . His work addresses challenges in Distributed Optimization where agents operate with limited communication and feedback, such as in multiplayer bandits and delayed adversarial environments . He has developed algorithms for max-min fairness , non-myopic informational cascades , and delay-robust regret minimization , achieving theoretical breakthroughs in Networked Artificial Intelligence . Scientific awards include the Best Student Paper Award at IEEE WCNC 2018 and Best Student Paper Finalist at WODES 2020 . His research emphasizes privacy-preserving protocols, scalable architectures, and applications in health monitoring , energy systems , and wireless networks .

• Time delayed systems
• Cooperative control
• Infinite delayed systems
• +۴ مورد دیگر

Xiang Xu is an Associate Professor at the School of Automation and Intelligent Manufacturing, Southern University of Science and Technology (SUSTech) in Shenzhen, China. He joined SUSTech in December 2022 as an Associate Professor in the Department of Electronic and Electrical Engineering, following a postdoctoral fellowship at City University of Hong Kong from 2018 to 2021. His educational background includes: Ph.D. in Mechanical and Biomedical Engineering from City University of Hong Kong (2014-2018) Bachelor of Engineering in Automation from Nanjing University of Science and Technology (2010-2014) Xu's research focuses on advanced control theory, particularly addressing complex challenges in time-delayed systems. His work has significantly contributed to the understanding and control of systems with infinite delays, which are notoriously difficult to analyze and stabilize. He has developed novel Lyapunov-based methods and predictor feedback techniques that have extended the theoretical foundations of control theory for systems with unbounded delays. His research bridges theoretical advancements with practical applications in multi-agent systems, traffic control, and reinforcement learning. Xu has been recognized with several prestigious awards, including: National Science Fund for Excellent Young Scholars (Overseas) in 2022 Shenzhen Peacock Plan Class C in 2022 2023 All-Wheel Drive System Theory and Application Conference Outstanding Young Paper Award City University of Hong Kong Outstanding Doctoral Dissertation Award in 2018 Shortlisted for the 2018 Guan Zhaozhi Award Xu has mentored four Ph.D. students during his postdoctoral period, all of whom have published papers in top control journals. Two of his mentees have secured assistant professor positions at other universities. His research has attracted significant funding, including two RGC grants totaling over HK$1.7 million that his supervisor successfully applied for based on Xu's work. He is actively recruiting PhD students, postdoctoral fellows, and research assistants to continue his research in time-delay systems and multi-agent control. Xu leads a research group focused on control theory at SUSTech, with ongoing projects in multi-agent systems, time-delay systems, and partial differential equations. His team collaborates with leading researchers worldwide, including IEEE Fellow Miroslav Krstic from the University of California, San Diego. The research group provides comprehensive training for students and postdocs, with strong support for publishing in top-tier journals and attending international conferences.

Britton D. Wolfeمشاهده پروفایل

استاد

• Machine Learning
• Computer Security
• 3D Vision
• +۳ مورد دیگر

Britton D. Wolfe is a Professor of Computer Science at Grove City College's College of Engineering and Business. His career spans academic research, industry collaboration, and teaching across multiple CS domains. Ph.D. in Computer Science and Engineering, University of Michigan (2009) M.S. in Computer Science and Engineering, University of Michigan (2005) B.S. in Computer Science, Carnegie Mellon University (2003) Research focuses on applying machine learning to diverse challenges: Android malware detection using Google Play data, 3D vision for robotics, and collaborative tracking systems for biological research. He develops deep learning techniques for ant-tracking robots in natural habitats, working with students to refine computer vision algorithms. His publications (2005-2017) demonstrate sustained expertise in malware analysis , tracking algorithms , and predictive state modeling . Current work combines AI with biology studies through interdisciplinary robotics projects. Contact: bdwolfe@gcc.edu

Jamshed Iqbalمشاهده پروفایل

مدرس ارشد

• Robotics
• Mechatronics
• Control Systems
• +۳ مورد دیگر

Dr. Jamshed Iqbal is a Senior Lecturer at the University of Hull , affiliated with the School of Digital and Physical Sciences and the Computer Science department . With over two decades of experience in academia and industry, he leads the BEng/MEng Robotics and AI program and contributes to pedagogical innovation via the CDIO framework.