Dr James Herbert-Read is an Associate Professor and Whitten Lecturer in Marine Biology at the Department of Zoology, University of Cambridge. He serves as Deputy Head of Department (Postgraduate Education) and leads the Marine Behavioural Ecology Group. His research focuses on understanding how animals, particularly marine organisms, collect and process information from their environments to make behavioral decisions, with emphasis on social interactions, adaptation mechanisms, and ecological constraints. His group employs theoretical frameworks, controlled experiments, and quantitative field studies to investigate behavioral diversity in marine species. Key themes include collective behavior, predator-prey dynamics, camouflage strategies, and the impacts of environmental stressors on animal decision-making. Recent publications highlight work on lionfish vocalization mechanisms, cuttlefish camouflage, citizen science applications in marine research, and behavioral responses to visual and acoustic noise. Scientific awards and affiliations include: Whitten Lecturer in Marine Biology Associate Professor, University of Cambridge He has supervised research projects on topics such as: Social attraction in invasive fish species Evolution of coordinated movement Neurophysiological basis for leadership in shoals Maternal effects on offspring exploration
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.
Professor Bing Chu is an academic at the University of Southampton, actively contributing to research in control systems, robotics, and machine learning. They are a member of the Vision, Learning and Control Centre for Internet of Things and Pervasive Systems and the Centre for Robotics, focusing on interdisciplinary approaches that combine control theory with data-driven methodologies. Current research interests include: Iterative learning control Human-robot interaction Wind farm power optimization Robot behavior modeling Control system architectures Collaborative learning systems Recent publications highlight trends in data-driven control systems, human-robot interaction datasets, and optimization techniques for both continuous-time systems and wind energy applications. Professor Chu supervises multiple PhD students across robotics and electronic engineering, including Balint Gucsi, Haonan Shen, and Aleksander Wolski, while leading projects funded by Zhengzhou University and the Royal Society.
Professor Jing Meng is a leading academic at University College London's Bartlett School of Sustainable Construction, holding the position since 2023 after progressing from Lecturer (2019-2021) to Associate Professor (2021-2023). She concurrently serves as a fellow at the Cambridge Centre for Environment, Energy and Natural Resource Governance and maintains active editorial roles as Executive Editor of the Journal of Cleaner Production and Associate Editor for Journal of Geophysical Research: Atmospheres. Her research spans three interconnected domains: Energy Transitions and Technology Innovation (examining cost forecasts and structural emission declines in China), Climate Change Policies (analyzing South-South trade effects and multinational enterprise emissions), and Emission-Health-Socioeconomics Nexus (assessing air pollution impacts and integrated co-mitigation strategies). This interdisciplinary approach is reflected in her publication record across Nature family journals and PNAS. Analysis of her recent publications reveals a consistent focus on global carbon accounting methodologies, with increasing attention to subnational (city-level) analyses, health co-benefits of climate policies, and technological innovation pathways for hard-to-abate sectors. Her work frequently employs multi-regional input-output modeling to trace emissions through complex supply chains. AGU Global Environmental Change Early Career Award (2023) MIT Technology Review Innovators Under 35 Asia Pacific (2022) Clarivate Highly Cited Researcher (2020-2024) Nature Communications Top 50 Earth Sciences Article (2018) MDPI Emerging Sustainability Leader Award (2020) Environmental Research Letters Best Early Career Article (2017) Professor Meng has secured substantial funding from diverse sources including NERC, the British Council, Quadrature Climate Foundation, The Royal Society, and UCL internal grants. She leads an interdisciplinary research group focused on technology innovation and climate policy, with particular emphasis on China's role in global emissions systems. Her work directly supports Sustainable Development Goal 13 (Climate Action) through actionable policy insights.
Shih-Chii Liu holds the rank of Privatdozent (Associate Professor) in the Department of Information Technology and Electrical Engineering at ETH Zürich. He is affiliated with the Institute of Neuroinformatics , a joint institute between the University of Zurich and ETH Zurich. His research focuses on neuromorphic engineering, bio-inspired neural hardware, and edge computing systems, emphasizing energy-efficient algorithms and sensor technologies. Key research areas include neuromorphic sensors for real-time data processing, sparsity-aware neural networks, and adaptive computing architectures for edge devices. His work spans applications such as speech enhancement, wearable health monitoring, and bio-inspired keyword spotting systems. He leads the Sensors Research Group, which develops neuromorphic systems integrating novel sensors, spiking neural networks, and low-power hardware accelerators. Recent projects include the DeltaKWS low-power keyword spotting IC, EFLOP computational cost metrics for spiking networks, and NeuroBench benchmarking frameworks for neuromorphic systems. His contributions emphasize bridging biological neural principles with practical engineering solutions for IoT and embedded systems. Liu teaches courses such as Neuromorphic Engineering I and collaborates on cross-disciplinary projects involving neuroprosthetics, smart wearables, and multimodal sensor fusion. His work is characterized by hardware-software co-design approaches to tackle challenges in real-time, low-latency, and energy-constrained computing environments.
Declan Nolan is a Senior Lecturer in the School of Mechanical and Aerospace Engineering at Queen's University Belfast. He holds a PhD (2013) on 'Defining Simulation Intent,' focusing on automating simulation workflows. Before academia, he worked at Michelin, Williams F1 (as a Stress Engineer), and B/E Aerospace (Senior Structural Engineer), specializing in composite structures and structural integrity. He currently serves as Postgraduate Research Director (since 2022) and is a member of the EPSRC Early Career Forum in Manufacturing and the Circular Economy, and UKACM board member. His research spans design-to-simulation automation, bio-inspired design, and structural impact analysis. Key projects include PROTEUS (reimagining engineering design), COLIBRI (composite research), and Biohaviour (biological development analogies). He teaches Mechanics of Materials and Computer-Aided Engineering courses. Education: PhD in Mechanical and Aerospace Engineering (2013) Affiliations: Chartered Engineer, IMechE Member Grants/Projects: 4 active research grants, including EPSRC-funded initiatives Research outputs include 45+ publications, with recent focus on propulsion system integration, parametric nacelle modeling, and CAD-based machine learning. He has received two Best Paper Awards (2019) for manufacturing research contributions.
Dr. Todd D. Murphey is a Professor of Mechanical Engineering at Northwestern University's Robert R. McCormick School of Engineering and Applied Science. He serves as Director of Transformative Research and Director of the Master of Science in Robotics Program at Northwestern, leading initiatives in computational dynamics, control systems, and robotics. His work bridges engineering, neuroscience, and biomedical applications, with a focus on developing systems that interact effectively with humans and their environments. Dr. Murphey received his Ph.D. in Control and Dynamical Systems from the California Institute of Technology in 2002, with a thesis titled "Control of Multiple Model Systems." Prior to that, he earned a B.S. in Mathematics, summa cum laude, from the University of Arizona in 1997. Dr. Murphey's research centers on computational methods in dynamics and control, with applications spanning neuroscience, health science, robotics, and automation. His work in the Interactive & Emergent Autonomy Lab focuses on computational models of embedded control, biomechanical simulation, dynamic exploration, and hybrid control. The group develops mathematical approaches that lead to orders of magnitude improvement in computational efficiency for real-time implementation. Key application areas include assistive exoskeleton control, stabilization of energy networks, bio-inspired active sensing, entertainment robots, robotic exploration, and software-enabled stroke rehabilitation. Analysis of Dr. Murphey's recent publications reveals a strong emphasis on human-swarm interaction, algorithmic matter, and control of cyber-physical systems in uncertain environments. His work increasingly integrates information theory with physical systems, exploring how both autonomous and biological systems interact with environments to learn and improve behaviors. Recent trends show growing applications in rehabilitation technology, with particular focus on human-machine interaction in biomedical devices and embodied intelligence. Dr. Murphey has received numerous honors and awards for his contributions to robotics and engineering: Named Director of Transformative Research at Northwestern University (2025) Appointed IEEE Robotics and Automation Society Vice President of Publication Activities (2022) Co-recipient of Best Paper Award for IEEE Transactions on Robotics (2020) Appointed to Air Force Scientific Advisory Board (2019) Recipient of ABB Best Student Paper Award for CPL-SLAM research (2019) Cole-Higgins Award from Northwestern Engineering (2015) Dr. Murphey has supervised numerous graduate students including Taosha Fan, Giorgos Mamakoukas, and Ian Abraham, with research spanning robotic exploration using electrosense and mechanical contact, human-in-the-loop control, and shared control for rehabilitation devices. His lab has secured significant funding from the National Science Foundation, DARPA, and industry partners including Siemens and Ekso Bionics, supporting research in algorithmic matter, emergent behavior, and human-swarm collaboration. The Interactive & Emergent Autonomy Lab, led by Dr. Murphey, investigates how both autonomous systems and biological systems interact with their environments to learn and improve behaviors. Current projects include active learning and data-driven control, active perception in human-swarm collaboration, algorithmic matter and emergent computation, control for nonlinear and hybrid systems, cyber physical systems in uncertain environments, harmonious navigation in human crowds, information maximizing clinical diagnostics, reactive learning in underwater exploration, robot-assisted rehabilitation, and software-enabled biomedical devices. The lab collaborates with researchers across Northwestern and institutions including Georgia Tech, MIT, and industry partners.
Vishesh Vikas is an Associate Professor in the Department of Mechanical Engineering at the University of Alabama, College of Engineering. He is based in the South Engineering Research Center (SERC) and leads the Agile Robotics Laboratory (ARL@UA), which focuses on bio-inspired, soft, and tensegrity robotics, as well as inertial sensing and estimation. Education: PhD, Mechanical Engineering, University of Florida, 2011 MS, Mechanical Engineering, 2008 B.Tech., IIT Guwahati, 2005 His research spans autonomous systems, wearable technologies, biomedical devices, guidance and control, intelligent systems, space robotics, and engineering education . The lab’s work integrates mechanical design, sensing, and advanced control to create agile, adaptive robotic systems for unstructured environments. The recent publications highlight a strong trend in soft and tensegrity robotics , with focus on gait synthesis, locomotion planning, shape and joint estimation, and dexterous manipulation. These works combine modeling, data-driven control, and sensor fusion, often using accelerometers, IMUs, and vision for real-time feedback. The research is published in top robotics venues such as IEEE TRO, RA-L, and ASME journals. Scientific Awards: No awards explicitly mentioned in the text. Vishesh Vikas actively advises graduate students, including PhD and Master’s candidates, and has successfully guided several to thesis and dissertation completion. His lab is affiliated with multiple research centers including the Alabama Center for the Advancement of AI, Center for Advanced Manufacturing, and Center for Advanced Public Safety. He is involved in outreach and education, including mechatronics workshops and seminar hosting. Current projects include exosuits for spine support and robotic systems for mobility in extreme environments. Laboratory and Team: The Agile Robotics Lab (ARL@UA) fosters interdisciplinary research in nature-inspired robotics, combining principles from biology, mechanics, and control. The team has hosted eminent scholars and is featured in university and college news for its innovative work on wearable robotics and soft manipulators.
Prof. Sander Bohte is a part-time full professor of Computational Neuroscience at the University of Amsterdam (Swammerdam Institute of Life Sciences) and an honorary full professor of Bio-inspired Neural Networks at the University of Groningen. He serves as a Scientific Staff Member and Group Leader in the Machine Learning department at CWI, Amsterdam. His work bridges computational neuroscience and machine learning with a focus on continuous-time information processing. Key research interests include: Spiking Neural Networks with predictive coding and multi-compartment models Biologically Plausible Learning in recurrent and deep architectures Working Memory modeling via reinforcement learning Neuromorphic Computing for real-time systems and GPU acceleration His recent publications highlight trends in neural adaptation , predictive coding , and SNN hardware-software co-design . Awards include the Veni Innovational Research Grant (2004) and ERCIM grant (2013) . He actively supervises MSc theses and leads grants like the NWO KIC project 'Selfhealing Neuromorphic Systems' (2024).
Dr. Sheng Yang is an Assistant Professor in the School of Engineering at the University of Guelph. He leads the Design Innovation and Intelligent Manufacturing (DIIM) lab, focusing on advancing additive manufacturing, generative design, and smart manufacturing technologies. His research integrates IoT, big data analytics, and bio-inspired design to address challenges in aerospace, green energy, and healthcare. Key areas include computational design for additive manufacturing, data-driven mass customization, and digital twin-based optimization. Education: Ph.D. in Mechanical Engineering from McGill University (2019), followed by a Postdoctoral Fellowship at McGill (2019–2020). Joined University of Guelph in 2020. Research interests span energy efficiency, complex system optimization, and personalized healthcare products. Recent work emphasizes digital twin synchronization in robotics, machine learning for quality prediction, and sustainable additive manufacturing processes. Notable awards include the 2019 Association of Commonwealth Universities Blue Charter Fellowship and 2018 ASME Best Paper Award. His lab actively seeks partnerships in personalized healthcare, product design, and smart manufacturing. Grants and collaborations focus on advancing manufacturing technologies and sustainability. No formal advisees listed, but active in graduate training through lab projects. The DIIM lab explores cutting-edge solutions for industrial and societal challenges through interdisciplinary approaches.
Vivek Boominathan is an Assistant Research Professor in the Department of Electrical and Computer Engineering at Rice University. He is affiliated with the GLEE lab (Geometry, Light, & Imaging lab). His research focuses on computational imaging, combining computer vision, machine learning, applied optics, and nanofabrication to develop innovative imaging systems for applications such as robotics, medical sensing, and virtual/augmented reality. He has contributed to projects like PhlatCam (a lensless camera) and NeuWS (neural wavefront shaping). His work bridges optics, algorithms, and materials science to overcome traditional limitations in imaging systems. Boominathan's research interests include lensless imaging, optical meta-devices, turbulence mitigation, and bio-inspired imaging systems. He has developed systems like Foveated thermal imaging prototypes and real-time lensless microscopes. His lab emphasizes interdisciplinary approaches, integrating hardware design with machine learning. Key projects include: NeuWS: Neural wavefront shaping for imaging through scattering media CoIR: Compressive implicit radar for sensing applications FlatCam and PhlatCam: Ultra-thin lensless imaging devices Bioluminescence imaging in marine species His work has been published in top venues like Science Advances, Optica, and IEEE TPAMI. He collaborates with institutions like NASA JPL and industry partners on applied imaging solutions. Current research trends emphasize sensor-algorithm co-design and high-speed imaging systems for AR/VR applications. Boominathan holds a PhD in Electrical Engineering and has extensive postdoctoral experience in computational imaging. He advises projects in the GLEE lab and mentors students in hardware-software co-design for imaging systems. His lab focuses on translating theoretical innovations into practical devices with commercial potential.
Prof. Dr. Sarah Dégallier Rochat is Head of the strategic thematic field 'Humane Digital Transformation' at Bern University of Applied Sciences (BFH). She holds a joint appointment as Professor at the School of Engineering and Computer Science and serves as co-leader of the Computer Perception and Virtual Reality Lab (cpvrLab) within the Institute for Human-Centered Engineering. Her educational background includes: Ph.D. in Robotics from École Polytechnique Fédérale de Lausanne (EPFL) Master's in Mathematics from EPFL Teaching Diploma in Mathematics from Haute École Pédagogique de Lausanne Psychology studies at University of Lausanne Her research focuses on human-centered technological development with emphasis on: Designing inclusive human-machine interfaces through participatory approaches Developing upskilling strategies for industrial workforce adaptation Examining how techno-narratives shape societal perceptions of technology Creating collaborative robotic systems for agile manufacturing (Cobotics) Exploring mixed reality interfaces for worker augmentation Her publications demonstrate strong interdisciplinary focus on robotics and human-centered AI, with recent works exploring human augmentation in industry, ethical AI implementation, and participatory robot programming. The trajectory shows increasing emphasis on socio-technical systems and workforce empowerment. Significant awards include: Industry 4.0 Shapers Award (2019) CHIRA Best Paper Award (2023) She leads multiple research projects funded by Innosuisse, SNF, and EU programs, including: CODIMAN (Cobotics and workplace humanization) Agile Robotics for High-Mix Low-Volume Production Upskill at Work (digital literacy initiatives) Augmented workers with mixed reality interfaces As founder of Auto-Mate Robotics, she develops flexible robotic cells for industrial applications. She co-leads the Computer Perception and VR Lab and serves on advisory boards including the Swiss Cobotics Competence Center and EUA Task Force on AI.
Albert H. Titus is a Professor in the Department of Biomedical Engineering and an Adjunct Professor in the Department of Electrical Engineering at the University at Buffalo, State University of New York. He serves as Associate Vice President for Regulatory Support in the Office of the Vice President for Research and Economic Development. His research focuses on analog VLSI design for neuromorphic visual processing, biosensors, wearable devices, optoelectronic systems, and neural networks. Education: PhD in Electrical and Computer Engineering, Georgia Institute of Technology (1997) MS in Electrical Engineering, University at Buffalo (1991) BS in Electrical Engineering, University at Buffalo (1989) Research Interests: His work spans wearable and implantable sensors, bioinstrumentation, neural network-based visual processing, analog VLSI implementations, optoelectronics, and electronic packaging. He pioneered CMOS-based neuromorphic systems and developed patented technologies for glare sensing and RF power calorimetry. Publication Trends: His recent articles emphasize CMOS-integrated sensors, machine learning for bioimpedance analysis, implantable medical devices, and xerogel-based optical biosensors. These works bridge biomedical engineering and microelectronics. Scientific Recognition: He is a Fellow of the National Academy of Inventors and has received the SUNY Chancellor’s Award for Excellence in Service (2017), NSF CAREER award, and Western New York Inventor of the Year (2010). His inventions include a patented low-power glare sensor (U.S. Patent 7,586,079) featured in Popular Science’s 2011 Top Ten Inventions. Academic Leadership: As a faculty member, he has supervised nearly 20 PhD and over 40 MS students, while teaching courses in circuits, IC design, sensors, and signal processing across electrical and biomedical engineering disciplines.
Robert Laganière is a Professor at the School of Electrical Engineering and Computer Science at the University of Ottawa, where he has been actively contributing to the fields of computer vision and image analysis. He is a member of the VIVA research laboratory and holds a Ph.D. and M.Sc. from INRS-Telecommunications in Montreal, as well as a bachelor's degree in Electrical Engineering from École Polytechnique de Montréal. Bachelor's in Electrical Engineering: École Polytechnique de Montréal (1987) Master's Degree: INRS-Telecommunications (1990) Doctorate: INRS-Telecommunications (1996) Professor Laganière's research focuses on computer vision, with particular expertise in image and video analysis, visual surveillance, embedded vision systems, and deep learning applications. His work spans fundamental research in feature detection and matching to practical applications in autonomous driving, human recognition, and real-time object tracking. He has made significant contributions to the development of algorithms for pedestrian detection, age and gender recognition, and 3D object localization. His publication trends reveal a consistent focus on practical computer vision applications with a strong emphasis on real-time performance and embedded implementation. Over the past decade, his research has evolved from foundational work in feature matching and homography estimation toward more complex applications in action recognition, human-computer interaction, and intelligent surveillance systems. His work consistently bridges theoretical computer vision with practical engineering constraints, particularly for mobile and embedded platforms. Best Paper Award, IEEE International Conference on Computer and Robot Vision (CRV 2014) Best Paper Award, CVPR Embedded Vision Workshop, Providence, RI, June 2012 Best Real-time Tracker, IEEE International Conference on Computer Vision (ICCV) Workshop on Visual Object Tracking (VOT2015) Professor Laganière has supervised numerous graduate students through the years, with a particular focus on practical applications of computer vision in surveillance, human recognition, and embedded systems. His research has been supported through industry partnerships with companies including CogniVue Corp, NXP, iWatchLife.com, Solink Corp, CBSA Canada, Ross Video, Thales, Habitat Seven, and YouI Labs. He has successfully translated his research into commercial applications through his founding of Visual Cortek (acquired by iWatchLife in 2009) and Tempo Analytics (founded in 2016). As a member of the VIVA research laboratory, Professor Laganière collaborates with colleagues on advanced computer vision projects, particularly those involving intelligent video analytics for security and commerce applications. His work on NAVIRE (Virtual Navigation in Remote Environments) demonstrates his commitment to developing practical solutions for real-world navigation challenges using image-based representations of real environments.
Heikki Handroos is a Full Professor of Mechanical Engineering at LUT University, leading the Laboratory of Intelligent Machines since 1993. He holds a DSc (Technology) from Tampere University of Technology and has served as Vice-Dean of the Faculty of Technology (2007-2009) and currently chairs the Collegiate Body of LUT University. His research focuses on mechatronics, robotics, control systems, and fluid power, with over 300 publications and 2,400+ citations. He has supervised 34 doctoral theses and 150+ MSc projects, managed R&D projects exceeding €20M, and co-founded four tech startups. His work spans industrial collaborations, digital twin applications, and innovative robotics for nuclear energy (e.g., DEMO reactor maintenance systems). He has held visiting professorships in the U.S., Japan, and Russia, and actively contributes to academic editorial roles and professional societies like ASME and IEEE.
