جست‌وجوی استاد و پژوهشگر

Tanja Kaiserمشاهده پروفایل

پژوهشگر

• Multi-Robot Systems
• Evolutionary Robotics
• Autonomous Intelligent Mobile Robot Systems
• +۴ مورد دیگر

Tanja Kaiser is a Senior Researcher in the Department of Computer Science & Artificial Intelligence at the University of Technology Nuremberg, Germany. She leads a junior research group and serves as an Ada Lovelace Distinguished Research Fellow at ScaDS.AI Dresden/Leipzig and Technische Universität Dresden. Her work spans evolutionary robotics, swarm intelligence, and collective behavior in autonomous systems. Dr.-Ing., Computer Science, University of Lübeck (2022) M.Sc., Computer Science, Technical University of Berlin (2017) B.Sc., Computer Science, DHBW Stuttgart (2014) Kaiser focuses on multi-robot systems and surprise minimization in swarm robotics. Her research explores evolutionary algorithms, self-organization, and autonomous decision-making, with applications in UAV tracking and onboard manipulation behaviors. Recent publications emphasize dynamic collective behaviors and task-independent behavior characterization. Kaiser’s scientific contributions include awards like the Bernd Fischer Prize (2023). She actively contributes to academic equity as a representative for the equity of women in sciences and arts at the University of Technology Nuremberg.

• Edge-Cloud Computing
• Resource Optimization
• Applied Machine Learning
• +۵ مورد دیگر

Jia Hu is an Associate Professor in Computer Science at the University of Exeter. He holds a PhD in Computer Science from the University of Bradford (2010), and M.Eng/B.Eng degrees in Electronic Engineering from Huazhong University of Science and Technology. His research specializes in edge-cloud computing, federated learning, and AI-driven optimization for networks and IoT systems. Research Interests: Hu's work spans resource optimization, applied machine learning (particularly in distributed settings), network security, blockchain integration, and intelligent systems for electric vehicles and Industry 4.0. His recent projects focus on federated edge AI, 6G-enabled industrial IoT, and real-time federated learning via hardware-algorithm co-design. Publications: His 150+ papers emphasize federated learning, edge computing, and reinforcement learning applications. Recent works (2020–2025) show a strong trend toward optimizing AI at the network edge, with themes like digital twins, blockchain security, and EV-integrated systems dominating. Awards & Recognition: Best Paper Awards: IEEE SOSE'16, IUCC'14 Outstanding Service & Leadership Awards for IEEE conferences Top 4% contributor to EPSRC Peer Review Fellow of the Higher Education Academy (HEA) Grants & Projects: Secured €4.7M+ funding from EU Horizon, EPSRC, and Royal Society for projects including: SAILING (Secure AI for Smart Internet-of-Energy, €3.6M) REFINE (Real-time Air Quality Monitoring with UAVs, €897K) SustainAIRA6G (Energy-Efficient AI for 6G Networks, £118K) Advising: Supervised 12 PhD students to completion; currently mentoring 7 students in federated learning, edge computing, and AIoT.

Jose Paolo Talusanمشاهده پروفایل

پژوهشگر

• Smart Transportation Systems
• Cyber-Physical Systems
• Middleware
• +۴ مورد دیگر

Dr. Jose Paolo Talusan is a Research Scientist at the Department of Computer Science and Computer Engineering , Vanderbilt University, specializing in smart transportation systems , distributed computing , and cyber-physical systems . He is affiliated with ScopeLab , a research group focused on smart cyber-physical systems. Education: PhD from Nara Institute of Science and Technology, Japan (2020) Research Interests: His work addresses challenges in urban mobility through middleware architectures, optimization algorithms, and machine learning. Key areas include incident detection in transportation systems, privacy-preserving route planning, and vehicle-to-building charging optimization. Publication Trends: Recent publications focus on real-time transit optimization (2024-2025), leveraging reinforcement learning for heterogeneous agents in vehicle-to-building systems, and privacy-aware route planning in smart cities. His work integrates IoT , edge computing , and graph neural networks to tackle imbalanced data and sparsity issues in transit analytics. Labs & Teams: Actively contributes to ScopeLab at Vanderbilt University, collaborating on interdisciplinary projects with researchers in computer science, electrical engineering, and urban planning.

• Human Factors
• Cognitive Science
• Cyberpsychology
• +۷ مورد دیگر

Professor Phillip Morgan is a leading academic in Human Factors and Cognitive Science at Cardiff University's School of Psychology, holding a Personal Chair since 2020. He directs the Human Factors Excellence (HuFEx) Research Group and serves as Director of Research for the Centre for Artificial Intelligence, Robotics & Human-Machine Systems (IROHMS) . Since March 2019, he has been seconded part-time to Airbus as Director of their Centre of Excellence in Human-Centric Cyber Security . BSc (Hons) Psychology, Cardiff University (2001) PGDip Research Methods, Cardiff University (2002, Distinction) PhD in Cognitive Psychology, Cardiff University (2005) PGCHE, University of Wales (2012, Distinction) His research merges Human Factors with Cognitive Science to address real-world challenges in: Human-machine interaction in autonomous systems Cyberpsychology and security behavior Transport human factors (connected/autonomous vehicles) Interruption/distraction effects on cognition Trust and blame dynamics in AI systems Industry 5.0 human-centric manufacturing Recent publications show AI and cybersecurity as dominant themes, with specific focus on autonomous vehicle interfaces, human fatigue analysis, and trust calibration in human-machine systems. His work integrates behavioral experiments, driving simulators, and human-state monitoring. Scientific Recognition: Associate Fellow of the British Psychological Society Best Paper Award at AHFE 2021 Member of Experimental Psychology Society Keynote speaker at multiple international conferences As supervisor, he leads projects on cybersecurity frameworks, fatigue detection, and human-AI interaction. His grants portfolio exceeds £37m from sources including EPSRC, ESRC, Airbus, and Wellcome Trust. Current supervisees include Victoria Marcinkiewicz, George Raywood-Burke, and Nicola Turner.

• Cooperative Robotic Systems
• Multi-Robot Systems
• Human-Robot Collaboration
• +۷ مورد دیگر

Luis Merino is an Associate Professor at the School of Engineering, Universidad Pablo de Olavide (UPO), Seville, Spain. He founded and leads the Service Robotics Laboratory and contributed to establishing the Systems Engineering and Automation division at UPO. He served as Vice-Dean for five years and currently coordinates the Computer Science degree program. Education: Ph.D. in Robotics from the University of Seville (2007), supervised by Anibal Ollero. Research: Focuses on cooperative robotic systems, human-robot collaboration, localization/navigation techniques, and machine learning in social robotics. His work includes leading 2 H2020, 4 FP7, 3 National R&D, and 3 Andalusian regional projects. Notable projects: MBZIRC 2020 (PI), collaboration with Honda Research Institute Japan, and EU-funded initiatives. He advocates for open-source code/datasets and industry technology transfer. Scientific Awards: ABB Award to the Best Doctoral Dissertation on Robotics (2007) Best Paper Award at ROBOT2019 Professional Roles: Associate Editor for Image and Vision Computing and IEEE Robotics and Automation Letters . Serves on ICRA/IROS conference program committees. Grant reviewer for FONDECYT (Chile), SBIR (USA), and ERC.

Justin Bradleyمشاهده پروفایل

دانشیار

• Artificial Intelligence and Intelligent Agents
• Cyber-Physical Systems
• Embedded and Real-Time Systems
• +۳ مورد دیگر

Justin Bradley is an Associate Professor in the Computer Science Department at North Carolina State University. Previously, he held the position of Richard L. and Carol S. McNeel Associate Professor of Computing in the School of Computing at the University of Nebraska-Lincoln. His educational background includes: Ph.D. in Aerospace Engineering from the University of Michigan (2014) M.S. in Aerospace Engineering from the University of Michigan (2012) M.S. in Electrical Engineering from Brigham Young University (2007) B.S. in Computer Engineering from Brigham Young University (2005) Dr. Bradley's research focuses on cyber-physical systems with particular emphasis on control, autonomy, software, and computing for aerospace vehicles. A key theme in his work involves developing algorithms that can dynamically adjust their resource utilization in response to uncertainty while maintaining performance requirements. His research spans several critical areas including Artificial Intelligence and Intelligent Agents, Cyber-Physical Systems, and Embedded and Real-Time Systems, with applications primarily in unmanned aircraft systems (UAS) operating in challenging environments like wetlands and fire-prone areas. His scientific achievements have been recognized with prestigious awards including: 2021 NSF CAREER award AIAA Associate Fellow designation Dr. Bradley has been actively involved in research funding and mentoring. His NSF CAREER award (NSF-2047971) supports work on "co-regulation" algorithms for unmanned aircraft systems. He has co-directed research labs including the MAGICC lab at BYU, the A2Sys lab at the University of Michigan, and the Nebraska Intelligent MoBile Unmanned System (NIMBUS) lab since 2015. His research group focuses on developing performance-adjustable, resource-aware algorithms for autonomous systems, with applications in environmental monitoring, wetland studies, and fire management. His educational efforts target K-12 through adult engagement to expand the cyber-physical systems educational pipeline. His laboratory work centers around the development of the Co-regulated Hybrid Systems (CHS) framework, Co-regulated Real-Time Kernel (CRTK), and co-regulated Markov Decision Process (MDP) for resource-aware autopilots. These technologies enable unmanned systems to dynamically reallocate computing resources while maintaining mission objectives, particularly valuable in complex environments like rainforests where systems must transition between surveillance, sampling, and sensor emplacement tasks.

Mirgita Frasheriمشاهده پروفایل

استادیار

• Autonomous Systems
• Multi-Agent Systems
• Digital Twins
• +۳ مورد دیگر

Mirgita Frasheri is a Tenure Track Assistant Professor at the Department of Electrical and Computer Engineering, Aarhus University. Her research focuses on autonomous systems, multi-agent systems, and digital twins, particularly in the context of cyber-physical systems and robotics. Education: PhD in Computer Science from Mälardalen University (2020), specializing in Modelling and Control of Collaborative Adaptive Autonomous Agents. Mirgita's research explores the application of digital twins for enhancing cyber-physical systems, fault tolerance mechanisms in autonomous robotics, and federated digital twin platforms. Her work bridges theoretical advancements with industry-oriented solutions. Recent publications highlight trends in systematic reporting for digital twins, federated architectures, and autonomous agent integration in sensor networks. She is actively involved in collaborative projects, including agricultural robotics and CPS optimization. She participated in the 20th Overture Workshop and contributes to interdisciplinary research in digital twin services and mobile sensor networks.

• Wireless Networking
• Network Security
• Broadband Wireless Access
• +۲ مورد دیگر

Anthony H. Smith serves as an Associate Professor in the Computer and Information Technology Department at Purdue University's Polytechnic Institute, leveraging over 15 years of technical expertise in LAN/WAN/wireless network design, implementation, and security. His career bridges academia and industry through applied research and active consultancy in wireless technologies. His educational foundation includes: MS in Technology from Purdue University (1994) BS in Business Administration from Wittenberg University (1984) Professor Smith's research centers on wireless networking security and innovative antenna systems , with significant contributions to broadband wireless access and network design. His work uniquely integrates academic theory with real-world applications, particularly through consultancy projects focused on wide-area wire-line replacement strategies and penetration testing. Key themes include the intersection of robotics and wireless networks for self-organizing systems. Analysis of his 15 publications (2007-2010) reveals concentrated expertise in wireless security vulnerabilities (e.g., evil twin attacks, EAP protocol flaws), 802.11 performance optimization, and robotics-driven network formation. His scholarship consistently addresses industry-relevant challenges while advancing wireless curriculum development for network engineering education. His scholarly impact is recognized through multiple Polytechnic Research Awards: Polytechnic Research Award (October 2024) Polytechnic Research Award (March 2024) Polytechnic Research Award (December 2023) Polytechnic Research Award (November 2023) While specific student advising details are unavailable, Professor Smith maintains strong industry connections through AHSmith Consulting (2005-2012) and prior roles at NetLink Technologies and Lennox International. His grant activity isn't documented, but his consultancy demonstrates sustained applied research funding. Professional engagement includes IEEE membership (2005-2012) and Microsoft Certified Systems Engineer certification. His operational framework combines academic instruction with hands-on network design for corporate/municipal clients, reflecting a practitioner-scholar approach where research directly informs real-world wireless solutions. Current focus areas likely extend his antenna-as-sensor innovations toward next-generation mobile broadband architectures.

• Robotics
• Multi-Agent Systems
• Crowd Simulation
• +۶ مورد دیگر

Stephen J Guy is an Associate Professor in the Department of Computer Science and Engineering at the University of Minnesota's College of Science and Engineering. His research focuses on robotics, multi-agent systems, and human-computer interaction with applications in biomedical engineering and digital entertainment. University of Minnesota, College of Science and Engineering Department of Computer Science and Engineering Active research in multi-agent navigation and biomedical applications Dr. Guy's work spans robotics and computer science, with particular emphasis on multi-agent navigation , crowd simulation , and path planning . His research also extends into biomedical applications such as motion analysis for developmental disorders and digital game design for interactive entertainment. Recent publications demonstrate expertise in motion tracking and behavioral analysis. His work on augmented reality games (2024) and multi-agent coordination (2020) represent key contributions to human-computer interaction and autonomous robotics. No specific scientific awards were identified in the scraped data. Dr. Guy collaborates across disciplines including biomedical engineering (e.g., Tourette Syndrome research) and retail analytics (trajectory pattern analysis with Tesco PLC). He serves as Principal Investigator for multiple NSF-funded projects related to robotics and human well-being.

• Developmental Robotics
• Multi-agent Systems
• Artificial Intelligence
• +۳ مورد دیگر

François Suro is a Lecturer at the University Institute of Technology, Valence within Grenoble Alpes University. He is affiliated with the LCIS laboratory and conducts research as part of the Co4Sys team. He earned his PhD in Computer Science from the University of Montpellier in 2020, focusing on epigenetic learning in multi-agent systems. Research Focus: His work centers on developmental approaches to artificial intelligence, with three primary domains: Progressive structuring of agent behaviors through hierarchical architectures (MIND framework) Acquisition and grounding of symbolic representations in embodied systems Emergence mechanisms for collective behaviors in agent societies Key application areas include robotics, social simulations, and cognitive modeling. Publication Trends: Recent works (2019-2021) demonstrate consistent exploration of hierarchical control architectures for autonomous agents, progressive learning methodologies, and collective behavior emergence in multi-agent environments. Dominant themes include developmental robotics frameworks, modular skill composition, and agent-based social simulations using platforms like NetLogo. Laboratory Context: As part of the LCIS laboratory's Co4Sys research team, he contributes to projects involving intelligent systems design and multi-agent coordination frameworks.

• Robotics
• Autonomous System Design
• Control Theory and Applications
• +۳ مورد دیگر

Abdurrahman Yılmaz is an Assistant Professor at Istanbul Technical University's Department of Control and Automation Engineering within the College of Electrical-Electronics. His career spans academic and industrial roles, including a Research Assistant position at Istanbul Technical University (2018-2022) and Test Rig Design Engineer at ASELSAN INC. (2014). Education: PhD in Control and Automation Engineering (Istanbul Technical University, 2014-2022) MSc in Mechatronics Engineering (Yildiz Technical University, 2014-2017) BSc in Electronics Engineering (Istanbul Technical University, 2009-2014) Double Major in Control and Automation Engineering (Istanbul Technical University, 2011-2014) Research Interests focus on Robotics, Autonomous System Design, and Control Theory. His work includes localization frameworks for autonomous mobile robots, adaptive control algorithms for quadcopters, and soft haptic sensing technologies. Recent research explores digital twin simulators and quadruped robot dynamics. Scientific Output trends highlight advancements in mobile robot navigation, industrial automation, and autonomous systems. Publications span journals like Journal of Field Robotics and conferences including TAROS and RoboSoft. Awards: The Most Successful Doctoral Thesis Award of 2022 (University, 2023) 1st Water Management Awards (Ministry of Forestry and Water Affairs, 2019) Collaborations extend to international researchers in robotics and control systems. He serves as PI for the project "Development of a Design-Aiding Analysis Tool for Four-Legged Robots" (2023-2024).

• computational multiscale modeling
• digital twin development
• applied artificial intelligence
• +۷ مورد دیگر

Davood Pourkargar is an Assistant Professor in the Tim Taylor Department of Chemical Engineering at Kansas State University. He is also a Graduate Faculty Member at the Food Science Institute and a Faculty Researcher at the Johnson Cancer Research Center. His work focuses on integrating data with first-principle models to understand complex systems across multiple scales. Ph.D. in Chemical Engineering from Pennsylvania State University (2015) M.S. in Process Simulation and Control from Sharif University of Technology (2010) B.S. in Chemical Engineering from Sharif University of Technology (2008) His research interests span computational multiscale modeling, digital twin development, applied artificial intelligence, and optimization-based control of complex process networks. Dr. Pourkargar's work integrates process systems engineering with artificial intelligence to address challenging problems in chemical, biological, energy, and food systems. He develops intelligent frameworks for controlling complex process networks, designing cyber-physical architectures for smart manufacturing, and advancing system identification using machine learning and process data analytics. A significant aspect of his research involves physics-informed machine learning applied to cancer dynamics modeling and drug distribution in the human body. Dr. Pourkargar's publication record shows a strong focus on predictive modeling and control of chemical processes, particularly ammonia synthesis systems, polysilicon reactor systems, and food extrusion processes. His recent work increasingly incorporates machine learning techniques, especially transformer architectures and physics-informed approaches, applied to both traditional chemical processes and emerging areas like organ-on-a-chip systems for drug discovery. 2024 Carl R. Ice College of Engineering Outstanding Assistant Professor Award NSF EPSCoR Research Fellowship 2023 Kansas EPSCoR First Award AFOSR Faculty Fellowship Big XII Faculty Fellowship Robert F. Smith School Distinguished Junior Researcher Award from Cornell University (2017) O. Hugo Schuck Best Paper Award (2014) Dr. Pourkargar has successfully mentored numerous graduate students through their master's and doctoral research, with several receiving departmental and college-level awards. His research has been supported by significant grants from the National Science Foundation, Kansas EPSCoR, and K-State's Global Food Systems initiative. His lab has presented extensively at major conferences including AIChE Annual Meetings and American Control Conferences. The Intelligent Systems and Process Systems Laboratory (ISPSL) led by Dr. Pourkargar operates computational and experimental facilities in Durland Hall. The lab is expanding into robotic additive manufacturing and autonomous biomanufacturing, supported by research infrastructure grants. The group maintains active collaborations with the Johnson Cancer Research Center and the Terasaki Institute for Biomedical Innovation.

Tingjun Leiمشاهده پروفایل

استادیار

• Bio-inspired Artificial Intelligence
• Robotics and Autonomous Systems
• Optimization and Evolutionary Computation
• +۳ مورد دیگر

Dr. Tingjun Lei is an Assistant Professor at the University of North Dakota's School of Electrical Engineering and Computer Science (SEECS). With a Ph.D. in Electrical and Computer Engineering from Mississippi State University (2023), his research focuses on bio-inspired artificial intelligence , robotics and autonomous systems , and human-autonomy teaming (HAT) . Research Interests : Bio-inspired AI for robot cognition Multi-robot coordination and control Graph-based path planning algorithms Human-autonomy collaborative systems Intelligent transportation frameworks Recent Article Trends span robotics , bio-inspired computation , and machine learning , with specific focus areas in swarm intelligence , cognitive mapping , multi-agent safety , and adaptive navigation systems . Scientific Awards : 2025 Honorable Mentions (IJCNN 2025) 2025 Early Career Scholars Award (UND) 2024 Best Paper Awards (Biomimetic Intelligence & Robotics, ASEE ECE Division) 2022-2023 ECE Best Graduate Researcher (Mississippi State) Students : Ashwin Mukunda Devanga (Ph.D.), Samuel Steen (Ph.D.), and Justin London (Ph.D.)

Nicole Abaidمشاهده پروفایل

دانشیار

• Dynamical Systems
• Control Theory
• Multi-Agent Systems
• +۵ مورد دیگر

Nicole Abaid is an Associate Professor in the Department of Mathematics at Virginia Tech, affiliated with the College of Science. Her research integrates dynamical systems, control theory, and robotics to study collective behavior in biological and engineered systems. She explores biologically-inspired models, such as bat swarms and brain networks, to develop applications in robotics and environmental monitoring. Her work combines agent-based modeling, network analysis, and data-driven approaches to understand interactions in animal groups and robotic systems. Notable projects include analyzing bat echolocation for acoustic sensing in robotics and studying stress effects in human crowd dynamics during emergencies. She has also contributed to piezoelectric energy harvesting and ex vivo muscle stimulation via Functional Electrical Stimulation (FES). Abaid’s research has been supported by grants like the NSF CAREER Award for collective behavior studies. She collaborates on interdisciplinary projects, including outreach programs in biomimetics and robotics for K-12 education. Her publications span journals and conferences, emphasizing applications in ecology, robotics, and control systems.

• Cybersecurity
• Machine Learning
• Network Security
• +۶ مورد دیگر

Dr. Zhiyuan Tan is an Associate Professor in the School of Computing at Edinburgh Napier University (ENU), specializing in cybersecurity research. He holds a PhD in Computer Systems from the University of Technology Sydney (UTS), Australia (2014), an MEng from Beijing University of Technology, China (2008), and a BEng with high distinction from North-eastern University, China (2005). Before joining ENU in 2016, Dr. Tan held research positions at the University of Twente (Netherlands), University of Technology Sydney (Australia), and La Trobe University (Australia). Dr. Tan's research focuses on cybersecurity, machine learning, data analytics, virtualisation, and cyber-physical systems. His work has resulted in over 44 scholarly publications with an H-Index of 13 and more than 830 citations according to Google Scholar. His recent publications demonstrate a continued focus on network security, intrusion detection systems, and the application of machine learning techniques to cybersecurity challenges, with publications spanning from 2022-2025 in top venues including IEEE Transactions and international conferences. Dr. Tan has received significant research funding, including AUD 27,800 from CSIRO and UTS for autonomous network intrusion detection research and £6,987 from ENU for securing future 5G health care systems. His research has been recognized with awards including the National Research Award 2017 from the Research Council of the Sultanate of Oman, a Best Paper Award, and the Kaspersky Lab's Annual Student Cyber Security Conference Finalist Award. National Research Award 2017 from the Research Council of the Sultanate of Oman Best Paper Award Kaspersky Lab's Annual Student Cyber Security Conference Finalist Award Dr. Tan has mentored 9 PhD students over the past 5 years, with 6 successfully completing their studies. His students have produced 12 journal and 10 conference publications. He has also served as an editorial board member for international journals, organized special issues, and participated as a technical program committee member for major international conferences. Dr. Tan is currently recruiting PhD students for research projects on network security, adversarial machine learning for anomaly/malware detection, virtualization security, and IoT security.