Chris Atkeson is a Professor at the Robotics Institute of Carnegie Mellon University. His research focuses on achieving human-level competence in machines through humanoid robotics and human-aware environments. He explores machine learning techniques such as reinforcement learning, nonparametric methods, and memory-based learning to develop robots capable of complex tasks like manipulation, locomotion, and perception. His work emphasizes bridging the gap between simulation and real-world applications (sim2real transfer), with contributions to tactile sensing (e.g., FingerVision), dynamic walking control, and human-robot collaboration. Notable projects include participation in the DARPA Robotics Challenge with Team WPI-CMU, where his team developed reliable humanoid behavior for disaster response scenarios. Atkeson’s research spans robotics, computer vision, and control systems, with a focus on enabling robots to perceive, learn, and act in unstructured environments. His recent work includes advancements in 3D scene capture, soft robotics, and energy-based planning for compositional tasks.
Joydeep Biswas is an Associate Professor in the Computer Science Department at the University of Texas at Austin, where he serves as the Director of the Autonomous Mobile Robotics Laboratory (AMRL). He is also affiliated with Texas Robotics, the UT Machine Learning Laboratory, and UT Good Systems. Previously, he was an Assistant Professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst. Dr. Biswas earned his PhD in Robotics from Carnegie Mellon University in 2014 and his B.Tech in Engineering Physics from the Indian Institute of Technology Bombay in 2008. His educational background has provided him with a strong foundation in both theoretical and applied aspects of robotics and artificial intelligence. Dr. Biswas's research focuses on enabling long-term autonomy for mobile robots operating in human environments. His work spans robot perception, motion planning, control systems, and AI, with the ultimate goal of creating self-sufficient autonomous mobile robots that can perform tasks accurately and robustly in real-world settings. He is particularly interested in perception, planning, and failure recovery for autonomous mobile robots, which supports his vision of having autonomous service mobile robots deployed at campus-to-city scale, both indoors and outdoors, performing assistive tasks over deployments spanning years. His IJCAI 2019 Early Career Spotlight talk summarizes much of his research to date and ongoing interests. His recent research has shown a strong trend toward social navigation, human-robot interaction, and the application of machine learning techniques to robotics problems. There's a clear progression from fundamental robotics research toward more complex, real-world applications that require robots to understand and navigate human social spaces effectively. His work increasingly integrates large language models and other advanced AI techniques with traditional robotics approaches, as evidenced by his recent publications on topics like preference-conditioned navigation, social navigation benchmarks, and instruction-following navigation systems. Dr. Biswas has received numerous prestigious awards including the NSF CAREER Award (2021), J.P. Morgan Faculty Research Award (2019), Amazon Research Award (2019), and a grant from Northrop Grumman Mission Systems (2018). These awards recognize his innovative contributions to the field of robotics and autonomous systems. As a dedicated educator and mentor, Dr. Biswas actively supervises PhD and master's students, with his PhD student Sadegh Rabiee winning the student poster award at the Northrop Grumman University Symposium 2019. He has secured significant grant funding from the National Science Foundation for projects including 'Introspective Perception and Planning for Long-Term Autonomy' and 'Interactive Synthesis and Repair For Robot Programs,' demonstrating his ability to secure competitive research funding and his commitment to advancing the field. Dr. Biswas leads the Autonomous Mobile Robotics Laboratory (AMRL), which serves as a hub for interdisciplinary research in mobile robotics. The lab has developed notable resources such as the UT Campus Object Dataset (CODA) for 3D perception research and SOCIALGYM, a framework for benchmarking social robot navigation. His team regularly deploys robots on the UT Austin campus and in urban environments to test and refine their approaches in realistic settings, bridging the gap between simulation and real-world application.
Professor Peter F. Driessen is a faculty member in the Department of Electrical and Computer Engineering at the University of Victoria, with a cross-appointment in the School of Music. He holds a BSc and PhD from the University of Victoria and is a Professional Engineer (PEng). His research focuses on communication systems, signal processing, control, and interdisciplinary projects in computer music and wireless technologies. Key areas include audio/video signal processing, radio propagation, sound recording, and multimedia systems. He leads the University of Victoria Propagation Laboratory, which explores radio wave propagation and Amateur radio integration with engineering education. His work spans theoretical research and applied projects like ECOSat satellite systems, software-defined radio (SDR), and innovative musical instruments such as the Radio Drum. He supervises undergraduate and graduate projects in these domains through ELEC 499 courses. Notable contributions include the APEGBC Editorial Board Award for Best Paper (2002) and patents in wireless networking and signal processing. His teaching includes courses in signal analysis and electromagnetics, and he collaborates on interdisciplinary programs like the Music/Computer Science degree. Education: BSc in Electrical Engineering, University of Victoria PhD in Electrical Engineering, University of Victoria Research Interests: Audio and video signal processing for music and media Software-defined radio and Amateur radio technologies Satellite communication and ground station development Gesture-based interfaces and musical instrument design Error mitigation in streaming audio/video Optical and microwave-photonic systems Labs & Collaborations: Propagation Laboratory (radio wave research) UVic Experimental Radio Group (Amateur radio club) UVic Satellite Design Team (ECOSat projects) UVic Centre for Aerospace Research Grants & Awards: APEGBC Editorial Board Award (2002) Multiple US patents in wireless systems and signal processing
Freek Persyn is a Full Professor of Architecture and Urban Transformation at ETH Zurich, where he has held the NEWROPE Professorship since 2019. He leads the Design in Dialogue Lab within the Department of Architecture, focusing on spatial design and social innovation. Persyn co-founded the spatial planning firm 51N4E in 1998, which specializes in urban and social transformation across Europe. Persyn's research centers on the concept of 'Design in Dialogue,' which emphasizes transdisciplinary collaboration to address the complexity of contemporary urban challenges. His work explores innovative solutions for European urban spaces, aiming to rediscover Europe as a habitable terrain and shared living space. Key research areas include urban design, spatial planning, social transformation, and the intersection of architecture with social innovation. The NEWROPE initiative seeks to examine diverse urban practices that shape Europe, fostering radical openness and learning from various urban practitioners through transdisciplinary projects. His scholarly output demonstrates a strong focus on reimagining urban spaces through dialogue-based approaches. Persyn's work examines European urban transformation, rural-urban connections, industrial heritage sites, and innovative design methodologies. Key themes across his publications include sustainable approaches to building, the social dimensions of space, and transformative design processes that challenge conventional architectural practices. His research often bridges theoretical frameworks with practical design applications, emphasizing participatory methods and material investigations. Persyn delivered his inaugural lecture at ETH Zurich on October 20, 2021, titled 'Wouldn't it be nice if architects started dreaming about building less?' The lecture explored his professional background, inspiration, and future plans for the NEWROPE Chair. The event featured collective sensing exercises developed by students of Studio Seebach with theater and dance maker Manuela Runge, highlighting his commitment to experiential and collaborative approaches to architectural education and practice. The Design in Dialogue Lab serves as a hub for exploring innovative approaches to urban transformation through projects across European cities including Brussels, Piraeus, Basel, and Plovdiv. Current initiatives examine topics such as urban spaces for more than human communities, collaborative processes, design approaches, and hybrid applications for European urban environments. Persyn's work consistently emphasizes transdisciplinary collaboration, bringing together spatial and strategic knowledge with other disciplines and urban practitioners to address complex contemporary challenges.
Bruño Fraga is an Assistant Professor in the Department of Civil Engineering at the University of Birmingham, part of the School of Engineering. He specializes in Computational Fluid Dynamics (CFD) with a focus on turbulent and multiphase flows, particularly in applications like indoor air quality, water treatment, and airborne pathogen transport. His research group develops models such as Multiflow3D, addressing challenges in multiphase flow dynamics and environmental engineering. Education: MEng in Environmental Engineering (University of Santiago de Compostela, 1st class honors), MSc in Applied Math and Numerical Simulation (University of A Coruña), PhD in Civil Engineering (Universities of A Coruña and Chalmers). Research Interests: CFD modeling, bubble-induced turbulence, indoor air quality, water treatment technologies, and multiphase flow dynamics. Dr. Fraga leads major projects such as Fusion Forest (£1m, UKRI) and the IAQ-EMS initiative (£1m, Met Office), focusing on indoor air quality and pathogen transmission modeling. His work includes collaborations with organizations like Deltares Institute and Severn Trent, addressing wastewater treatment and environmental challenges. He is co-leader of the Fluids Research Group and the Water Technology stream at the University of Birmingham’s Water Centre. Scientific Awards: National Outstanding Graduate Prize (2011). Advising & Grants: Supervises graduate students in CFD and multiphase flow research. Oversees grants totaling over £2.1M, including fusion forest and buildair projects. Focuses on translating CFD expertise into real-world solutions for public health and environmental sustainability. Labs & Teams: Leads the Multiflow3D development team and collaborates with the Fluids Research Group and Water Technology stream.
Justin Yim is an Assistant Professor at the Department of Mechanical Science and Engineering at the University of Illinois Urbana-Champaign (UIUC), where he runs the Novel Mobile Robots Lab (NMbL). His research focuses on enabling high-performance locomotion in robots through concurrent design of mechanisms and controllers, inspired by biological systems. He previously earned his PhD in Electrical Engineering from UC Berkeley (2020) and dual BS degrees in Mechanical Engineering and Applied Mechanics/Electrical Engineering from the University of Pennsylvania (2015), followed by a postdoctoral researcher role at Carnegie Mellon University (2020-2022). PhD, Electrical Engineering, University of California, Berkeley (2020) MSE, Robotics, University of Pennsylvania (2015) BSE, Mechanical Engineering and Applied Mechanics/Electrical Engineering, University of Pennsylvania (2015) His research explores legged robot design, bioinspired robotics, and locomotion dynamics, with a focus on overcoming terrain challenges through minimalist mechanical systems and control strategies. Recent work emphasizes squirrel-inspired jumping and landing mechanics, programmable substrates for locomotion studies, and energy-efficient robot mobility. Selected article trends highlight innovations in monopedal hopping with series-elastic actuators, bioinspired balance control, underactuated bipedal walkers, and cooperative cable-driven modular robots. His work bridges theoretical insights with practical applications in extreme-terrain mobility. NSF CAREER Award (2025): 'Extreme Robot Walking: Speed, Agility, and Efficiency via Reduced Degrees of Freedom' NASA Innovative Advanced Concepts Fellow (2025) Justin Yim actively mentors graduate students and leads research projects in the NMbL lab, which develops robots capable of walking, hopping, and rolling in complex environments. Recent lab achievements include a Best Demo award at the 2nd Unconventional Robots Workshop (2025) and awards for outstanding locomotion papers. He teaches courses such as ME 370 Mechanical Design I and SE 422 (ME 446, ECE 489) Robot Dynamics and Control.
Zeynep Temel is an Assistant Professor at Carnegie Mellon University's College of Engineering, jointly appointed in the Biomedical Engineering and Robotics Institute. She leads the Zoom Lab, focusing on bio-inspired compliant mechanisms for robotic systems. Current research emphasizes adaptable robots for complex environments through mechanical intelligence and embedded control . Key application areas include surgical robotics , search-and-rescue , and micromanipulation . Her work spans bio-inspired design, compliant robotics, and human-centered applications. Recent publications highlight advancements in: Swarm robotics for collaborative exploration Soft actuators using bioplastics and gelatin Dexterous manipulation via delta robot frameworks The Zoom Lab trains students in robotic fabrication and biological modeling, with members transitioning to roles in academia and industry.
Justin K S Yim is an Assistant Professor in the Department of Mechanical Science and Engineering at the University of Illinois Urbana-Champaign with a secondary appointment at the Coordinated Science Lab. His research focuses on bioinspired robotics, particularly legged locomotion systems and dynamic balance control mechanisms derived from animal behavior. Education: Ph.D. in Electrical Engineering (awarded May 15, 2020) Dr. Yim's work centers on translating biological principles—especially squirrel locomotion—into robotic systems capable of complex maneuvers like branch-to-branch leaping and stable landings. His research integrates hardware design, control theory, and biomechanical analysis to address challenges in robot-environment interaction on non-rigid surfaces and complex terrains, with applications in search-and-rescue and construction robotics. Recent publications (2024-2025) reveal a cohesive research trajectory exploring monopedal jumping dynamics, squirrel-inspired balance control, and cooperative cable-driven manipulation. Key themes include state-space stability analysis, nonprehensile foot torque utilization, and programmable surface interactions, demonstrating interdisciplinary convergence of robotics, biomechanics, and materials science. Dr. Yim maintains active affiliation with the Coordinated Science Lab, a premier UIUC research hub fostering innovation in robotics, control systems, and autonomous technologies through cross-departmental collaboration.
Byron Boots is the Amazon Professor of Machine Learning in the Paul G. Allen School of Computer Science and Engineering at the University of Washington, where he directs the UW Robot Learning Laboratory. He also serves as a Principal Research Scientist in the Seattle Robotics Lab at NVIDIA Research and co-chairs the IEEE Robotics and Automation Society Technical Committee on Robot Learning. Dr. Boots received his Ph.D. from the Machine Learning Department in the School of Computer Science at Carnegie Mellon University, where he was a member of the Sense, Learn, Act (SELECT) Lab co-directed by Carlos Guestrin and his advisor Geoff Gordon. Prior to joining the University of Washington faculty, he was an Assistant Professor in the School of Interactive Computing within the College of Computing at Georgia Tech, and before that, he completed a post-doc in the Robotics and State Estimation Lab directed by Dieter Fox at the University of Washington. Professor Boots' research focuses on the intersection of machine learning, artificial intelligence, and robotics, with particular emphasis on developing theory and systems that tightly integrate perception, learning, and control. His work spans computer vision, state estimation, localization and mapping, high-speed navigation, motion planning, and robotic manipulation. His group develops algorithms drawing from deep learning and neural networks, nonparametric statistics, graphical models, nonconvex optimization, quantum physics, online learning, reinforcement learning, and optimal control. The research demonstrates a strong theoretical foundation while maintaining practical relevance to real-world robotic systems. His recent publications reveal a clear trend toward integrating advanced machine learning techniques with robotics, particularly in model predictive control, motion planning, and learning-based approaches to robot control. His work shows increasing focus on developing theoretically grounded methods that can handle the complex, nonlinear dynamics of real-world robotic systems while maintaining computational efficiency. The publications span top venues including ICRA, CoRL, IROS, and NeurIPS, demonstrating broad impact across multiple subfields of robotics and AI. Finalist for Best Systems Paper at Conference on Robot Learning (CoRL-2021) Multiple papers selected for oral presentations at top robotics conferences Work recognized for theoretical contributions and practical applications in robot learning As director of the UW Robot Learning Laboratory, Boots leads a vibrant research group focused on fundamental and applied research in robot learning. The lab maintains strong collaborations with NVIDIA Research and has produced numerous high-impact publications that bridge theory and practice. Professor Boots teaches courses in autonomous robotics, machine learning, and reinforcement learning, contributing to both undergraduate and graduate education at the University of Washington.
Alex John London is the K&L Gates Professor of Ethics and Computational Technologies at Carnegie Mellon University, where he also serves as co-lead of the K&L Gates Initiative in Ethics and Computational Technologies, Director of the Center for Ethics and Policy, and Chief Ethicist at the Block Center for Technology and Society. His work spans multiple institutions, including affiliations with the Center for Bioethics and Health Law at the University of Pittsburgh. Dr. London earned his Ph.D. in Philosophy from the University of Virginia, followed by a post-doctoral fellowship at the University of Minnesota's Center for Bioethics. He joined Carnegie Mellon University in 2000 and has established himself as a leading scholar in ethics at the intersection of technology, medicine, and policy. His academic journey includes being a Visiting Scholar at Harvard University's Program in Ethics and Health. Professor London's research spans ethical and policy issues surrounding novel technologies in medicine, biotechnology and artificial intelligence, methodological issues in theoretical and practical ethics, and cross-national issues of justice and fairness. His work in AI ethics critically examines structural obstacles to safe and effective technologies, challenges conventional notions of algorithmic bias, and questions requirements for explainability in medical contexts. His foundational work on clinical equipoise and the 'integrative approach' to risk assessment has shaped research ethics guidelines globally. He has made significant contributions to international research ethics, particularly regarding justice, responsiveness to host community health needs, and post-trial access. Professor London's scholarly output demonstrates a trajectory toward addressing the ethical challenges of emerging technologies, with increasing focus on justice-led approaches to AI innovation, accountability frameworks, and the sociotechnical dimensions of healthcare AI systems. His work increasingly addresses how AI can be designed to respect human dignity while navigating complex ethical terrain in healthcare settings. New Directions Fellowship from the Andrew W. Mellon Foundation (2005, 2010) Hastings Center Fellow (2011) Elliott Dunlap Smith Award for Distinguished Teaching (2016) Distinguished Service Award from the American Society of Bioethics and Humanities (2017) As an educator, Professor London teaches courses on ethical theory, bioethics, ethics and AI, and research ethics. His influential textbook 'Ethical Issues in Modern Medicine' (8th edition) is one of the most widely used resources in medical ethics education. His book 'For the Common Good: Philosophical Foundations of Research Ethics' (2022) provides a comprehensive framework for understanding research ethics as serving the common good. Professor London has advised numerous students and mentored early-career researchers in bioethics and technology ethics. His policy work extends to multiple national and international organizations including the World Health Organization Expert Group on Ethics and Governance of AI, the National Academy of Medicine Action Collaborative, and the U.S. National Science Advisory Board for Biosecurity. Professor London leads several significant research initiatives, including serving as co-leader of the ethics core for the NSF AI Institute for Collaborative Assistance and Responsive Interaction for Networked Groups (AI-CARING). His Center for Ethics and Policy at CMU serves as a hub for interdisciplinary research addressing pressing ethical challenges in technology and healthcare. He is actively involved in shaping policy through his membership on the steering committee of the AAAI/ACM Conference on Artificial Intelligence, Ethics and Society (AIES) and his co-chair role in the U.S. National Academies planning committee on computational modeling of biological agents.
Alireza Ramezani is an Associate Professor of Electrical and Computer Engineering at Northeastern University, leading the SiliconSynapse Lab. He focuses on bio-inspired robotics, nonlinear systems, and robot locomotion, with a particular emphasis on morphological design and control inspired by biological systems. His work integrates control theory and experimental robotics to develop robots capable of navigating confined spaces, such as caves and ducts, using mechanisms derived from bat movements. Education : PhD, Mechanical Engineering, University of Michigan (2014) MS, Mechanical Engineering, ETH Zurich (2010) BSc, Mechanical Engineering, Iran University of Science and Technology (2007) Research Interests : Design of robots with non-traditional morphologies Nonlinear feedback control systems Legged and fluidic-based locomotion Bio-inspired robotics and biology-driven engineering Awards : 2024 ASME Rising Star Award 2024 NSF CAREER Award 2022 NASA Game Changing Program Award Science Magazine Top 5% Research Output (2020) Advising & Labs : Ramezani mentors students in projects like the NASA-funded “Crater Observing Bio-inspired Rolling Articulator” and oversees the SiliconSynapse Lab, which develops robots for space exploration and confined environments. Notable advisees include Henry Noyes, a NASA Space Technology Fellow. Labs/Teams : His lab collaborates with institutions like NASA’s Jet Propulsion Lab (JPL) on projects such as the Mars Multi-modal Morphing (M4) Rover and bio-inspired snake robots for lunar crater exploration.
Lingxi Li is a Professor at the Elmore Family School of Electrical and Computer Engineering at Purdue University's Indianapolis campus. His research focuses on modeling complex systems, connected and automated vehicles, intelligent transportation systems, and parallel intelligence. He holds a Ph.D. from the University of Illinois at Urbana-Champaign (2008), and master's and bachelor's degrees from the Chinese Academy of Sciences (2003) and Tsinghua University (2000). Research Interests: Dr. Li's work bridges control systems, transportation engineering, and AI, with emphasis on human-machine interaction, autonomous vehicle systems, and scenario-based traffic modeling. His projects include developing frameworks for Industry 5.0 collaboration, enhancing traffic flow prediction through parallel learning, and advancing safety in micro-mobility systems like e-scooters. Recent Publications: Over 15+ articles (2023-2025) explore topics such as game-theoretic vehicle interaction modeling, vision-language systems for autonomous driving, and acoustic SLAM technologies. These studies reflect a focus on real-world validation and system integration in smart transportation. Labs & Initiatives: Leads research in autonomous mining systems and scenario engineering for intelligent vehicles, leveraging parallel intelligence concepts. Collaborates on projects like ParallelWorkforce (Industry 5.0 frameworks) and SceNDD++ (naturalistic driving datasets).
Huy T Tran is an Assistant Professor in the Department of Aerospace Engineering at the University of Illinois at Urbana-Champaign's College of Engineering, with additional appointments at the Applied Research Institute. His research focuses on the intersection of robotics, artificial intelligence, and multi-agent systems, with applications spanning autonomous navigation, critical infrastructure resilience, and intelligent transportation. Dr. Tran earned his Ph.D. in Aerospace Engineering from Georgia Institute of Technology in 2015, following advanced degrees from Georgia Tech and University of Wisconsin-Madison. His academic journey includes research assistant professor positions before achieving his current assistant professor role in 2021. He previously worked as a Senior Multi-Disciplinary Systems Engineer at The MITRE Corporation and served as a Visiting Scholar at the Air Force Institute of Technology. His research interests encompass Autonomy, Reinforcement Learning, Artificial Intelligence, Machine Learning, Robotics, Multiagent Systems, Intelligent Transportation Systems, and Critical Infrastructure Resilience. As director of the Lab for Intelligent Robots and Agents (LIRA), he leads cutting-edge research in autonomous systems that interact with humans and other robots. His work has evolved from foundational resilience modeling in aerospace systems toward increasingly sophisticated AI applications in multi-robot coordination and explainable decision-making. Dr. Tran's publication record demonstrates a clear trajectory toward explainable AI and human-AI collaboration, with recent work focusing on generating explanations for reinforcement learning policies, coordination in ad hoc teams, and neuro-symbolic approaches to robot policy interpretation. His research bridges theoretical advances with practical applications in air traffic control, field robotics, and critical infrastructure management. Best Paper Award: Theoretical (2016 Complex Adaptive Systems Conference) Selected for oral presentation at IROS 2023 Workshop 27% full paper acceptance rate at AAMAS 2022 44% acceptance rate at ICRA 2020 As an educator, Dr. Tran teaches core aerospace courses including Computational Systems Engineering, Aerospace Numerical Methods, and Reinforcement Learning. He has secured significant research funding from NASA's Transformational Tools and Technologies program, ARL A2I2 program, ONR Science of AI program, and DARPA. His current projects span ad hoc teaming in multi-robot systems, collective autonomous air mobility, hierarchical reinforcement learning, and interpretable AI agents.
Dr. Horia Hangan is a Professor of Mechanical Engineering and Canada Research Chair in Adaptive Aerodynamics at Ontario Tech University's Faculty of Engineering and Applied Science. He holds an adjunct professorship at Western University. His research focuses on Experimental Fluid Mechanics, particularly bluff body aerodynamics, turbulent coherent structures, and aerodynamic control, with applications to buildings, vehicles, and aerostructures. He pioneered the WindEEE Dome, a unique facility simulating complex 3D wind flows, enabling studies of tornado-like vortices and non-Gaussian wind phenomena. Education: PhD in Wind Engineering from Western University (1996), Diplomat Engineering Degree in Aeronautics from the Polytechnic University of Bucharest (1985). Research interests include downburst dynamics, wind–structure interaction, and renewable energy. Over 150 publications span experimental and numerical studies of tornado-like vortices, downburst flows, and wind turbine performance. Notable awards include the CSME Fellowship (2016), ENR News Maker of the Year (2015), and the ASME Lewis F. Moody Award (2010). His work bridges fundamental aerodynamics with practical engineering solutions for wind-related challenges.
Professor Sara Bernardini is a leading academic in Artificial Intelligence at the University of Oxford's Department of Computer Science, where she holds a joint appointment as a Tutorial Fellow at Mansfield College. Her research specializes in decision-making for autonomous systems, automated planning, and robotics, with applications in extreme environments like space missions, nuclear decommissioning, and offshore energy. She bridges theoretical AI with real-world challenges through projects funded by Innovate UK, EPSRC, NERC, and the Alan Turing Institute. Her research interests span: Autonomous Systems : Developing agents that support humans in complex cognitive tasks. Automated Planning : Algorithms for goal recognition, pathfinding, and multi-agent coordination. Robotics : Solutions for subterranean exploration, offshore wind farms, and UAV operations. AI Safety : Risk-aware autonomous systems and interpretable decision-making. Bernardini's publications emphasize algorithmic robustness in path planning, multi-agent coordination , and real-world AI deployments . Recent work explores goal legibility in uncertain environments, energy-efficient robotics, and AI education tools. Her 65+ papers in top venues (e.g., AIJ, JAIR, ICAPS) show a trend toward safety-critical applications and human-AI collaboration. Awards & Leadership: ICAPS-2020 Best Paper Honorable Mention Executive Council Member, Association for the Advancement of Artificial Intelligence (AAAI) Program Chair, International Conference on Automated Planning and Scheduling (ICAPS 2024) Associate Editor, Artificial Intelligence Journal She leads interdisciplinary teams for projects like autonomous offshore wind farm maintenance and modular robots for extreme environments. As Principal Scientist at the UK National Oceanography Centre, she advanced marine robotics. She mentors PhD candidates and collaborates globally (e.g., NASA Ames, MIT).
