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Sara AchourView profile

Assistant Professor

• Programming Languages
• Compilers
• Runtime Systems
• +2 more

Sara Achour is an Assistant Professor jointly appointed to the Computer Science and Electrical Engineering departments at Stanford University. She earned her PhD in Computer Science from MIT in 2021. Her research develops programming languages, compilers, and runtime systems for emerging analog computing platforms. Dr. Achour leads research in hardware-aware optimization frameworks and novel analog compute paradigms, with applications spanning quantum computing, IoT devices, and neuromorphic systems. Her research focuses on: Bridging software abstractions with unconventional hardware capabilities Energy-efficient computing paradigms for edge devices Cross-layer optimization of analog and hybrid computing systems Publication analysis reveals consistent themes in analog computing architectures, hardware-aware optimizations, and emerging computing platforms. Recent work explores quantum compilation techniques, hyperdimensional computing optimizations, and hardware security metrics. Dr. Achour advises multiple graduate students including: 16 doctoral candidates across computer architecture and quantum computing 10 master's students in software-hardware co-design She maintains active research collaborations through the Stanford SystemX Alliance.

Otar AkanyetiView profile

Senior Lecturer

• Bio-inspired Robotics
• Health Informatics
• Underwater Robotics
• +3 more

Dr. Otar Akanyeti is a Senior Lecturer in the Department of Computer Science at Aberystwyth University. His research integrates engineering, physics, computer science, and biology to advance underwater robotics and health informatics. He holds a BSc in Electronic Engineering, an MSc in Embedded Systems and Robotics, and a PhD in robot learning from the University of Essex. He co-founded the Aberystwyth Stroke Research Group and leads projects on AI-driven healthcare interventions. His research focuses on two primary strands: 1) Bio-inspired Robotics , developing sensors and control systems for underwater autonomy using biological principles; and 2) Health Informatics , employing wearable technology and AI to improve stroke rehabilitation and chronic disease management. Current investigations include hydrodynamic imaging, collective intelligence for data mining, and predictive tools for neurorecovery. Akanyeti's recent publications emphasize interdisciplinary approaches, with articles spanning gait analysis using smartphone sensors, clinical outcome prediction in stroke, and biomimetic robotics. His work consistently bridges biomechanics, machine learning, and clinical applications. He leads multiple funded projects including 'Miscanthus AI' (plant phenotyping for Net Zero), 'Intelligent Exercise Practitioner for Stroke Survivors', and 'iNavigate' (brain-inspired navigation technologies). His lab utilizes advanced equipment like instrumented treadmills and eye-tracking systems.

Alexander DittrichView profile

Researcher

• Robot Learning
• Hebbian Learning
• Bio-inspired Neural Network Architectures
• +4 more

Alexander Dittrich is a doctoral researcher at École Polytechnique Fédérale de Lausanne (EPFL) , affiliated with the School of Engineering and the Laboratory of Intelligent Systems . His work focuses on Hebbian learning , bio-inspired neural network architectures , and the simulation of tensegrity robots , with applications in deep reinforcement learning , meta learning , and neuroevolution . Recent publications include: (1) a 2025 RoboSoft paper on tensegrity-based robotic legs with variable stiffness (a Best Paper Finalist ), and (2) a 2023 ICRA paper on the AIMY table tennis ball launcher's high-level trajectory control system. These projects reflect his expertise in merging adaptive AI with soft robotics. Awards : Best Paper Finalist, RoboSoft 2025

Auke IjspeertView profile

Professor

• Robotics
• Computational Neuroscience
• Machine Learning
• +2 more

Auke Ijspeert is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), leading the Biorobotics Laboratory (BioRob). He earned a B.Sc./M.Sc. in physics from EPFL (1995) and a Ph.D. in artificial intelligence from the University of Edinburgh (1999). After postdoctoral work at IDSIA, EPFL, and the University of Southern California (USC), he returned to EPFL as an SNF assistant professor, becoming associate professor in 2009 and full professor in 2016. He holds primary affiliation with EPFL's Institute of Bioengineering and secondary affiliation with the Institute of Mechanical Engineering. 1995: B.Sc./M.Sc. in Physics, EPFL 1999: Ph.D. in Artificial Intelligence, University of Edinburgh 2002: SNF Assistant Professor, EPFL 2009: Associate Professor, EPFL 2016: Full Professor, EPFL His research explores the intersection between robotics, computational neuroscience, nonlinear dynamical systems, and machine learning. He develops robotic models to study animal locomotion principles and creates bio-inspired adaptive controllers. His work extends to assistive technologies like exoskeletons and smart furniture for mobility assistance. Notable publications include Science 2007 and 2014, and Nature 2019 with Nyakatura et al. He has received numerous awards, including: 2020: IEEE Fellow 2006: SNSF Professorship 1997: Marie Curie Scholarship 2024: IEEE ICRA Most Influential Paper Award 2019: CLAWAR Best Paper Prize 2018: SAB Best Conference Paper Award 2014: IEEE RO-MAN Best Paper Award 2007: IEEE Humanoids Best Paper Award 2002: ICRA Overall Best Paper Award Professor Ijspeert teaches courses in autonomous robotics, computational motor control, and legged robots at EPFL. He supervises numerous PhD students and contributes to editorial boards of leading journals in robotics and neuroscience. His laboratory investigates locomotion principles through robotic models and simulations, bridging biological understanding with technological innovation.

• Cybersecurity
• Cryptography
• IT Security
• +7 more

Assoc. Prof. Peter Schartner is an Associate Professor at the Department of Artificial Intelligence and Cybersecurity, Alpen-Adria-Universität Klagenfurt. He also serves as the Data Protection Officer, overseeing institutional compliance with data privacy regulations. His research focuses on cybersecurity, cryptography, and secure communication systems, with particular emphasis on automotive cybersecurity, quantum-resistant protocols, and secure exam environments. His work spans hardware security for embedded systems, privacy-preserving healthcare technologies, and IoT community-based security models. Notable contributions include developing the Secure Exam Environment (SEE) for online testing, cryptographic authentication methods, and quantum nonce mechanisms. He actively collaborates with the Trust Center to advance interdisciplinary security solutions. Research interests include: Cryptology, Digital Signatures, Information Security, Secure E-Business, and Cybersecurity in distributed systems. His projects often address practical challenges like functional safety in automotive control units and privacy in smart city technologies.

Mingjie LinView profile

Professor

• Bio-Inspired Computing
• Computer Architecture
• Robotics
• +5 more

Mingjie Lin is a Professor in the Department of Electrical Engineering and Computer Science at the University of Central Florida's College of Engineering. He received his Ph.D. in Electrical Engineering from Stanford University in 2008 and has established himself as a leading researcher in bio-inspired computing and robotic control systems. Dr. Lin's research interests span multiple cutting-edge domains including: Bio-Inspired Logic Design with Graph and Field Theory Minimum-Energy Bio-Inspired Computing with Emerging Spintronic Devices Hardware-Assisted Large-Scale Neuroevolution for Multiagent Learning and Robotic Control Computer Architecture/Compiler, and Reconfigurable Computing His ongoing research is primarily funded by NSF grants focusing on Bio-Inspired Logic Design, Minimum-Energy Bio-Inspired Analogic Computing Devices, and Metaphysical and Probabilistic-Based Computing Transformation. Dr. Lin leads the Autonomous Computing Laboratory at UCF, where his team develops algorithms for improving dynamic adaptability of robotic agents in high non-stationary environments through the fusion of artificial intelligence techniques and classical robotic control algorithms. Dr. Lin has received numerous prestigious awards for his work: UCF Reach for the Star Award (2017) UCF CECS Dean's Advisory Award (2017) UCF Teaching Incentive Program Award (2016) NSF CAREER AWARD (2016) SAIC Faculty Fellowship in Electrical Engineering At the Autonomous Computing Laboratory, Dr. Lin and his team are engaged in creating innovative approaches to robotic control, particularly focusing on Dynamic Amorphous Obstacle Avoidance (DAO-A) where robotic arms can dexterously avoid dynamically generated obstacles that constantly change their trajectories and 3D forms. Their methodology leverages topological manifold learning and deep learning for dimension reduction, enabling conflict-free human-robot interactions even in dynamically constrained environments.

Ghaith AndrowisView profile

Part-Time Lecturer

• Rehabilitation Robotics
• Wearable Technology
• Neuromotor Control
• +3 more

Dr. Ghaith Androwis is an Adjunct Instructor in Bio-Medical Engineering at NJIT, specializing in rehabilitation robotics and neurorehabilitation technologies. His research focuses on developing and evaluating robotic exoskeletons, myoelectric orthotics, and novel therapy tools for spinal cord injury, multiple sclerosis, and cerebral palsy rehabilitation. Current investigations include deep reinforcement learning for exoskeleton control, wearable sensor systems for motor recovery assessment, and vestibular stimulation techniques to enhance rehabilitation outcomes. He maintains clinical research partnerships with rehabilitation hospitals and conducts trials on robotic gait training and upper extremity functional recovery.

• Materials Engineering
• Aerospace Engineering
• Macromolecular and Materials Chemistry
• +3 more

Bronwyn Fox is an Adjunct Professor at Swinburne University of Technology, with a focus on materials engineering and manufacturing processes. She previously served as Deputy Vice-Chancellor (Research and Enterprise) and founded the Manufacturing Futures Research Institute to advance Industry 4.0 in Australia's manufacturing sector. Her expertise includes carbon fibre composites, sustainable materials, and advanced manufacturing technologies. Roles: Adjunct Professor, former Deputy Vice-Chancellor, and founder of the Manufacturing Futures Research Institute Key Contributions: Pioneered the Carbon Nexus facility at Deakin University, fostering industrial research collaboration Research Interests: Her work spans materials science, composite materials, and sustainable manufacturing. Key areas include carbon fibre composites, Industry 4.0 automation, and recyclable vitrimers. She emphasizes interdisciplinary collaboration to bridge materials innovation with industrial application. Awards: Fellow of the Academy of Technological Sciences and Engineering (ATSE), Fellow of the Royal Australian Chemical Institute (RACI), and Chair of the Victorian Division of ATSE. Grants & Supervision: Led projects funded by the Australian Research Council, Department of Industry, and industry partners like Boeing. Supervised numerous PhD students exploring topics such as composite materials, graphene applications, and structural batteries. Labs/Teams: Associated with Swinburne Research and collaborates on initiatives like the ARC Research Hub for Future Fibre Industry.

• Artificial Intelligence
• Robotics
• Evolutionary Computing
• +4 more

Kyrre Glette is a Professor at the University of Oslo's Department for Informatics, affiliated with the RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion and the Robotics and Intelligent Systems (ROBIN) research group. His work focuses on co-designing robot bodies and behaviors using AI methods, particularly through the open-source robotic platform DyRET. Research interests include evolutionary robotics, bio-inspired computing, and embodied AI. Research Groups: Robotics and Intelligent Systems (ROBIN) RITMO Centre of Excellence fourMs Lab Projects: COCOMO: Co-evolution of Control and Morphologies Multimodal Elderly Care Systems (MECS) Predictive and Intuitive Robot Companion (PIRC) His publications explore topics like evolutionary algorithms for morphological adaptation, embodied music interfaces, and neural mechanisms of auditory prediction. Advising focuses on MSc projects in evolutionary robotics and modular robot control.

Pim BouteView profile

Adjunct Professor

• Marine Biology
• Fisheries Sustainability
• Biomimetics
• +3 more

Pim Boute is an Externe medewerker (External Member) at the University of Groningen's Faculty of Science and Engineering , within the Biomimetics department. His research focuses on sustainable fishing technologies, marine organism behavior, and biomimetic engineering solutions. Key areas include electrotrawling sustainability, fish behavioral responses to electric fields, and hydrodynamic adaptations in boxfishes. He has contributed to international initiatives like the ICES Working Group on Electrical Trawling (WGELECTRA), advocating for environmentally friendly fishing practices. His work aligns with UN Sustainable Development Goals related to life below water and sustainable consumption. Boute has published extensively on electrotrawling's ecological impacts, comparing traditional beam trawls with pulse methods. Notable collaborations include studies on fish welfare, gear optimization, and bio-inspired filtration systems derived from manta rays. Boute actively engages in policy discussions, presenting findings in the European Parliament and contributing to media discourse on fisheries sustainability. He organizes international workshops, such as the Nature4Nature project's training modules on bioinspired design and numerical modeling. Key Projects: Electrotrawling sustainability reviews, biomimetic filtration prototypes, and fish injury studies. Media Outreach: Over 35 press mentions, including expert commentary on pulse trawling's environmental benefits. Labs/Teams: Collaborates with ICES and EU-funded networks, focusing on marine conservation and gear innovation.

Tjeerd V. olde ScheperView profile

Professor

• Dynamic Systems
• Neurocomputation
• Biological Systems Modeling
• +3 more

Dr. Tjeerd V. olde Scheper is a Professor and Research Lead in Computing at the School of Engineering, Computing, and Mathematics, Oxford Brookes University. He specializes in Dynamic Systems and Neurocomputation, focusing on biological problem-solving mechanisms and their applications in engineering, health, and medical fields. His notable contributions include the Rate Control of Chaos (patented) for stabilizing complex systems and Criticality Analysis for machine learning and biological data analysis. He leads the UG Computing Programmes and supervises PhD/MSc students in biomodelling and AI. Education: Holds MSc and PhD degrees in relevant disciplines (details unspecified). Active in research grants including DASA (£90k, 2020), Newton Fund (£97k, 2018), and multiple HEIF grants. Collaborates with institutions globally through projects like CARDIGAN (diabetic gait analysis) and [SENTIENT] (intelligent decision support). Research interests span bio-inspired control systems, nonlinear dynamics, and AI applications in healthcare. His work bridges computational models with real-world challenges in robotics, biomedical engineering, and environmental control (e.g., wind turbines, combustion engines). He contributes to interdisciplinary groups like CAVEPET, VAIL, and the Machine Learning & Robotics Group. Grants/Awards: Secured £90k+ from DASA and £97k+ from the Newton Fund. HEIF grants for wind turbine and engine control projects (2011–2012). Member of AAAS, IEEE, and neuroscientific societies. Consultancy roles include workshops on AI for diabetes and neural networks. Advising & Labs: Supervised Salman Khan (2023). Affiliated with CAICS, MOReS, DASOBU, and AIDAS. Leads projects like Map-to-Human Research Roadmap (NASA-funded, 2024–2026), emphasizing applied AI and movement science.

• Unmanned Aerial Vehicles (UAVs)
• Autonomous Systems
• Bird Damage Management
• +3 more

Dr. Zihao Wang is a Lecturer at the School of Aerospace, Mechanical and Mechatronic Engineering , University of Sydney. His research focuses on autonomous systems, particularly Unmanned Aerial Vehicles (UAVs) for agricultural pest control, with extensions into biomedical microfluidics and satellite technology. He holds a PhD (2021) on Intelligent UAVs for Pest Bird Control and a Bachelor of Engineering (Honours Class 1, 2014). Research Focus Dr. Wang’s work integrates aerospace engineering, biomimetics, and autonomous systems to solve real-world challenges. Primary domains include: Development of UAV-based bird deterrent systems using psychological warfare tactics Biomedical microfluidic platforms for thrombosis modeling Satellite attitude estimation and fault recovery systems Robotic aerial manipulation and perching mechanisms Publications Overview His multidisciplinary publications span UAV applications in agriculture (bird psychology, swarm systems), aerospace (satellite control, magnetorquers), and biomedical engineering (microfluidic thrombosis models). Recent work shows increasing convergence of autonomous systems with healthcare technology. Grants and Advising Grant (2022): Accelerating Australia's Space Innovation: Enhancements to the VR Flight Simulator (James N Kirby Foundation) Current Student : Advising Lucien on 3D Printing Molding Equipment for Pan-Space Specialty Environments Media Recognition Featured in The Newcastle Herald , Wine Australia , and Daily Democrat for pioneering UAV-based bird control solutions in vineyards.

Per HenningssonView profile

Researcher

• Aerodynamics
• Animal Flight Mechanics
• Biological Fluid Dynamics
• +3 more

Per Henningsson is a Researcher at Lund University's Department of Evolutionary Ecology and Infection Biology. His work focuses on the aerodynamics and flight performance of flying animals, particularly insects, birds, and bats. He leads a four-year project funded by the Swedish Research Council (VR), studying maneuvers in wind tunnel experiments using Particle Image Velocimetry. Previously, he was a postdoctoral researcher at Oxford University's Zoology department, investigating insect flight efficiency, and completed his PhD at Lund University on swift flight behavior using radar and high-speed filming. Education: PhD in Zoology (Lund University, 2005-2010), Postdoctoral Research (Oxford University, 2010-2013). Research emphasizes aerodynamic wake analysis, wing morphology, and flight mechanics. Current projects explore uncharted areas of maneuvering flight across taxonomic groups. Funding includes grants from VR and Carl Tryggers Stiftelse. Collaborations span international institutions, with outputs published in journals like Journal of the Royal Society Interface and Royal Society Open Science . His work bridges engineering and biology, aiming to elucidate foundational principles of animal flight for applications in robotics and ecology.

• Integrated Photonics
• Imaging Systems
• Medical Diagnostics
• +7 more

George Giakos is a Professor and Chair of the Department of Electrical and Computer Engineering at Manhattan College, NY, and Director of the Graduate Program. Previously, he served as a Professor at the University of Akron for over 20 years, directing imaging technologies and surveillance laboratories. His research focuses on imaging systems, photonics, medical diagnostics, and defense applications. Giakos holds a PhD from Marquette University and has authored over 200 peer-reviewed articles, 16 patents, and received prestigious awards including the IEEE Fellow distinction and the 2014 IEEE-USA Professional Achievement Award. Education Ph.D., Electrical & Computer Engineering, Marquette University M.S., Nuclear Physics, Ohio University Postgraduate Diploma, Nuclear Instrumentation, University of Edinburgh Laurea, Applied Physics, University of Turin Research Interests Giakos pioneers advancements in imaging devices and systems, integrating photonics, nanotechnology, and bio-inspired techniques. His work spans medical diagnostics (e.g., cancer detection via polarimetric imaging), defense (space surveillance, autonomous systems), and semiconductor characterization. He emphasizes interdisciplinary innovation, bridging defense and bioscience through novel imaging paradigms. Articles Overview Recent work includes neuromorphic architectures for space IoT, adversarial machine learning in power grids, and interdisciplinary frameworks for systematic innovation. His research often combines AI with domain-specific applications, addressing challenges in healthcare site selection, cybersecurity, and quantum sensing. Awards IEEE Fellow (2014) ONR Distinguished Faculty Fellow (2005) AFRL Space Surveillance Fellowships (2007–2009) NASA Faculty Fellowships (2000, 2001, 2004) Advising & Grants Giakos has secured over $6M in grants as PI, collaborating with AFRL, NASA, and industry partners like Lockheed Martin. His leadership spans IEEE committees, including chairing the TC-19 Imaging Systems Technical Committee and organizing international conferences like IEEE International Conference on Imaging Systems and Techniques. Labs & Teams Directs Manhattan College’s imaging and surveillance laboratories, advancing technologies such as multifusion polarimetric detection and bio-inspired robotic vision systems. His team develops platforms like the AFRL Multifunctional Imaging Surveillance system for defense and medical applications.

• Robotics and Automation
• Control Systems
• Biomedical Engineering
• +4 more

Dr. Tajdari is a distinguished researcher at Delft University of Technology, specializing in interdisciplinary fields at the intersection of robotics, control systems, and biomedical engineering. His work focuses on advanced control methodologies, non-rigid registration techniques for medical imaging, intelligent transportation systems, and personalized product design through digital fabrication. He has contributed significantly to the development of adaptive controllers for robotics systems, including Stewart platforms and surgical robots, as well as innovative approaches to 3D/4D human mesh registration for applications in healthcare and biomechanics. Key Research Areas: Autonomous Vehicles, Medical Robotics, Intelligent Transportation, 3D Reconstruction, and Human-Motion Analysis His recent research emphasizes integrating machine learning with traditional control theory to address challenges in traffic management, spinal deformity prognosis, and human-centered design. Collaborations include projects on smart infrastructure systems and personalized medical devices. Over 25 peer-reviewed articles demonstrate his expertise in both theoretical and applied engineering domains.