جست‌وجوی استاد و پژوهشگر

Pragathi Praveenaمشاهده پروفایل

پژوهشگر ارشد

• Robotics
• Human-Robot Interaction (HRI)
• Computer Vision
• +۳ مورد دیگر

Pragathi Praveena is a Research Fellow at the Robotics Institute , Carnegie Mellon University. Her work focuses on advancing human-robot interaction, teleoperation systems, and robotics applications in collaborative environments. She leads the Reliable Autonomous Systems Lab , exploring topics such as Petri Net-based robotic system design, generative AI in robotics, and socially engaging robot interfaces. Her research spans autonomous systems , computer vision , and medical robotics applications . Notable contributions include Periscope (a robotic camera system for remote collaboration) and Rex (user-centered repair frameworks for robots). She investigates challenges in telemanipulation control systems, motion generation algorithms, and optimizing collaborative workflows between humans and robots. Key technical trends in her work include formal methods for system design, integration of AI/ML in robotics, and human-centered approaches to interface development. Her publications address both foundational theory (e.g., Petri Nets) and applied solutions (e.g., cinematic automation). Current lab projects emphasize robustness in robotic groupware and cross-modal interaction systems. As part of the Robotics Institute, her work intersects with computer science, engineering, and design disciplines. Her lab collaborates on projects involving drone motion optimization, real-time respiration monitoring via video analysis, and enhancing remote collaboration through robotic systems.

Jingao Xuمشاهده پروفایل

پژوهشگر ارشد

• Event Cameras
• Drone Systems
• SLAM
• +۵ مورد دیگر

Jingao Xu is a Research Fellow in the Computer Science Department at Carnegie Mellon University's School of Computer Science, based in room 9120 of the Gates and Hillman Centers. His research bridges computer vision, robotics, and edge computing with a focus on real-world applications in drone systems and mobile sensing. His work addresses critical challenges in resource-constrained environments through innovative sensor fusion techniques. Xu's primary research centers on event camera technology , where he pioneers applications in drone navigation, SLAM, and environmental monitoring. His contributions include deraining algorithms using state space models (PRE-Mamba), mmWave radar-event camera fusion for drone landing, and multi-robot gas source localization (SniffySquad). He specializes in extracting value from high-frequency event streams under challenging conditions like rain, low light, and high-speed motion, with significant work in fall detection systems and urban air quality monitoring through mobile crowd-sensing (CatUA). Analysis of his 15 most recent publications (2024-2025) reveals three dominant trends: (1) Adoption of state space models (particularly Mamba variants) for efficient event stream processing, (2) Integration of event cameras with complementary sensors (mmWave radar, depth, IMU) for robust perception, and (3) Development of edge-assisted frameworks for real-time drone operations in wildfire suppression and autonomous navigation. His work consistently targets practical deployment on mobile platforms with severe computational constraints. No scientific awards or honors were mentioned in the available information. Details regarding student advising, research grants, laboratory affiliations, or team structures were not provided in the source material.

• Multi-Robot Systems
• Robotic Swarms
• Autonomous Technologies
• +۵ مورد دیگر

Spring Berman is an Associate Professor of Aerospace and Mechanical Engineering at Arizona State University (ASU), with affiliations in the School for Engineering of Matter, Transport and Energy, the Global Security Initiative, and the Center for Human, Artificial Intelligence, and Robot Teaming. She also holds an adjunct professorship in the Sandra Day O’Connor College of Law. Berman’s research focuses on multi-robot systems, swarm robotics, and biologically-inspired control strategies. She earned her Ph.D. (2010) and M.S. (2008) in Mechanical Engineering from the University of Pennsylvania and a B.S.E. (2005) in Mechanical and Aerospace Engineering from Princeton University. Her work includes grants from DARPA, NSF, and industry partnerships. She has led projects on swarm robotic control frameworks, boundary coverage, and cooperative manipulation. Berman teaches advanced engineering courses on system dynamics, control theory, and research methodologies. Her recent publications emphasize decentralized control strategies, swarm intelligence, and ethical considerations in autonomous systems. Her research activities span robotic swarm dynamics, autonomous vehicle testbeds, and human-swarm interaction. Key collaborations include projects on stochastic coverage strategies and multi-agent systems. Berman’s contributions bridge robotics, control theory, and societal applications through interdisciplinary initiatives.

Juan Sandinoمشاهده پروفایل

پژوهشگر ارشد

• Autonomous Systems
• Reinforcement Learning
• Remote Sensing
• +۶ مورد دیگر

Dr. Juan Sandino is a Research Fellow at the QUT Centre for Robotics, affiliated with the School of Electrical Engineering and Robotics at Queensland University of Technology (QUT). He holds a BEng (Mechatronics) from Nueva Granada Military University and a PhD in Robotics and Autonomous Systems from QUT (2022). His research focuses on autonomous UAV decision-making, machine learning, and remote sensing for environmental monitoring, biosecurity, and search and rescue operations. Education : PhD in Robotics and Autonomous Systems (2018–2022), QUT Bachelor of Engineering (Mechatronics, 2010–2015), Nueva Granada Military University Diploma in Project Management (2017–2018), Australian Pacific College Research Interests : Dr. Sandino specializes in developing drone-based solutions for environmental challenges. His work integrates autonomous systems, reinforcement learning, and hyperspectral imaging to address issues such as biosecurity threats, Antarctica's fragile ecosystems, and search and rescue missions in GPS-denied environments. His projects include UAV frameworks for planetary exploration (UAV4PE), detection of invasive species like Bitou Bush and Parthenium Weed, and real-time vegetation monitoring in polar regions. Awards & Recognition : CSIRO Data61 PhD and Top-Up Scholarships (2018–2021) Best Team Award, QUT Centre for Robotics (2021) Phase 1 Finalist, OpenCV AI Competition (2021) Projects & Grants : He leads projects funded by the Australian Research Council (SAEF initiative) and industry partners, including aerial mapping of forests affected by pathogens, UAV-based monitoring in Antarctica, and pest risk modeling for Buffel Grass. His work emphasizes collaboration with organizations like CSIRO Data61 and Charles Sturt University. Labs & Teams : Dr. Sandino contributes to the Securing Antarctica’s Environmental Future (SAEF) initiative and collaborates with interdisciplinary teams at QUT’s Centre for Robotics. His research integrates robotics software (ROS, PX4), sensor instrumentation, and AI for real-world applications.

Branko Risticمشاهده پروفایل

پژوهشگر ارشد

• Information Sciences
• Information Fusion
• Statistical Signal Processing
• +۷ مورد دیگر

Dr. Branko Ristic is a Principal Research Fellow at the School of Engineering, RMIT University. His research focuses on information fusion, statistical signal processing, target tracking, and robotics, with applications in defense and security. He leads projects on autonomous systems, sensor networks, and uncertainty modeling. Ristic advises on topics like decentralized multi-platform search, machine learning for tracking, and possibility theory-based methods. His work appears in top journals like IEEE Transactions and Entropy. He offers short courses in target tracking and sensor fusion. Research Interests: Information fusion, statistical estimation, Monte Carlo methods, and field robotics. His recent work emphasizes autonomous search algorithms and threat assessment systems, leveraging possibilistic frameworks and Bayesian networks. Articles span radar technology, IoT localization, and multi-agent systems. Supervision Projects: Includes decentralized search strategies, real-data maritime tracking, and threat valuation networks. Affiliations: RMIT University, School of Engineering (City Campus).

• Robotic Systems
• Unmanned Aerial Vehicles
• Path Planning
• +۲ مورد دیگر

Dr. Matheus Santos is a researcher at the Centre for Robotics and Intelligent Systems within the School of Engineering at the University of Limerick. His work focuses on developing cooperative robotic systems for inspection and monitoring applications. His research interests include path planning algorithms for unmanned systems, multi-robot cooperation (UAV/USV), 3D reconstruction for infrastructure assessment, visual inspection technologies, and fault-tolerant control systems for inaccessible environments. Recent projects involve developing modular UAV systems for wildlife monitoring, cooperative robotic teams for bridge inspection using LiDAR, and fault-tolerant control systems for offshore wind turbine inspection. Dr. Santos' work emphasizes practical applications in environmental monitoring and infrastructure maintenance.

Scott Koziolمشاهده پروفایل

دانشیار

• Robotics
• Neuromorphic Engineering
• Embedded Systems
• +۹ مورد دیگر

Dr. Scott Koziol is an Associate Professor and Associate Chair in the Department of Electrical & Computer Engineering at Baylor University, College of Engineering. He is actively leading research and teaching in robotics, embedded systems, and neuromorphic engineering. PhD in Robotics, Georgia Institute of Technology (2013) MS in Mechanical Engineering, Georgia Institute of Technology (2011) MS in Electrical Engineering, Iowa State University (2000) BS in Electrical Engineering, Cedarville University (1998) His research focuses on robotics, neuromorphic engineering, embedded systems, and analog/digital signal processing . He develops bio-inspired algorithms for autonomous navigation and implements them using reconfigurable analog VLSI and Field Programmable Analog Arrays (FPAA). His work integrates machine learning with stochastic computing and explores event-based vision, quantum random number generation, and assistive technologies such as The Reminding Walker device. His recent publications span topics including autonomous path planning, millimeter-wave radar for biomechanics, stochastic neural networks, and quantum workforce development. These works appear in journals like IEEE Access , Entropy , and Quantum Science and Technology , reflecting a multidisciplinary approach that bridges robotics, computing, and biomedical applications. Best Live Demo Award, ISCAS 2010 Outstanding Poster Presentation Award, URSA Scholars Week 2016 Dr. Koziol advises numerous graduate and undergraduate students, including thesis authors in robotics and neuromorphic computing. His research is supported by sponsors such as DARPA, ONR, DOE, and Baylor’s internal programs. He leads the Neuromorphic & Robotic Systems Lab located at the Baylor Research and Innovation Collaborative (BRIC), where his team conducts cutting-edge work in hardware-based neural computation and autonomous systems.

• Robotics
• Control Systems
• Nonholonomic Systems
• +۲ مورد دیگر

Adam Ratajczak is a Researcher at the Department of Control Systems and Mechatronics, Faculty of Information and Communication Technology, Wrocław University of Science and Technology. His work focuses on robotics, control systems, and nonholonomic motion planning. Research Interests: Nonholonomic robotic systems Jacobian motion planning algorithms Kinematic calibration Space manipulator dynamics Fuzzy logic control systems Selected Publications Trends: His research spans 2013-2025, with emphasis on nonholonomic robotics, trajectory optimization, and calibration techniques. Keywords include Robotics, Control Theory, and Algorithm Design. Subfields cover Nonholonomic Constraints, Jacobian Methods, and Space Docking. Labs & Teams: Affiliated with Wrocław University of Science and Technology's robotics research groups.

Eduardo Feo Flushingمشاهده پروفایل

استاد آموزشی

• Robotics
• Multi-Agent Systems
• Machine Learning
• +۴ مورد دیگر

Dr. Eduardo Feo Flushing is an Assistant Teaching Professor in the Software and Societal Systems Department at Carnegie Mellon University's School of Computer Science , based in Pittsburgh, PA. His role involves academic instruction and research at the intersection of software engineering, societal computing, and intelligent systems. Research Focus: His work spans robotics, distributed AI, and networked systems, with applications in critical domains. Primary research themes include: Multi-robot coordination for spatially distributed tasks Machine learning in healthcare diagnostics and renewable energy Wireless network optimization for mobile systems Human-robot collaboration under uncertainty Publication Trends: Recent articles (2021-2025) demonstrate a strong emphasis on applied machine learning (LLMs for medical ECG, deep learning for solar panel inspection) and advanced robotics (indoor mapping, task allocation in communication-constrained environments). Earlier work (2016-2020) focused on foundational aspects of multi-robot coordination, optimization, and wireless network resilience.

Tay Fei Siangمشاهده پروفایل

مدرس ارشد

• Intelligent Control System
• Dynamic Fuzzy Modelling of Complex System
• Smart Farming
• +۲ مورد دیگر

Dr. Tay Fei Siang serves as Senior Lecturer and Head of the Department of Robotics and Mechatronics Engineering at Swinburne University of Technology Sarawak Campus within the Faculty of Engineering, Computing and Science. Joining in 2013 as Associate Lecturer, he earned promotion to Senior Lecturer in 2021 while demonstrating leadership in both academic administration and research innovation. His academic credentials include: BEng (Hons) in Electrical and Computer Systems Engineering from Monash University, Australia (2008) PhD in Engineering from Swinburne University of Technology, Australia (2013) focusing on 'Sliding mode learning control for complex systems with dynamic fuzzy models' Dr. Tay's research bridges theoretical control engineering with practical applications across three interconnected domains: intelligent control systems for complex machinery, smart farming technologies addressing agricultural challenges, and wireless communications solutions for rural infrastructure. His work consistently targets Sarawak-specific problems, such as developing cost-effective internet deployment models for remote communities and creating sensor-based systems for precision agriculture. This applied approach transforms theoretical concepts into tangible community benefits while advancing engineering knowledge. Analysis of his 15 most recent publications reveals a strategic evolution from pure control theory (2014-2017) toward interdisciplinary applications (2018-2022), with 70% focusing on smart farming and rural telecommunications. His collaborative approach is evident in co-authorship patterns spanning agricultural science, healthcare technology, and civil engineering domains. Key recognitions include: Swinburne Vice-Chancellor Award 2019 (Community Engagement – Team) Innovation and Technology Expo 2019 dual awards (Gold/Silver) IEM-UTM InvecMax Competition 2021 First Runner Up (as Main Advisor) Innovate Malaysia Sarawak Edition 2022 First Prize in Electronic and IoT Track Dr. Tay actively mentors postgraduate researchers while managing externally funded projects including the Sarawak Digital Economy Research Grant 2019 ('Feasibility study on rural digital infrastructure') and SRDC 2020 grant ('Treated local marine sand in construction'). His supervision style emphasizes real-world problem solving, with students contributing to publications in IEEE transactions and international conferences. Current research directions focus on IoT-enabled agricultural systems and sustainable rural connectivity solutions. Though no dedicated lab name is specified, Dr. Tay leads research groups developing smart irrigation systems, vertical farming monitors, and light-based pest traps, frequently collaborating with Sarawak-based industry partners to ensure practical applicability of研究成果. His work exemplifies engineering solutions tailored to regional needs while maintaining academic rigor.

Stefan Wirtensohnمشاهده پروفایل

پژوهشگر

• Control Engineering
• Mechatronic Modeling
• Parameter Identification
• +۴ مورد دیگر

Stefan Wirtensohn is a Researcher at the Institute of System Dynamics, Konstanz University of Applied Sciences, where he has served as a research associate since 2012. His work bridges theoretical control engineering with practical marine robotics applications, focusing on autonomous surface vehicle development and advanced control systems. His academic credentials include: Bachelor of Engineering in Mechanical Engineering, HTWG Konstanz (2010) Master of Engineering in Mechatronics, HTWG Konstanz (2012) Wirtensohn's research centers on Control Engineering, Mechatronic Modeling, and Nonlinear Control systems for marine environments. He specializes in parameter identification, motion estimation, and trajectory optimization for autonomous vessels, with significant contributions to docking control, wave filtering, and extended object tracking. His methodology integrates unscented Kalman filters, model predictive control, and sensor fusion techniques to address real-world navigation challenges. Analysis of his 15 most recent publications (2013-2022) reveals consistent focus on marine robotics control systems. Key trends include the application of random matrices for lidar-based target tracking, model predictive path integral control for vessel stabilization, and advanced disturbance estimation techniques. His work demonstrates strong emphasis on experimental validation using autonomous surface vehicles across diverse maritime scenarios. He actively contributes to teaching through Control Engineering 1 exercises and laboratory supervision, emphasizing hands-on implementation of control algorithms. Current projects under his involvement include: Integrated autonomous measuring system for maritime surveying tasks Automated parking systems for truck trailers Collision prevention procedures for inland waterway vessels Wirtensohn operates within the Institute of System Dynamics research team specializing in signal processing, control engineering, and robotics, maintaining close collaboration with Johannes Reuter and other institute members on marine automation challenges.