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James A. Sethian is a Professor in the Department of Mathematics at the University of California, Berkeley , with additional affiliation at Lawrence Berkeley National Laboratory . His work focuses on developing and applying Level Set Methods and Fast Marching Methods to track evolving interfaces across diverse scientific domains. Education: Ph.D. in Applied Mathematics , University of California, Berkeley (1982) B.A. in Mathematics, Princeton University (1976) Research spans Applied Mathematics , Computational Physics , and Numerical Analysis , with applications in Semiconductor Manufacturing , Fluid Dynamics , Medical Imaging , Image Processing , Seismic Analysis , and Optimal Control . His publications demonstrate expertise in modeling interfaces that develop sharp corners, break apart, and merge, particularly through PDE-based numerical techniques. Key contributions include algorithms for noise removal , minimal surface computation , and multi-layer coating flows . As a mentor, he has advised numerous PhD students in computational methods and applied mathematics, including Robert I. Saye , Jon Arthur Wilkening , and David Layne Chopp . Projects under his leadership integrate ViscoElastic Flow , Tumor Modeling , and Robotics via curvature-driven evolution and interface tracking.

• Applied Mathematics
• Computational Physics
• Partial Differential Equations
• +6 more

Jim Torresen is a Professor at the Norwegian University of Science and Technology (NTNU), specializing in Computer Science, Artificial Intelligence, and Robotics. He earned his M.Sc. and Dr.ing. (Ph.D.) in computer architecture and design from NTNU in 1991 and 1996 respectively, followed by industry experience in hardware design before transitioning to academia in 1999. Research Interests: His work spans Machine Learning, Evolvable Hardware, and Ethical AI, with notable contributions to music technology, facial expression recognition, and healthcare monitoring systems. He actively explores interdisciplinary applications of AI in creative domains and clinical environments. Publications & Editorial Roles: Torresen has published extensively in journals like Frontiers in Artificial Intelligence and Genetic Programming and Evolvable Machines . He serves as a Topic Editor for Frontiers in Explainable AI and has editorial roles in robotics and biomedical AI domains.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +9 more

Aafke Fraaije is a postdoctoral researcher at the Section Ethics & Philosophy of Technology , Faculty of Technology, Policy and Management , Delft University of Technology. Her work bridges art, ethics, and technology through interdisciplinary approaches to citizen engagement and responsible innovation. Institution: Delft University of Technology School: Faculty of Technology, Policy and Management Department: Section Ethics & Philosophy of Technology Academic Rank: Research Fellow Research Interests : Ethics of human-nature-technology relationships Art-based methods for public engagement with technology Participatory futuring in smart city development Inclusive approaches to technology governance Communication frameworks in clinical and engineering contexts Critical analysis of responsible research and innovation (RRI) Recent Research Trends : Her publications focus on using artistic practices (dance, theatre) to explore ethical implications of smart city technologies, developing frameworks for responsible innovation, and analyzing communication dynamics in high-stakes environments like surgery and robotics. Key themes include citizen participation in technological development, interdisciplinary methodologies, and ethical accountability across sectors.

• Ethics of Technology
• Responsible Innovation
• Citizen Engagement
• +3 more

Dr. Leila Notash is a Professor in the Department of Mechanical and Materials Engineering at Queen's University, where she has been a faculty member since 1997. She is a Fellow of Engineers Canada (FEC) and a licensed Professional Engineer with Professional Engineers Ontario (PEO), with significant contributions to engineering education and professional service. Her educational background includes: Bachelor of Science in Mechanical Engineering, Middle East Technical University (Ankara, Turkey) - High Honor Student (2nd out of 166) Master of Applied Science in Mechanical Engineering, University of Toronto PhD in Mechanical Engineering, University of Victoria Dr. Notash's research centers on robotics and mechatronics, with specialized expertise in cable-driven parallel manipulators. Her work integrates kinematics, fault-tolerant design, and neural network applications to address challenges in robot calibration, workspace analysis, and motion control under real-world constraints like cable mass and elasticity. She investigates both theoretical frameworks and practical implementations for industrial and specialized robotic systems. Analysis of her recent publications (2020-2024) reveals a clear trajectory toward intelligent control systems, where machine learning techniques—particularly neural networks and reinforcement learning—are increasingly applied to solve complex problems in cable-driven robotics. This includes motion control optimization, path generation, and kineto-static analysis while accounting for physical limitations such as cable elasticity and mass effects, demonstrating a shift from traditional mechanical analysis to data-driven adaptive control methodologies. Her scientific recognition includes: Fellow of Engineers Canada (FEC) University of Toronto Open Fellowship University of Toronto International Differential Fee Waiver Charles S. Humphrey Graduate Student Award NSERC Doctoral Prize Nominee (1996) Dr. Notash has mentored 161 undergraduate students as Faculty Advisor for the Mechanical '06 cohort and pioneered international educational initiatives like the International Undergraduate Student Design project (IVDS), connecting Queen's University with Middle East Technical University and Union College. Her service extends to editorial leadership for Mechanism and Machine Theory and ASME journals, and governance roles including Faculty Senator at Queen's University (2009-2025) and PEO Council Councillor-at-Large (2019-2025). She has established collaborative research networks through initiatives like the Reading Week shop course 'Design Basics 1.0' and sustained leadership in the Canadian Committee for the Promotion of Mechanism and Machine Science (CCToMM) and the International Federation for the Promotion of Mechanism and Machine Science (IFToMM), where she chaired the Permanent Commission on Communications (2006-2011).

• Robotics
• Mechatronics
• Kinematics
• +3 more

Marilena Vendittelli is a Professor at Sapienza University of Rome, affiliated with the Robotics group. Her research spans control systems, biomedical robotics, motion planning, and autonomous systems. Research Areas: Control systems for robotics and nonholonomic systems Biomedical applications (hyperthermia therapy, needle insertion) UAV navigation and obstacle avoidance Haptics and human-robot interaction Adaptive estimation algorithms Recent Publications focus on adaptive control of bio-heat equations, safe UAV motion planning, soft robotics actuation, and haptic feedback in medical procedures.

• Robotics
• Control Systems
• Biomedical Engineering
• +7 more

Jeff Shamma is the Department Head and Professor of Industrial and Enterprise Systems Engineering (ISE) at the University of Illinois at Urbana-Champaign, holding the Jerry S. Dobrovolny Chair. He is also courtesy Professor in Aerospace Engineering and Mechanical Science and Engineering. Formerly, he held the Julian T. Hightower Chair at Georgia Institute of Technology and faculty positions at KAUST. Dr. Shamma earned his PhD in Systems Science and Engineering from MIT (1988) and a BS in Mechanical Engineering from Georgia Tech (1983). He is a Fellow of IEEE and IFAC, recipient of the IFAC High Impact Paper Award, AACC Donald P. Eckman Award, and NSF Young Investigator Award. His research spans Decision and Control , Game Theory , and Multi-Agent Systems , focusing on human-machine networks, distributed autonomy, and adaptive robotic systems. Recent work examines crowd dynamics, risk-sensitive control, and feedback linearization for constrained optimization. Jeff has served as Editor-in-Chief of IEEE Transactions on Control of Network Systems (2020–2024) and held editorial roles in journals like Annual Reviews in Control and IEEE Transactions on Robotics . His 15 most recent publications (2024–2025) analyze learning dynamics, multi-agent optimization, and UAV-crawler systems, reflecting trends in autonomous systems, game-theoretic modeling, and industrial inspection technologies. Scientific distinctions include: Fellow of IEEE and IFAC IFAC High Impact Paper Award (2020) AACC Donald P. Eckman Award (1996) NSF Young Investigator Award (1992) Mohammed Dahleh Distinguished Lecture Award (2013) Dr. Shamma advises current PhD students Hassan Abdelraouf, Aya Hamed, and Nawaf Otaibi, with former advisees including Sarah Toonsi (2025) and Fat-hy Rajab (2025). His lab integrates theoretical research with applied projects like FalconScan, a UAV-crawler system for industrial inspection, and develops magnetic legs for curved surface UAV landing.

• Decision and Control
• Game Theory
• Multi-Agent Systems
• +7 more

Luís Miguel Mendonça Rato is an Associate Professor at the Universidade de Évora and a Senior Researcher with a PhD at Centro ALGORITMI. He is affiliated with the CST R&D Group and VISTA Lab R&D Lab, focusing on interdisciplinary research at the intersection of Electrical Engineering, Computer Science, and Agricultural/Biomedical applications. Academic Degree: PhD Current Position: Associate Professor Labs: VISTA Lab Researcher IDs: ORCID 0000-0003-4492-7548, ResearcherID A-9152-2013, CiênciaID A914-6344-CD2D His research spans machine learning applications in Agricultural Engineering (Sentinel-2 satellite data for nutrient analysis), Biomedical Imaging (MRI-ADC texture analysis for tumor classification), and Control Systems (predictive control algorithms for water delivery canals and solar fields). With an h-index of 11 and 51 publications, his work emphasizes hybrid systems combining traditional engineering with computational innovation. Recent publications highlight trends in SLAM efficiency (2024), cloud service optimization (2022), and deep learning for medical imaging (2022-2023). He has contributed to Smart Cities initiatives through projects like M-Traffic (2006) and NanoSen-AQM (2020). As a senior researcher, he leads projects in the CST R&D Group and VISTA Lab , with notable work in the Universidade de Évora ecosystem.

• Machine Learning
• Electrical Engineering
• Computer Science
• +3 more

Taylor Ware is an Associate Professor in Biomedical Engineering and Materials Science & Engineering at Texas A&M University's College of Engineering, holding the Cain Faculty Fellowship. Her research focuses on designing structured biomaterials and medical devices using stimuli-responsive polymers for clinical applications. Education: Ph.D. in Materials Science and Engineering, The University of Texas at Dallas, 2013 Research Interests: Dr. Ware pioneers the development of liquid crystal elastomers as artificial muscles and implantable electronics substrates, engineered living materials for infection treatment, and directed self-assembly of hydrogels. Her lab specializes in polymer formulation, thermomechanical testing, and microfabrication. Key research thrusts include: Smart elastomers, hydrogels, and composites for dynamic medical devices Programming liquid crystalline polymers for shape-morphing applications Engineered living materials that respond to biomolecular cues in urinary tract environments Publication Trends: Recent work (2023-2025) demonstrates convergence of materials science, microbiology, and medical device engineering. Her group advances liquid crystal elastomers for soft robotics and implantable electronics, develops engineered living materials for UTI treatment using microbial competition, and creates novel hemostats and urethral support devices. Publications emphasize translational applications in urology, wound healing, and neural interfaces. Scientific Awards: Invited Participant, NAE Japan-USA Frontiers of Engineering Bilateral (2023) Senior Member, National Academy of Inventors (2022) NSF CAREER Award (2018) Air Force Young Investigator Award (2017) NSF Graduate Research Fellowship (2011) Fellow of AIMBE (American Institute for Medical and Biological Engineering) Advising and Grants: Dr. Ware leads the Ware Lab with significant funding including an NIH R01 grant (with UT Dallas and Case Western collaborators) and the NSF CAREER award. Her lab mentors postdoctoral fellows like Mustafa (winner of a prestigious postdoctoral fellowship) and graduate students. Current projects are supported by the NSF Engineering Research Center HAND, focusing on advanced materials for healthcare applications. Laboratory and Teams: The Ware Lab collaborates globally and is featured in Texas Monthly, Houston Chronicle, and National Geographic for breakthroughs in engineered living materials. As part of the NSF HAND ERC, the lab develops dynamic materials for stress urinary incontinence treatment and collaborates with medical institutions on UTI therapies using engineered E. coli strains.

• Biomaterials
• Micro/Nanotechnology
• Medical Devices
• +7 more

Lifeng Zhou is an Assistant Professor in the Department of Electrical and Computer Engineering at Drexel University, where he leads the Zhou Lab focused on advancing robustness and reliability in multi-robot systems through integration of foundation models. His research addresses real-world challenges in environmental monitoring, disaster response, and urban mobility. Education PhD, Electrical and Computer Engineering, Virginia Tech, 2020 MS, Control Science and Engineering, Shanghai Jiao Tong University, 2016 BS, Automation, Huazhong University of Science and Technology, 2013 Research Focus Dr. Zhou's work integrates robotics, algorithms, game theory and machine learning to develop secure and scalable autonomous systems. Primary research thrusts include: Resilient multi-robot coordination in adversarial environments Large language model integration for robotic decision-making Game-theoretic resource allocation strategies Risk-aware planning for autonomous vehicles Publication Trends Recent work (2024-2025) demonstrates strong focus on large language model applications in multi-robot systems, with 12/15 articles exploring LLM integration for flocking, scene segmentation, and decision-making. Additional emphasis includes adversarial robustness in target tracking (5 articles) and autonomous driving applications (4 articles). Awards and Recognition Best Paper Award, WACV 2025 LLVM-AD Workshop Professional Service Associate Editor, ICRA Conference Editorial Board Laboratory Focus The Zhou Lab develops foundational algorithms for secure and scalable multi-robot systems, with current projects spanning environmental monitoring drones, disaster response coordination, and autonomous vehicle perception systems.

• Robotics
• Algorithms
• Combinatorial Optimization
• +4 more

Dr. Meng Fang is a researcher specializing in Artificial Intelligence with a focus on Reinforcement Learning, Large Language Models, and their applications in medical QA, game theory, and causal inference. Their work combines technical innovation with practical problem-solving in safety-critical and domain-specific contexts. Key research areas: Social bias in AI, data augmentation, embodied agents, and model-based reinforcement learning Teaching: Coordinated module COMP532 - Machine Learning and BioInspired Optimisation (2024-25). Recent publications address challenges in offline RL robustness, vision-based safe reinforcement learning, and strategic game generalization.

• Artificial Intelligence
• Reinforcement Learning
• Large Language Models
• +3 more

Renate Sachse is a Researcher and Responsible Investigator at the Chair of Structural Analysis, Technical University of Munich (TUM), under Prof. Kai-Uwe Bletzinger. She holds a Dr.-Ing. from the University of Stuttgart and has held postdoctoral positions at Harvard University (Bertoldi Lab) and TU Munich's Institute for Computational Mechanics. Her research focuses on biomimetic adaptive structures, biomechanics, and smart materials. Education M.Sc. in Civil Engineering (University of Stuttgart, 2014) – Thesis: "Isogeometric Contact Analysis of Thin-Walled Structures" B.Sc. in Civil Engineering (University of Stuttgart, 2011) – Thesis: "Elementary School Pavilion Structural Analysis" Study Abroad: École Spéciale des Travaux Publics (ESTP, France, 2012) Research Interests Her work integrates principles from biology and mechanics to design adaptive structures, including motion design, soft robotics, and active metamaterials. Notable projects include studying snapping mechanisms in plants (e.g., Venus flytrap) and developing bio-inspired systems like Flectofold shading devices. She also explores isogeometric analysis and structural optimization for thin-walled and slender structures. Grants & Awards Bertha Benz Prize 2022 (Daimler and Benz Foundation) Klaus Tschira Boost Fund Fellowship (€80,000 interdisciplinary grant) 3rd Place AVK-Prize for Innovations (2017, Flectofold Shading System) GAMM Juniors Fellowship (2020–2022) Teaching & Grants She teaches advanced finite element methods and nonlinear mechanics at TUM and has supervised projects in computational mechanics. Her grants include CareerDesign@TUM funding and the Klaus Tschira Fellowship for high-risk, interdisciplinary research. Labs & Teams Associated with the Chair of Structural Analysis at TUM, collaborating on projects like livMatS (Living Materials Systems) and the Harvard SEAS Bertoldi Lab. Involved in software development (e.g., Carat++, Kiwi!3d) and third-party initiatives (CoDA, FlexWing).

• Motion Design
• Active and Adaptive Structures
• Biomechanics
• +6 more

David Wettergreen is a Research Professor at the Robotics Institute within Carnegie Mellon University's School of Computer Science , where he has been a faculty member since 2000. He directs the PhD Program in Robotics and holds a courtesy appointment in Mechanical Engineering. His research focuses on robotic exploration systems for extreme environments, spanning planetary surfaces, underwater caves, and terrestrial deserts. Key areas include autonomous navigation , science autonomy , multi-modal perception , and resource-cognizant planning . Field validation drives his work, with deployments in the Atacama Desert, Antarctic volcanoes, and lunar analog sites. Co-founder of Mesh Robotics LLC for off-road autonomy Former Research Fellow at Australian National University Former National Research Council Research Associate at NASA Ames Research Center His 15 most recent publications (2023-2025) demonstrate expertise in autonomous path planning , machine learning applications , terrain modeling , and science-driven exploration . Collaborations span planetary science, environmental monitoring, and space systems engineering. He has advised 17 PhD and 33 MS students , many of whom now work in space exploration or field robotics, and teaches courses in Robotics Systems Engineering . Current projects include the MoonRanger lunar micro-rover and technologies for autonomous resource mapping .

• Space Robotics
• Robotic Exploration
• Autonomous Navigation
• +7 more

Ming Lin is a Distinguished University Professor at the University of Maryland, College Park, holding joint appointments in Computer Science (Department of Computer Science), the Institute for Advanced Computer Studies (UMIACS), Electrical and Computer Engineering (ECE), and the Maryland Robotics Center. She holds the Dr. Barry Mersky and Capital One E-Nnovate Endowed Professorships. Her research focuses on physically-based modeling, virtual environments, haptics, robotics, and AI applications in healthcare and urban computing. Education: Ph.D., M.S., and B.S. in Electrical Engineering & Computer Sciences from UC Berkeley. She previously spent 20 years at UNC Chapel Hill before joining UMD in 2018. Research interests include collision detection algorithms (e.g., Lin-Canny algorithm), real-time physics simulation, virtual/augmented reality systems, and medical imaging applications. Her work has led to over 2 million downloads of her group's software tools and licenses with 60+ companies. Notable contributions include the Oculus Rift-related VR technologies and Amazon's virtual try-on system. Awards: IEEE Fellow (2012), ACM Fellow (2011), NAI Fellow (2022), and Washington Academy of Sciences Distinguished Career Award (2020). Active in professional service, she serves on the CRA Board and chairs the Committee on Widening Participation in Computing Research. Advising: Supervises 12+ PhD/Master's students. Her lab (GAMMA Group) focuses on AI-driven robotics, autonomous systems, and physically-based simulations. Key projects include traffic simulation frameworks, medical VR applications, and 3D garment modeling.

• AI and Robotics
• Computer Vision
• Computer Graphics
• +5 more

Professor Khac Duc Do is a faculty member at Curtin University, holding a position in the School of Civil and Mechanical Engineering within the Faculty of Science and Engineering. He serves in the Office of the Provost and is based at Curtin Perth campus. His research focuses on advanced control systems, nonlinear dynamics, and robotics applications in marine, aerospace, and mechanical systems. He earned a PhD with distinction in 2003 and has held prestigious fellowships including ARC Postdoctoral Fellow (2004) and ARC Australian Research Fellow (2009). His teaching includes courses like Advanced Control and Mechatronics, Navigation and Marine Control Systems, and Advanced Control Engineering. Key research interests encompass control of nonlinear systems, stochastic systems, formation control of mobile agents, fluid-structure interaction, and boundary control of PDE-governed systems. His funded projects include wave-energy converter development (2023-2026), inerter-based damper research (2019-2021), and ocean vehicle control systems. Scientific awards include ARC grants totaling over AUD 2 million. Current opportunities include scholarships in control systems/fluid-structure interaction and a postdoc position in wave-energy conversion.

• Control of Nonlinear Systems
• Autonomous Marine Vehicles
• Partial Differential Equation Systems
• +3 more

Nazanin Tajik is an Assistant Professor in the Department of Industrial and Systems Engineering at Mississippi State University (MSU). She holds a Ph.D. from the University of Oklahoma, an M.S. from the University of Tehran, and a B.S. from Sharif University of Technology. Her research focuses on integrating artificial intelligence, machine learning, and social science concepts to develop cross-disciplinary frameworks for infrastructure resilience, smart transportation systems, and disaster management. Her academic journey includes a Ph.D. at the University of Oklahoma where she contributed to the Risk-Based Systems Analytics Laboratory. At MSU, she established a research center bridging AI/ML tools with socio-technical systems. Key research domains include cyber-physical-social infrastructure resilience, search-and-rescue planning, and game-theoretic robotic designs. Tajik's work emphasizes optimization algorithms for network vulnerability assessment, resource allocation in disaster scenarios, and adaptive recovery strategies. She is actively involved with professional organizations such as INFORMS, ISE, and POMS, reflecting her commitment to advancing operations research and systems engineering methodologies.

• Artificial Intelligence
• Machine Learning
• Infrastructure Resilience
• +4 more