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Justin BradleyView profile

Associate Professor

• Artificial Intelligence and Intelligent Agents
• Cyber-Physical Systems
• Embedded and Real-Time Systems
• +3 more

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.

• Concurrency
• Real-Time Systems
• Distributed Systems
• +3 more

Lukasz Ziarek is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, and serves as the Associate Dean for Academic Affairs in the School of Engineering and Applied Sciences. His research focuses on concurrency, real-time systems, distributed systems, and formal verification. He holds a PhD from Purdue University (2011) and a BS from the University of Chicago (2003). His research explores topics such as real-time Java implementations, session types for distributed protocols, and visual debugging techniques. Recent work includes formal models for secure multiparty computation, IoT device validation, and optimizing visual SLAM systems for robotics applications. He has contributed to frameworks like Juav (a Java-based UAV autopilot) and RTDroid (a real-time Android extension). Ziarek has received notable awards including the 2023 IEEE Technological Innovation Award, 2022 Meyerson Teaching Award, and 2018 NSF CAREER Award. His grants include collaborative research on UAV software infrastructure and real-time communication protocols. He actively develops tools like PTDETECTOR for JavaScript library analysis and Anodize for mixed-criticality systems. His work integrates formal methods with practical systems, addressing challenges in embedded systems security, compiler optimization, and real-time programming language design. He maintains a lab focused on advancing reliable software for autonomous systems and distributed computing environments.

Haiyang ChaoView profile

Associate Professor

• Unmanned Aircraft Systems (UAS)
• Control Systems Engineering
• Remote Sensing
• +4 more

Haiyang Chao is an Associate Professor at the Department of Aerospace Engineering, College of Engineering, University of Kansas. His research focuses on Unmanned Aircraft Systems (UAS) with emphasis on control systems, wind estimation, remote sensing, and cooperative UAV operations. Recent work includes FireCrowdSensing for prescribed fire monitoring Wake vortex hazard estimation for airport UAS operations Thermal imaging for fire spread measurement Vertical wind velocity analysis in fire plumes System identification techniques for flying-wing UAVs Honors include the 2016 Summer Faculty Fellowship at Air Force Research Lab. He leads the Cooperative Unmanned Systems Lab (CUSL) and collaborates with NASA on gust sensing projects. Teaching interests include Avionics, Control Systems, and Autonomous Aerospace Vehicles.

Tetsuya SatoView profile

Assistant Professor

• Human Factors Psychology
• Automation Trust
• Attention Allocation
• +3 more

Tetsuya Sato is an Assistant Professor at Wichita State University's Fairmount College of Liberal Arts and Sciences, affiliated with the Human Factors Psychology Program. His research focuses on human-automation trust, attention allocation in multitasking environments, and advanced air mobility systems. He leads the SATO LAB, which explores topics like automation trust dynamics, cognitive workload management, and human-AI collaboration. Education: Ph.D. (2020), M.S. (2020), and B.S. (2018) in Psychology from Old Dominion University His work bridges cognitive psychology and engineering, addressing challenges in aviation autonomy and unmanned vehicle operations. Recent studies include entropy-based gaze analysis for attention measurement and meta-analytic approaches to trust-attention relationships. Current projects emphasize developing frameworks for human-centered AI and managing attentional resources in complex systems. The SATO LAB actively recruits undergraduates for Fall 2025.

• Artificial Intelligence
• Robotics Innovation
• Digital Innovation
• +3 more

Antti Lyyra is a Lecturer in Information Management at Loughborough Business School, part of Loughborough University. His work focuses on how artificial intelligence (AI), robotics, and digital technologies transform organizations and society. He holds a PhD from the London School of Economics (LSE), a BSc/MSc from Aalto University (Finland), and is a Fellow of the Higher Education Academy (FHEA). Dr Lyyra's research explores innovation dynamics in AI/robotics, contrasting them with traditional digital innovations like communication systems and modular manufacturing. His teaching includes digital innovation and information management modules for undergraduates and postgraduates. He previously worked at Oxa (autonomous vehicle developer) and LSE as a Fellow, and has over eight years in technology consulting at Accenture and Deloitte, specializing in enterprise systems for global logistics and finance sectors. His research trends emphasize cyber-physical systems (e.g., Tesla Autopilot), trust in autonomous technologies, and the sociotechnical implications of AI. His articles highlight interdisciplinary themes spanning engineering, business strategy, and ethics. Lyyra's career bridges academic research, industry R&D, and business strategy. He has advised on product lifecycle management in automotive industries and contributed to open-source robotics frameworks like the Robot Operating System.

İsmail BayezitView profile

Assistant Professor

• Unmanned Aerial Vehicles
• Flight Control Systems
• Autopilot Design
• +3 more

Dr. İsmail Bayezit serves as an Assistant Professor in the Department of Aeronautical Engineering at Istanbul Technical University (ITU), Turkey, with active research since 2007. His work bridges aerospace and marine engineering domains, focusing on unmanned systems and control technologies. With an h-index of 8 and 321 Scopus citations across 33 research outputs, he has secured 6 major research projects including VTOL system development and marine craft autonomy initiatives. His research fingerprint reveals dominant expertise in Quadcopter Engineering (100%), Motion Control (81%), and Unmanned Aerial Vehicle systems (80%). He specializes in advanced control methodologies including extremum-seeking control, LQR techniques, and distributed control strategies. Current work extends into AI-integrated navigation systems and energy-optimized flight performance, with significant crossover applications in marine craft control and underwater acoustics. Recent publications (2024-2025) demonstrate three converging trends: optimization of electric multirotor performance through energy-aware control, neural network-assisted navigation for GPS-denied environments, and cross-domain applications of control theory to both aerial and marine systems. His work increasingly integrates artificial intelligence with traditional control frameworks while maintaining strong experimental validation through physical prototypes. Bayezit has supervised 21 students and led 6 research projects from 2017-2025, including EU-funded initiatives on VTOL systems and national projects on UAV education sets. His project portfolio shows consistent progression from fundamental control theory (2017-2019) toward applied AI integration (2023-2025), with recent work focusing on autonomous marine craft instrumentation and next-generation UAV performance optimization.

Ketan P. DetrojaView profile

Associate Professor

• Control Theory
• State Estimation
• Fault Diagnosis
• +9 more

Ketan P. Detroja is an Associate Professor in the Department of Electrical Engineering at Indian Institute of Technology Hyderabad . With a Ph.D. from IIT Bombay (2006) and a specialization in Multivariable Control, Distributed State Estimation, and AI/ML for Control Applications , his research focuses on ensuring fault-tolerant and economical operation of microgrids , developing distributed Kalman filtering techniques , and applying machine learning to process monitoring and control . Education: B.E., D. D. Institute of Technology, Gujarat, India Ph.D., IIT Bombay, 2006 Research Interests span Advanced Process Control, Fault Detection and Diagnosis, Cooperative Control, Microgrid Optimization and Control , and Hardware-Software Design for Control Systems . His work addresses challenges in data-driven process monitoring , distributed state estimation , and machine learning-based controller design , particularly for large-scale systems. Scientific Contributions include innovative approaches to inverse-free Kalman filters , reinforcement learning-based PI controllers , and data reduction algorithms for fault diagnosis. His publications reflect a focus on control theory, optimization, and machine learning integration , with applications in power systems, wind energy, and fault diagnostics . Scientific Awards: Best Paper Award at ADCONIP - 2011 Best Paper Award at DYCOPS-2013 Advising has been a significant part of his career, with supervision of Ph.D. students working on topics like fault detection in induction motors , microgrid scheduling , and adaptive control using fuzzy logic . His M.Tech students have explored areas such as visual object tracking, battery SOC estimation, and wind farm control , many of whom are now in prominent roles across academia and industry.

• Control Systems
• Convex Optimization
• Aerospace Systems
• +7 more

Dr. Emmanuel Prempain is an Associate Professor at the School of Engineering, University of Leicester. His research focuses on control systems, convex optimization, and their applications in aerospace systems such as helicopters, re-entry vehicles, and UAVs. He specializes in robust control methodologies like gain scheduling, fixed-order synthesis, and Linear Matrix Inequality (LMI) frameworks. Recent work emphasizes energy-efficient control strategies for robotic arms and quadrotor UAVs, leveraging iterative learning control (ILC) and hybrid optimization algorithms. His contributions include model predictive control (MPC) designs for nonlinear systems and fault-tolerant switched control for multivariable systems. Key Technologies: Robust control, MPC, ILC, UAV control, aerospace systems Applications: Autopilot design, robotic trajectory tracking, energy optimization Dr. Prempain has developed a 2DoF Twin Rotor MIMO system for educational and research purposes, demonstrating practical applications of advanced control theories. His publications span over two decades, reflecting a sustained commitment to advancing control system methodologies.

• Active Debris Removal
• Flight Control Systems
• Unmanned Aerial Vehicles (UAVs)
• +5 more

Dr. Jason Forshaw is a Research Fellow II at the Surrey Space Centre, University of Surrey. He holds a PhD in Electronics Engineering from the same institution, an MS in Aeronautics and Astronautics from Stanford University, and an MEng in Aerospace Engineering from the University of Sheffield. His career includes roles at Rolls-Royce, BAE Systems, and QinetiQ, where he led the QinetiQ Eye-On UAV project. His research focuses on active debris removal technologies, flight control systems for UAVs and satellites, and experimental robotics. Education: MEng (Hons) in Aerospace Engineering, University of Sheffield (2008) MS in Aeronautics and Astronautics, Stanford University (2010) PhD in Electronics Engineering, Surrey Space Centre (2013) Research interests include UAV control, debris removal, satellite dynamics, and optimal control algorithms. He led the EU FP7 RemoveDEBRIS mission (€11.3M), demonstrating netting, harpooning, and drag sail technologies. His work on the Intrepid satellite testbed and the Service-Oriented Active Debris Removal (SOADR) project further highlights his contributions to space engineering. Key awards include the IET Undergraduate Scholarship and Sir Basil Blackwell Award. He has managed over 60 staff across 9 partners in RemoveDEBRIS and coordinated a Royal Society exhibition on space debris, featured globally. His technical leadership spans project management, bid support, and dissemination in space research.

Ankit AgrawalView profile

Assistant Professor

• Cyber Physical Systems
• CPS Safety
• Simulation
• +6 more

Dr. Ankit Agrawal serves as an Assistant Professor in the Department of Computer Science within the College of Arts and Sciences at Saint Louis University. His academic journey includes a Ph.D. in Computer Science from the University of Notre Dame (2022), where he worked under Dr. Jane Cleland-Huang. Prior to his current position, he conducted research on drone surveillance systems and human-machine interfaces for search and rescue operations. Dr. Agrawal's research focuses on the intersection of Software Engineering and Safety-Critical Systems, with particular emphasis on Cyber Physical Systems, CPS Safety, and Simulation. His work bridges theoretical foundations with practical applications in autonomous aerial platforms. Current research areas include Software Validation for testing and verification of cyber-physical systems, Simulation modeling of complex socio-technical systems, Requirements Engineering for safety-critical systems, and Human-Computer Interaction design for complex technical systems. His recent publications demonstrate a strong trend toward integrating AI and simulation technologies for validating autonomous drone systems. Research increasingly focuses on human-drone collaboration in emergency response scenarios, safety validation in realistic environmental conditions, and leveraging large language models for automated testing. The work spans both theoretical frameworks and practical tool development, with emphasis on bridging simulation-to-reality gaps. Honorable Mention at CHI Conference 2024 for HIFuzz: Human Interaction Fuzzing for small Unmanned Aerial Vehicles Best Paper at SPLC Conference 2020 for Requirements-Driven Configuration of Emergency Response Missions with Small Aerial Vehicles Fifth Place in Poster Presentation Award at NASA ImaginAviation 2024 Dr. Agrawal actively mentors graduate and undergraduate students through his UAV Research Lab at Saint Louis University. His lab currently supports multiple Ph.D. and Masters students working on projects including DroneReqValidator, DroneResponse, and React-G. The lab has secured research funding for projects related to drone safety validation and human-autonomy teaming, with collaborations including NASA Langley Research Center. Dr. Agrawal has served on program committees for major conferences including ASE, ICSE, and Requirements Engineering. The UAV Research Lab at Saint Louis University investigates software systems for autonomous aerial platforms, with three primary research thrusts: Software Engineering for Autonomous Systems (developing reliable software architectures and testing frameworks), Human-Autonomy Interaction (designing intuitive interfaces for human oversight), and Intelligent Software Systems (building AI-powered solutions for dynamic environments). The lab maintains active collaborations with NASA and emergency response organizations.

Hamid BagheriView profile

Associate Professor

• Software Engineering
• Security of Mobile Devices and IoT Systems
• Formal Methods
• +4 more

Hamid Bagheri is an Associate Professor in the School of Computing at the University of Nebraska-Lincoln, where he conducts cutting-edge research at the intersection of software engineering, security, and formal methods. He also serves as a faculty associate of the Institute for Software Research (ISR) at the University of California, Irvine, and co-directs the ESQuaReD Lab (Engineering Software Quality and Reliability through Deductive methods), which focuses on ensuring software quality through rigorous engineering approaches. Dr. Bagheri's research spans several critical areas including security of mobile devices and IoT systems, scaling formal verification with machine learning, software analysis and testing, dependable cyber-physical systems, and automated program repair and fault localization. His work combines theoretical rigor with practical applications, addressing real-world challenges in software security and reliability through publications in top venues like ICSE, FSE, ASE, and IEEE/ACM Transactions journals. His recent publications demonstrate a strong trend toward integrating machine learning techniques with formal methods to enhance software analysis capabilities. This includes leveraging transformers for database design optimization, neuro-symbolic approaches for certified software synthesis, and large language models for repairing formal specifications, reflecting his ability to adapt to emerging technologies while maintaining a strong theoretical foundation. Dr. Bagheri has received numerous prestigious awards including the EPSCoR FIRST Award, the NSF CISE Career Research Initiation Initiative Award, multiple Distinguished Paper Awards from top conferences, and teaching honors such as the SoC Student Choice Outstanding Teaching Award (2023-2024) and the CSE Outstanding Teaching Award (2020-2021). As an advisor, Dr. Bagheri has mentored several successful PhD students including Mohannad Alhanahnah (who joined Chalmers University as a tenure-track faculty member in Fall 2024) and Clay Stevens (who joined Iowa State University as a tenure-track faculty member in Fall 2023). His research has been supported by significant grants from NSF and other funding agencies, with recent work focusing on automated specification repair, security analysis of IoT systems, and verification of network protocols. The ESQuaReD Lab, which Dr. Bagheri co-directs, brings together a multidisciplinary team focused on addressing critical challenges in software quality and reliability through innovative engineering approaches and formal analysis techniques, with applications spanning mobile security, IoT systems, and cyber-physical systems.

• Marine Control Systems
• Autonomous Vessels
• Robust Control Theory
• +4 more

Zenon Zwierzewicz is a Professor at the Maritime University of Szczecin, Faculty of Mechatronics and Electrical Engineering, where he has been employed since July 1, 1978. His academic career spans over four decades with continuous contributions to marine control systems and autonomous vessel technologies. His research focuses on Marine Control Systems , Robust and Adaptive Control Theory , and Autonomous Vessel Navigation . Key interests include Active Disturbance Rejection Control (ADRC) for ship autopilots, energy-efficient steering systems, path-following algorithms for underactuated vessels, and cybersecurity challenges in autonomous transportation. His work bridges theoretical control methodologies with practical marine applications. Analysis of his 15 most recent publications reveals a clear evolution from classical ship control systems (2010-2018) toward modern challenges in autonomous vessel cybersecurity (2024) and energy optimization (2021). The predominant themes include robustness against environmental disturbances, adaptive parameter estimation for uncertain models, and real-time implementation of nonlinear control strategies. His 2024 work on cybersecurity represents a strategic expansion into emerging threats in autonomous marine systems. Professor Zwierzewicz has collaborated extensively with researchers including Lech Dorobczyński, Sławomir Jaszczak, and Tymoteusz Miller across multiple institutions. His publication record demonstrates consistent productivity in high-impact journals like IEEE Access and Energies, with strong emphasis on practical validation through full-scale ship modeling. His laboratory work centers on marine control system development, particularly ADRC-based autopilot implementations and path-following control validation using realistic hydrodynamic models. Current research directions integrate cybersecurity frameworks with traditional marine control architectures to address next-generation autonomous vessel challenges.

• Power Electronics
• Automotive Electrical Systems
• Renewable Energy Integration
• +5 more

Amar Bousbaine serves as Associate Professor in Power Electronics and Automotive Electrical Systems within the Department of Electronic and Electrical Engineering at De Montfort University's College of Science and Engineering. His academic work bridges theoretical research with practical hardware implementation across power electronics, renewable energy systems, and advanced control engineering. His research spans critical domains including: Power converter design for automotive applications (buck, boost, and buck-boost topologies) Renewable energy integration (solar, fuel cells) with hybrid storage systems (batteries, supercapacitors) Microgrid optimization for electric vehicle charging infrastructure Advanced control strategies for robotics (quadcopters, PUMA robots) using fuzzy logic, sliding mode, and Kalman filtering Thermal modeling of electrical machines and electro-thermal coupling analysis Bousbaine's work emphasizes real-world validation through hardware implementation on platforms like Texas Instruments C2000 microcontrollers, demonstrating strong industry relevance in naval propulsion, cathodic protection, and electric transportation systems. Analysis of his 15 most recent publications reveals dominant research trajectories in power electronics for renewable integration (40%), electric vehicle infrastructure (25%), and robotics control systems (35%). His work consistently combines simulation with experimental validation, particularly in DC-DC converter design, fuel cell applications, and quadcopter control algorithms.

Samuel GuyerView profile

Adjunct Associate Professor

• Programming Languages
• Program Analysis
• Software Reliability
• +7 more

Samuel Guyer is an Adjunct Associate Professor in the Department of Computer Science at Tufts University. His research focuses on programming languages, compilers, program analysis, and runtime systems, with an emphasis on enhancing communication between runtime systems and programmers. He holds a Ph.D. and M.Sc. from the University of Texas at Austin. Education: Ph.D., Computer Science, University of Texas at Austin M.Sc., Computer Science, University of Texas at Austin Research Interests: Dr. Guyer explores techniques to improve software reliability, memory management, and runtime performance. Key areas include domain-specific programming languages, compiler optimizations, and tools for debugging memory managers. His work often addresses challenges in aviation software safety, garbage collection strategies, and object lifecycle analysis. Article Trends: Recent work emphasizes runtime systems analysis (e.g., Permchecker for memory managers, Iceberg for Java concurrency), visualization tools (Heapviz, Garbology), and safety-critical systems (avionics fault monitoring). His research bridges theoretical insights with practical tools for industry-relevant problems. Grants: CAREER: Cooperative Virtual Machines (NSF grant) SHF grants for garbage collection and runtime bug detection Labs/Teams: Collaborates on projects involving compiler infrastructure (e.g., C-Breeze), domain-specific compilers (Broadway), and runtime analysis frameworks. His work often intersects with industry needs for robust software systems.

Kevin GoheenView profile

Lecturer

• Helicopter Dynamics
• Underwater Vehicle Dynamics
• System Identification
• +3 more

Kevin Goheen is a Contract Instructor at Carleton University's Faculty of Engineering and Design, holding a Ph.D. from University College London, United Kingdom. His research focuses on dynamics of helicopters, submarines, curling stones, and management of high-growth companies. He has contributed extensively to control systems design, underwater vehicle dynamics, and marine engineering through publications spanning from 1986 to 1996. Educational Background: Ph.D., University College London, United Kingdom Research Interests: Dr. Goheen’s work bridges mechanical engineering and systems control, with a focus on helicopter hover dynamics, remotely operated vehicles (ROVs), and submarine dynamics. His research often integrates advanced modeling techniques and adaptive control systems, as seen in his studies of slow drift motion in moored structures and system identification for marine vehicles. His unique interest in curling stone dynamics reflects an interdisciplinary approach to engineering problems. Publications Trends: His articles emphasize practical applications of control theory in marine and aerospace contexts, with a strong focus on system identification, adaptive controllers, and time-domain modeling. Key themes include ROV dynamics, helicopter modeling, and robust control strategies for underwater systems. Awards and Grants: No awards or grants explicitly mentioned in the provided text. Advising and Mentorship: No advisee names listed in the available information. Labs and Affiliations: Associated with the Department of Mechanical and Aerospace Engineering at Carleton University, contributing to research in marine dynamics and control systems.