Dr. Danesh Tarapore is an Associate Professor at the University of Southampton specializing in robotics and AI. He focuses on human-robot interaction, swarm intelligence, and autonomous systems. His current research involves developing resilient robotic teams and optimizing learning algorithms for constrained environments. He supervises 6 PhD students in the iPhD MINDS and Computer Science programs. Dr. Tarapore's work bridges theoretical advancements with practical applications in autonomous navigation, multimodal dataset creation, and quality-diversity optimization. His publications span conferences like HRI and journals in robotics and AI. He collaborates with institutions like the University Hospital Southampton and the Boldrewood Innovation Campus. Research Interests: Human-robot collaboration, swarm systems, machine learning, and adaptive control Key Contributions: HRI-SENSE dataset, evolutionary subset selection algorithms, forest navigation frameworks Grants and Funding: Active projects in multi-agent systems and resilient robotics Dr. Tarapore maintains active roles in the robotics community through conference participation and interdisciplinary collaborations.
Pawel Ladosz is a Lecturer in Engineering Systems for Robotics at the Department of Mechanical and Aerospace Engineering, The University of Manchester. His research focuses on applying machine learning and computer vision to mobile robots, particularly in extreme environments such as total darkness or cluttered spaces. He is actively involved in developing autonomous navigation systems, wireless signal mapping, and high-level decision-making for robotic swarms. He teaches courses including Robotic Systems Design Project and Autonomous Mobile Robots. Education: PhD in Establishing and Optimising Unmanned Airborne Relay Networks (Loughborough University, 2014–2019) MEng in Aerospace Engineering (The University of Manchester, 2010–2014) Research Interests: Ladosz’s work emphasizes reinforcement learning for robotics, vision-based autonomous systems, and exploration in challenging environments. His projects often intersect with UN Sustainable Development Goals, contributing to innovations in robotic autonomy and sensor networks. Awards: He received the 2nd Autonomous Flying Technology Competition award in 2021, recognizing his contributions to autonomous flight systems. His research has also led to the establishment of the Centre for Robotic Autonomy in Demanding and Long-Lasting Environments (CRADLE), fostering cross-disciplinary collaborations. Grants & Projects: As Principal Investigator in the Aerospace Engineering initiative (2010–2035), he explores UAV communication networks and trajectory planning. His work addresses urban environment challenges, including relay positioning and signal prediction. Labs/Teams: Ladosz contributes to CRADLE, advancing robotic autonomy in extreme scenarios. His lab focuses on integrating AI and robotics for real-world applications.
Prof. Vinod Namboodiri is the Forlenza Chair in Health Innovation and Technology at Lehigh University's Department of Computer Science & Engineering and College of Health. He leads the Accessibility and Assistive Technologies (ACCESS) Lab, focusing on computing technologies to address health disparities affecting people with disabilities. His NSF-funded research develops navigation solutions for individuals with disabilities, with emphasis on smart communities and built environment accessibility. He holds a Ph.D. from UMass Amherst and previously served as Full Professor/Associate Director at Wichita State University and Adjunct Senior Scientist at Envision Research Institute. His research spans assistive technologies, applied computer vision, and smart health systems. Notable work includes MABLESim (indoor accessibility simulation), NaVIP (visually impaired navigation), and economic analyses of accessibility investments. His publications explore both technical innovations and policy implications of assistive technologies. Prof. Namboodiri has received multiple awards for research, teaching, and innovation. His work bridges computer science with disability studies, emphasizing real-world impact through interdisciplinary collaboration. Current projects address indoor navigation systems, cost-benefit analysis of accessibility infrastructure, and human-agent interaction platforms for disability empowerment.
David Schlipf is a Professor at the Fachbereich Energy and Life Science, Hochschule Flensburg, leading the Wind Energy Technology Institute. His expertise spans lidar-assisted control systems, floating offshore wind turbines, and aeroelastic modeling. He actively collaborates with international initiatives like IEA Wind Task 32 and contributes to projects such as the 'Lidar Knowledge Europe (LIKE)' network. His research focuses on enhancing wind turbine efficiency through advanced control strategies and sensor technology integration. He has been instrumental in developing the TorqTwin open-source framework for multibody modeling and has published extensively on topics including wind field reconstruction, load mitigation, and floating platform dynamics. His work bridges academic research with industrial applications, emphasizing practical solutions for offshore wind energy challenges. Notable projects include the evaluation of lidar-assisted control performance, optimization of floating turbine designs, and contributions to wind energy education's role in climate resilience. His research outputs span over 200 publications, highlighting his global impact in advancing renewable energy systems.
Colin Britcher is a Professor in the Department of Mechanical & Aerospace Engineering at Old Dominion University (ODU), affiliated with NASA Langley and the National Institute of Aerospace. He has held roles including Deputy Director for Education at AIAA Region I and led the Center for Experimental Aeronautics. His research focuses on wind tunnel test techniques, magnetic suspension systems, and experimental aerodynamics, with applications to planetary entry capsules and drone stability. Education: Ph.D. in Aeronautics and Astronautics, Southampton University (1983) B.S. in Aeronautical Engineering, University of Southampton (1978) Research Interests: Wind tunnel design and dynamic stability testing Magnetic suspension systems for aerodynamic measurements Unmanned aerial vehicles (UAVs) and propeller aerodynamics Boundary layer effects and flowfield analysis His recent work includes developing wind tunnel techniques for multi-rotor drones and planetary entry vehicles, as well as textbook authorship on wind tunnel design. Grants & Awards: $1.04M Virginia Institute for Performance Engineering grant (2023) Leadership in $355K NIA Director of Graduate Programs role (2014–2017) 2004 NASA Honorary Superior Accomplishment Award 1995 NASA Turning Goals into Reality (TIGR) Award Labs & Collaborations: Collaborates with NASA Langley on magnetic suspension systems Developed the NASA/ODU 6-inch Magnetic Suspension and Balance System (MSBS)
Soufiene Djahel is a Professor at the Centre for Future Transport and Cities (CFTC) at Coventry University, UK. His research focuses on connected and autonomous vehicles (CAVs), unmanned aerial vehicles (UAVs), cyber security, and smart cities. He holds a PhD in Secure Routing and Medium Access Protocols from Université des Sciences et Technologies de Lille (2010), and has held academic positions including Senior Lecturer at the University of Huddersfield and Manchester Metropolitan University. His research interests include CAV coordination protocols, cyber-physical security solutions, and intelligent transportation systems. Djahel leads projects such as the £1.2M AeroPharma Logistics initiative and has secured funding from the Newton Fund and JSPS. He is a recipient of the 2021 JSPS Invitational Fellowship and has published extensively in IEEE journals and conferences. Current projects explore UAVs-as-a-service, digital twins for CAVs, and B5G/6G for smart infrastructure. He advises PhD students on topics like AI-based threat mitigation and transport electrification. Djahel also serves as an external examiner and editorial board member for journals like IEEE Transactions on Intelligent Transportation Systems.
Tina Comes is a Full Professor in Decision-Making & Digitalisation at the University of Maastricht, Netherlands. She holds a part-time position (0.2 FTE) and has previously held academic roles at TU Delft (Associate Professor in Decision-Making for Resilience, 2017), University of Agder (Full Professor in ICT, 2015-2017), and Visiting Professor at Lamsade, Université Dauphine, Paris (2014). Her research focuses on Crisis Informatics , Decision Theory , Disaster Management , Humanitarian Logistics , and Resilience . Her work spans building simulation , ventilation systems , and energy-efficient design , with grants totaling €9.6 million since 2012. Key projects include Resilient Systems (NL Ministry of Defense, 2020-2026), H2020 HERoS (2020-2023), and Climate Resilient Urban Infrastructure (Amsterdam, 2020-2022). She has supervised 6 PhD students at TU Delft (2017-2022), 3 Postdocs/PhDs at University of Agder (2013-2020), and 1 PhD at Université Toulouse (2014-2018). Her scientific awards include: 2020 José Maria Sarriegi Award by the Spanish Red Cross 2019 Emerald Literati Award 2016 Delft Technology Fellowship (acceptance rate 2012 Best Paper Award at ISCRAM Conference
Dr. Vagelis Papalexakis is an Associate Professor and Ross Family Chair in the Computer Science & Engineering Department at the University of California, Riverside. His research focuses on data science, machine learning, and tensor methods, with applications in multi-aspect/multi-modal data analysis. He holds a Ph.D. from Carnegie Mellon University and a Diploma/M.Sc. from the Technical University of Crete. Affiliations: Ross Family Chair, Bourns College of Engineering, UCR Education: Ph.D. in Computer Science, Carnegie Mellon University M.Sc./Diploma in Electronic & Computer Engineering, Technical University of Crete His work emphasizes interpretable insights from complex datasets, including tensor-based defenses against adversarial attacks, graph representation learning, and scalable algorithms for high-dimensional data. Notable awards include the NSF CAREER Award (2021), IEEE DSAA Next Generation Award (2021), and ICDM Tao Li Award (2022). Grants include NSF funding for railway safety (CISE MSI: RPEP CPS), USDOT transportation research, and NVIDIA GPU grants. He leads projects in AI ethics, misinformation detection, and gravitational wave analysis. His lab collaborates with industry (e.g., Cisco, Instacart) and national labs (e.g., Lawrence Livermore).
Tina Shoa is an Associate Professor in the School of Sustainable Energy Engineering at Simon Fraser University. She holds a Ph.D. in Electrical Engineering from the University of British Columbia (2010), an M.Sc. from the University of Manitoba (2004), and a B.Sc. from Iran University of Science and Technology (2000). Her research focuses on battery performance modeling, electrochemical methods for fault detection, sustainable battery manufacturing, and AI-based diagnostics. Education: Ph.D., Electrical Engineering, University of British Columbia, 2010 M.Sc., Electrical Engineering, University of Manitoba, 2004 B.Sc., Electrical Engineering, Iran University of Science and Technology, 2000 Research Interests: Battery performance modeling, analysis, and optimization Electrochemical and ultrasound-based battery fault detection Sustainable battery manufacturing processes AI-driven battery diagnostics Teaching and Courses: Advanced Battery and Fuel Cell Technologies Power Plant Systems Smart Grids Practicum SEE 354 D100 Energy Storage (Summer 2025) Patents: Battery State-of-health Determination upon charging (US Patent 11079437B2, 2022) Battery State-of-health Determination using multi-factor normalization (US Patent 10,302,709, 2019) Apparatus and Method for testing electrochemical systems (US Provisional Patent 62/994687, 2020) Key Contributions: Her work integrates electrochemical principles and AI to advance battery diagnostics and sustainable energy storage solutions. She has authored over 15 publications in top-tier journals and conferences, addressing battery aging, state estimation, and novel manufacturing techniques.
Liuping Wang is a Professor in the School of Electrical and Computer Engineering at RMIT University, Australia, since 2007. He serves as Head of Discipline for Electrical Energy and Control Systems since 2005 and teaches Advanced Control Systems (EEET 2100) and Real Time Estimation and Control (EEET 2221). Current academic rank: Professor Location: City Campus, Australia Industry collaborators: ANCA, Australian Power Academy, Advanced Manufacturing CRC His research interests span: Control Theory with applications to UAVs and industrial processes Development of Model Predictive Control systems System Identification using neural networks Robust Control for constrained systems Control of AC motors and power electronics Applications in biomedical research and food process monitoring The 15 most recent publications (2015-2025) demonstrate expertise in: UAV control systems with segmented surfaces Battery condition monitoring for electric vehicles Mult-agent robotics with coordination algorithms Smart grid security and electricity dispatch GPS-denied localization for mobile robots Disturbance observer control with input constraints As a supervisor, he oversees Masters Research and PhD projects but no specific student names are listed. His email is liuping.wang@rmit.edu.au for collaboration or supervision inquiries.
Professor Klaus McDonald-Maier is a full Professor in the School of Computer Science and Electronic Engineering (CSEE) at the University of Essex , where he leads the Embedded and Intelligent Systems (EIS) Research Laboratory and heads the Intelligent Embedded Systems and Environments Research Group . He is also Director of Impact , Visiting Professor at the University of Kent, and Visiting Research Affiliate at NASA Jet Propulsion Laboratory, California Institute of Technology. Education PhD in High-Performance Parallel Neural Network Architectures, Friedrich-Schiller-University Jena (Germany, 1999) Electronic Engineering studies, University of Ulm (Germany) Electronic Engineering studies, Cardiff University (Wales) Electronic Engineering studies, École Supérieur de Chimie Physique Électronique de Lyon (CPE-Lyon) (France) Research Interests Professor McDonald-Maier’s research integrates embedded systems , System-on-Chip (SoC) architectures , and AI-driven robotics . He pioneers visual place recognition techniques that remain robust under severe appearance and viewpoint changes, develops cybersecurity frameworks based on ICMetrics for autonomous vehicles and IoT, and designs approximate real-time computing solutions for energy-constrained multicore and FPGA platforms. His work on radiation-tolerant systems supports space and nuclear applications, while his bio-inspired algorithms enable lightweight, neuromorphic perception on resource-limited robots. Publication Trends Between 2022 and 2025 his output converges on FPGA-accelerated AI , secure edge intelligence , visual navigation for autonomous systems , and healthcare analytics . He repeatedly couples rigorous algorithmic innovation with practical hardware deployment, yielding energy-efficient, real-time systems validated in domains ranging from autonomous driving to post-stroke rehabilitation. Scientific Awards & Recognition Best Paper Award – IEEE Transactions on Sustainable Computing (2024) Best Paper Award – IEEE/ACM DATE (2024) Best Paper Award – IEEE Systems Journal (2022) Best Paper Award – IEEE Sensors Journal (2021) Best Paper Award – IEEE Access (2020) Research Grants & Industrial Collaboration He has secured major funding from EPSRC , EU Horizon 2020 , Innovate UK , and industry partners. Current projects span trustworthy autonomy, radiation-hardened edge AI, and AI-enhanced rehabilitation technologies. He is Chief Scientist of UltraSoC Technologies Ltd and CEO of Metrarc Ltd , commercialising University research in semiconductor debug and cybersecurity respectively. Laboratory & Team Leadership As Director of the Embedded and Intelligent Systems Laboratory (EIS Lab) , he oversees a multidisciplinary team of researchers and PhD students, providing state-of-the-art FPGA, robotics, and embedded-systems facilities. The lab collaborates closely with NASA JPL, UK Atomic Energy Authority, and leading semiconductor firms to translate fundamental research into high-impact industrial solutions.
Philippe Moireau is a Full Professor in the Department of Applied Mathematics at École Polytechnique, where he is also affiliated with the Center for Applied Mathematics (CMAP). He serves as the head of the Inria Project-Team MΞDISIM (Mathematical and Mechanical Modeling with Data Interaction for Simulation in Medicine) and holds the distinguished position of Ingénieur Général of The Corps des Mines. His primary research focuses on inverse problems and data assimilation for partial differential equation models, with particular emphasis on: Observer-based methods from optimal control perspectives Stabilization approaches for evolution equations Numerical analysis of time-dependent control problems Digital twin applications in cardiovascular medicine Professor Moireau's publication portfolio demonstrates consistent focus on mathematical methods for physical systems, with recurring themes in: Data assimilation techniques for PDE-based models Numerical stabilization and discretization methods Cardiovascular biomechanics and hemodynamics Stochastic modeling of biological systems Epidemiological forecasting and control He leads the ANANKΞ project-team at Inria focused on Analysis And Numerics of physical-Knowledge-based Estimation. His educational contributions include lectures on data assimilation theory at CEMRACS and courses on mathematical modeling in cardiac biomechanics at Institut Polytechnique de Paris.
Prof. Ahmed Al-Dubai is a Professor at the School of Computing, Engineering and the Built Environment, Edinburgh Napier University, where he leads the IoT and Networked Systems Research Group and serves as Cybersecurity and Cyber Physical Systems Research Lead. His interdisciplinary research spans Multi-access Edge Computing, High-Performance Networks, Cognitive IoT Systems, VANETs, AI, E-Health, Smart Cities, and Security . He earned his PhD in Computing Science from the University of Glasgow in 2004. His recent publications focus on edge computing architectures, digital twin security, Arabic NLP, wireless energy harvesting, and vehicular communication . His work has been recognized with IEEE Outstanding Service Award, Best Paper Awards at IEEE IUCC 2015 and ACM MoMM 2013 , and fellowships like Senior IEEE Member and British Higher Education Academy Fellow . He supervises 20+ PhD students and has served on 60+ IEEE/ACM conference committees. Current projects include AI-driven fish identification (Innovate UK £265K) , secure IoT protocols (Royal Society £12K) , and COG-MHEAR (EPSRC £3.26M) . He has held visiting professorships at Universite de Valenciennes, University of Sydney, and University of Shenyang.
Dr. Kang Liang is a Scientia Associate Professor at the University of New South Wales (UNSW Sydney), specifically within the School of Chemical Engineering. He leads the Nano-Micro-Bio Systems research group and serves as Co-Chair of the Australian Synchrotron Program Advisory Committee for SAXS/WAXS and BioSAXS. His research focuses on the intersection of nanotechnology, biocatalysis, and materials science, with particular expertise in metal-organic frameworks and their applications in biomedical and environmental contexts. Dr. Liang's research interests center around interfacial engineering of nanostructured materials, NanoBionics, biomimetics and biomineralization, and smart nano-micro-bio systems. His work explores how nanomaterials can interface with biological systems to create innovative solutions for healthcare, environmental monitoring, and energy applications. He has made significant contributions to the field of biocatalytic metal-organic frameworks, demonstrating their potential in drug delivery, cytoprotection, and cell manipulation. His publication record shows a strong focus on developing advanced nanomaterials with applications spanning from environmental remediation (water purification, contaminant removal) to biomedical applications (drug delivery, biosensing, cancer treatment). The trends in his recent publications indicate increasing sophistication in the design of nanomotors and nanoswimmers, with growing emphasis on precision targeting, multi-functionality, and integration with biological systems. Victoria Fellowship in Physical Sciences (2017) Fellow of the Australian Royal Chemical Institute (FRACI) Fellow of the Royal Society of Chemistry (FRSC, UK) NHMRC Career Development Fellow (2019-2022) ARC Future Fellow (2023-2027) Dr. Liang actively mentors PhD and MPhil students through his research group and encourages highly motivated candidates to join his team. His research is supported by significant funding including his current ARC Future Fellowship (2023-2027). His work bridges chemical engineering, materials science, and biomedical applications, creating a unique interdisciplinary approach to solving complex problems in healthcare and environmental sustainability. His laboratory focuses on developing innovative nanomaterial platforms that interface with biological systems, with particular emphasis on creating responsive and adaptive systems that can perform specific functions when triggered by environmental conditions. The group's work represents a cutting-edge intersection of nanotechnology, bioengineering, and materials science.
Professor Francois Ladouceur is a distinguished academic at the University of New South Wales (UNSW), where he serves in the Faculty of Engineering, specifically within the School of Electrical Engineering and Telecommunications. With a career spanning over three decades, Professor Ladouceur has established himself as a leading expert in photonics, optical engineering, and neural interfaces. His educational background includes: Ph.D. in Optical Communication from The Australian National University (1992) Masters in Solid State Physics from École Polytechnique, Montréal, Canada (1987) B. Eng. in Engineering Physics from École Polytechnique, Montréal, Canada (1985) Professor Ladouceur's research spans several cutting-edge areas in photonics and optical engineering. His work focuses on integrated optics, silica and diamond-based photonics, optical sensing networks, and photonics-based brain/machine interfaces. He has made significant contributions to both fundamental waveguide theory and applied integrated optics, introducing innovative approaches to waveguide path design that have improved the size and ease of design of integrated optics devices. His recent work has particularly emphasized the development of liquid crystal-based optical electrodes for neural interfacing and brain/machine interfaces. Analysis of his recent publications reveals a strong trend toward biomedical applications of photonics, particularly in neural interfaces and optrode technology. His research has evolved from fundamental optical engineering to practical applications in healthcare, with a focus on developing novel optical sensing technologies for electrophysiological measurements. The interdisciplinary nature of his work combines optical engineering, materials science, and biomedical engineering to create innovative solutions for neural interfacing. Professor Ladouceur has secured significant research funding through multiple prestigious grants: ARC Discovery (DP200102825): "A Multi-Optrode Array for Closed-Loop Bionics" ($495k) NHMRC Ideas Grant (APP2002282): "Re-engineering the Future of Electrophysiological Measurements" ($732k) ARC Discovery 2016 (DP160104625): "Design of an optrode for next generation brain-machine interfaces" ($457.6k) CRC Project 2016: "High performance optical telemetry system for ocean monitoring" ($1,014,320) US Office of Naval Research: "Multi-Optrode Array for Neural Interfacing" (US$360,000) Professor Ladouceur has extensive experience in translating research into practical applications, having founded Bandwidth Foundry Pty Ltd after raising approximately $20 million from private and public sources. His work bridges the gap between academic research and commercial applications, with a particular focus on developing novel hybrid opto-electronics devices from initial design through to commercial realization. He collaborates extensively with researchers across disciplines, particularly with Professor Nigel Lovell and other colleagues in biomedical engineering. His laboratory focuses on developing optical technologies for neural interfaces, with current projects including multi-optrode arrays for brain-machine interfaces, optical telemetry systems for various sensing applications, and diamond-based photonic structures. The research group maintains strong connections with industry partners and defense organizations, applying photonics solutions to real-world problems in healthcare, mining safety, and ocean monitoring.
